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Open Access

Peer-reviewed

Research Article

How do project managers’ competencies impact project success? A systematic literature review

Roles Conceptualization, Supervision, Writing – review & editing

* E-mail: [email protected]

Affiliation ESPAE Graduate School of Management, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador

Roles Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Roles Investigation, Methodology, Software, Writing – original draft

Roles Conceptualization, Formal analysis, Writing – review & editing

Roles Writing – review & editing

• Paola Ochoa Pacheco, 
• David Coello-Montecel, 
• Michelle Tello, 
• Virginia Lasio, 
• Alfredo Armijos

• Published: December 7, 2023
• https://doi.org/10.1371/journal.pone.0295417
• Peer Review
• Reader Comments

Despite the existence of systematic literature reviews focused on examining the factors contributing to project success, there remains a scarcity of reviews addressing the relationship between the project managers’ competencies and project success. To fill this gap in the literature, this review aimed to evaluate peer-reviewed articles, published between 2010 and 2022, and analyze the impact of project managers’ competencies on project success. The Web of Science, Scopus, ScienceDirect, and ProQuest electronic databases were first consulted in September 2021, with an update in August and October 2022. A total of 232 titles were analyzed. Ten articles met the criteria and were fully reviewed. A content analysis and a citation network were carried out to analyze the included articles. The analysis revealed that the existing literature has primarily explored the influence of competencies from the personal and social dimensions, such as leadership, communication, and emotional intelligence, on project success. Conversely, competencies from other dimensions have received less attention in the literature. In addition, this review contributes to the literature by providing a holistic categorization of competencies associated with project success and examining and organizing project success criteria into three dimensions.

Citation: Ochoa Pacheco P, Coello-Montecel D, Tello M, Lasio V, Armijos A (2023) How do project managers’ competencies impact project success? A systematic literature review. PLoS ONE 18(12): e0295417. https://doi.org/10.1371/journal.pone.0295417

Editor: Jamshid Ali, University of Tabouk: University of Tabuk, SAUDI ARABIA

Received: July 19, 2023; Accepted: November 21, 2023; Published: December 7, 2023

Copyright: © 2023 Ochoa Pacheco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data are available either within the manuscript (Tables 1 , 2 , 3 , 4 ) or as supplementary files . Hyperlinks are provided within the manuscript in the reference list.

Funding: The authors received no specific funding for this work.

Competing interests: The authors declare no conflict of interest.

1. Introduction

The profound economic, technological, and social changes experienced in recent years [ 1 , 2 ] have compelled organizations to devise strategies and implement initiatives to adapt to uncertain environments [ 3 ]. Projects allow organizations to face these challenges by leveraging their expertise and capabilities to deliver solutions aligned with business objectives [ 4 ]. Project management (PM) has been acknowledged as a valuable discipline for managers and professionals implementing strategic organizational transformations [ 1 ]. Given the shortage of qualified talent to execute strategic initiatives and drive change [ 5 ], the project managers’ (PMGs) competencies have garnered significant attention from scholars [ 6 – 11 ] and PM institutions [ 12 , 13 ]. Consequently, a substantial body of literature has devoted considerable effort to delineating the competencies that have the potential to enhance projects’ positive outcomes [ 14 – 18 ].

There has been a growing interest in exploring the individual and organizational factors contributing to project success (PS). At the individual level, the PMGs’ leadership style [ 19 ], job satisfaction [ 20 ], trust [ 21 ], job crafting [ 22 ], and work-family conflict [ 23 ], among other factors have been associated with PS. At the organizational level, scholars have highlighted that PS can be influenced by innovative climate [ 24 ], organizational culture [ 25 ], cultural diversity [ 26 ], governance [ 27 ], knowledge sharing and perceived trust and cohesion of the team [ 28 , 29 ], among others.

Despite the existence of systematic literature reviews (SLRs) that summarize the available evidence regarding factors associated with PS [ 30 ], there remains a scarcity of SLRs focusing on PMGs’ competencies [ 31 , 32 ] and their impact on PS. Only a limited number of SLRs [ 33 ] have been dedicated to identifying the competencies essential for achieving PS. However, to the best of our knowledge, an SLR focused on analyzing the relationship between PMGs’ competencies and PS has not been conducted before. To fill this gap in the literature, this SLR analyzes the existing evidence regarding the relationship between PMGs’ competencies and PS. Therefore, the present SLR was designed to address the following research questions: (RQ1) Which PMGs’ competencies are the most examined in the existing literature? (RQ2) Which success criteria are the most considered when measuring PS in the existing literature? (RQ3) Which PMGs’ competencies have a relationship with PS?

This SLR contributes to the literature on the PM discipline in four ways. Firstly, it fills a gap in the existing literature by employing the SLR methodology to comprehensively synthesize the available evidence from published empirical studies concerning the relationship between PMGs’ competencies and PS. Secondly, it employs a thematic analysis and a holistic perspective to categorize the PMGs’ competencies associated with PS. This methodological approach provides a comprehensive framework for understanding the diverse competencies relevant to PS. Thirdly, it offers an insightful analysis of a graphical representation that showcases the primary authors and institutions that have significantly influenced the conceptualization of PMGs’ competencies. Lastly, it examines the criteria utilized for measuring PS in the included articles and organizes them into three dimensions, enhancing the understanding of the multifaceted nature of PS assessment. By addressing these aspects, this SLR contributes to advancing knowledge in PM.

The subsequent sections of this paper are structured as follows. Section 2 presents the conceptualization of PMGs’ competencies and PS. Section 3 outlines the procedure for conducting the SLR, encompassing the search strategy, study selection, data extraction, and analysis. The findings derived from the SLR are presented in Section 4. Lastly, the paper concludes by discussing the implications of the results, highlighting the strengths and limitations of the SLR, and offering final remarks.

2. Competencies and project success

This section provides an overview of the conceptualizations of competencies adopted in the PM literature, and briefly discuss the evolution of the PS dimensions.

2.1. Competencies

Various conceptualizations of competencies have been explored in the existing literature [ 16 , 34 – 38 ]. Within the PM discipline, several studies [ 18 , 39 – 42 ] have aligned with the classical definition proposed by Boyatzis [ 35 ]. According to his framework, competencies encompass the underlying characteristics of an individual, including knowledge, skills, abilities, attitudes, and more, that collectively enable the achievement of high performance. These elements have served as a foundational basis for scholars [ 9 , 43 , 44 ] and institutions [ 12 , 13 ], who have further expanded the scope to develop frameworks tailored explicitly to the domain of PM.

PM institutions, including the Project Management Institute (PMI) and the International Project Management Association (IPMA), have played a crucial role in the definition and development of various standards and frameworks that pertain to the competencies of PMGs [ 45 ]. Several studies [ 16 , 46 , 47 ] have employed these institutional standards to define competencies. The next paragraph provides a concise overview of these institutional frameworks.

According to the IPMA [ 13 ], competencies comprise the practical application of knowledges, skills, and abilities to achieve desired outcomes. This framework recognizes the interconnectedness of these elements, as proficiency entails acquiring relevant knowledge and developing skills that, when put into practice, enable professionals to manage projects effectively and successfully. Similarly, the PMI [ 12 ] defines competencies as the capability to carry out activities within a portfolio, program, or project setting that yield anticipated results based on established and accepted standards. This definition builds upon Boyatzis’ [ 35 ] elements and aligns with the IPMA [ 13 ] perspective, but it also emphasizes compliance by acknowledging the significance of adhering to current regulations and guidelines to meet stakeholders’ expectations. More recently, the PMI [ 48 ] introduced the concept of power skills , which refers to the abilities and behaviors that facilitate working with others and enable project professionals to succeed in the workplace, align projects to organizational objectives, and motivate teams to contribute value to the organization and its customers.

The scholarly literature [ 8 , 37 , 43 , 44 ] has significantly contributed to the conceptualization of the competencies required by PMGs by incorporating key elements from the PM discipline. For instance, Hanna et al. [ 43 ] emphasized the evolving nature of projects. They argued that competencies entail the demonstrated ability to perform project activities within a dynamic environment, leading to expected outcomes based on established standards. Building upon this perspective, Bashir et al. [ 44 ] defined competencies as a meta-ability that integrates skills, aptitudes, and abilities to perform throughout the project life cycle, from initiation to closing, intending to achieve expected results. Moreover, Crawford [ 49 ] posited a close relationship between PMGs’ competencies and PS. Recent literature has underscored the pivotal role of PMGs’ competencies in attaining higher levels of success, enhancing efficiency and effectiveness, and consequently increasing the likelihood of PS [ 8 ].

2.2. Project success

This section provides an overview of the historical development of the conceptualization of PS, tracing its progression from a unidimensional to a more comprehensive and multidimensional concept [ 50 ]. It also aims to identify the dimensions and criteria incorporated into the concept in recent years. Furthermore, it defines PS and examines its distinctions from related concepts, such as project performance and efficiency.

Traditionally, scholars [ 39 , 51 – 53 ] have viewed PS as a combination of success factors and criteria. On the one hand, success factors refer to the significant elements that enhance the probability of achieving success. On the other hand, success criteria comprise a set of measures used to evaluate if the project can be judged as successful [ 39 ]. This SLR specifically focuses on PS criteria.

The measurement criteria for assessing PS have undergone significant evolution to encompass the complex and dynamic nature of projects, resulting in the development of more comprehensive models [ 52 , 54 ]. Initially, PS frameworks primarily focused on efficiency criteria, commonly referred to as the “golden triangle,” “iron triangle,” or “holy trinity,” which encompassed elements such as time, cost, and quality [ 54 ]. Subsequent models expanded to incorporate dimensions of client and project team satisfaction [ 55 ]. From the year 2000 onwards, the emergence of integrative models took into account additional dimensions, including realized benefits to the business or organization [ 56 , 57 ], satisfaction levels of internal and external stakeholders such as end-users, suppliers, and other relevant parties [ 58 ], the impacts on the community and environment [ 59 ], long-term effects like the creation of new markets or product lines [ 56 , 60 ], and investment returns [ 61 ].

The conceptual boundaries between PS, project performance, project efficiency, and PM success have often been blurred. On the one hand, PM success represents a conventional measure of PS that primarily focuses on time, cost, and quality, assessed upon project completion [ 62 , 63 ]. These criteria are also called project efficiency [ 64 ]. On the other hand, project performance refers to the degree to which management practices and processes contribute to the achievement of goals and objectives, as well as the fulfillment of stakeholders’ expectations. It is typically evaluated throughout project execution and upon completion [ 54 , 65 ]. In contrast, PS represents a broader and multidimensional concept encompassing the achievement of goals and objectives determined by key stakeholders after project completion [ 63 , 64 ], as well as the long-term impacts of the project [ 66 ].

The SLR was undertaken to investigate the abovementioned research questions and followed the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The protocol employed for conducting this SLR is elaborated next.

3.1. Search strategy

The Web of Science, Scopus, ScienceDirect, and ProQuest electronic databases were selected for this SLR. The databases were first consulted in September 2021, with an update in August and October 2022, by searching the following keywords in the title of the article: “competence,” “competency,” “competences,” “competencies,” “skill,” “skills,” and “project success,” without any additional constraint. The search was performed by two of the authors using the following search strings:

• Scopus database : TITLE ((competence) OR (competency) OR (competences) OR (competencies) OR (skill) OR (skills)) AND TITLE ((project AND success))
• Web of Science database : TI = (competence OR competency OR competences OR competencies OR skill OR skills) AND TI = (project success)
• ScienceDirect database : Title: (competence OR competency OR competences OR competencies OR skill OR skills) AND (project success)
• ProQuest database : title((competence OR competency OR competences OR competencies OR skill OR skills)) AND title((project success))

The metadata of the records (title, authors, document type, source title, author keywords, abstract, publication year, volume number, issue number, and DOI) was exported, compared, and saved on Microsoft Excel spreadsheets to remove duplicated studies and conduct the screening process.

3.2. Study selection

The study selection process comprised several stages to find relevant articles for the review. The initial research resulted in 232 articles. After removing duplicated records, 172 articles were considered for the next stages. The procedures followed by the authors are described below.

3.2.1. Inclusion and exclusion criteria.

The inclusion and exclusion criteria for document selection in this review were based on various factors, including publication timeline, document type, language, study type, population, and context. To be included in this review, documents had to meet the following criteria: (1) they had to be peer-reviewed scholarly research articles, (2) they had to be published between January 2010 and October 2022, (3) they had to be written in English, (4) they had to have a quantitative approach measuring PMG’s competencies as independent variable and PS as a dependent variable, (5) the study population had to consist of PMGs or similar positions (e.g., project director, project leader, senior PMG, department manager, functional manager, team leader), and (6) the research work had to be conducted in professional settings. The study selection process did not impose restrictions on industry, project type, or project size to ensure a broader scope and encompass various perspectives. This approach allowed for the retrieval of peer-reviewed scholarly articles that addressed the research questions of this SLR. Initially, 172 articles were evaluated, and after applying the inclusion criteria, 131 records were removed. Subsequently, 41 research articles remained for the screening process.

3.2.2. Article screening process.

After applying inclusion and exclusion criteria, the retained articles were screened by title, abstract, and full text. This process was conducted by two of the authors independently. The reasons for excluding articles were reported in each step. The exclusion criteria were objectively applied. Studies were excluded if the relationship between PMGs’ competencies and PS was not examined. Each reviewer’s number and list of excluded articles were compared after the screening. In those cases where there was disagreement between reviewers, a third author reviewed the article and discussed it with the other two authors to reach a consensus. Eligible articles were included in the final review. Ineligible articles were formally excluded, with the reasons for exclusion noted.

Out of 41 articles, seven were excluded based on the title. In this step, the main reasons for exclusion were: (a) the study was related to project-based learning ( n = 4), (b) the article was a literature review ( n = 3), and (c) the article was a case of study ( n = 1). The retained 34 articles were screened by abstract. After analyzing the abstract of each article, eight were removed because of the following: (a) the study had a qualitative design ( n = 1), (b) the article was a case of study ( n = 1), (c) the article analyzed only leadership styles ( n = 1), (d) the article was theoretical ( n = 2), (e) the study was not conducted in a PM professional setting ( n = 1), and (f) the article did not analyze the relationship between PMGs’ competencies and PS ( n = 2). Finally, the full-text screening was carried out on 26 articles. Thirteen records were excluded based on the following reasons: (a) PMGs’ competencies were not measured ( n = 3), (b) the article was theoretical ( n = 3), and (c) the study did not analyze the relationship between PMGs’ competencies and PS ( n = 7). After the whole screening process, 13 articles were considered for quality assessment.

3.2.3. Quality assessment.

The quality assessment focused on ten quality criteria statements: (1) The research questions, objectives, or hypothesis were appropriately established; (2) The study design was well described and appropriate for answering the research questions; (3) The sample and population of the study were clearly described, and its size was sufficient to carry out the proposed analysis; (4) The response rate was reported and above 50%; (5) The instruments used for measuring PMGs’ competencies were well described and design-based; (6) The instrument used for measuring PS was well described and design-based; (7) The statistical method was appropriate and sufficiently described to enable them to be repeated; (8) The research questions were adequately answered; (9) The statistical significance of associations was tested and reported; (10) The conclusions were clearly described and based on the results.

The abovementioned criteria were adapted from the Newcastle-Ottawa Quality Assessment Scale (adapted for cross-sectional studies), the Appraisal Tool for Cross-Sectional Studies (AXIS), and similar studies [ 67 ]. Each statement had three rating options coded as “Yes” (1 point), “No” (0 points), and “Partial” (0.5 points). Articles with a score of 7.5 points or higher were included in the final sample. The quality assessment was carried out by two authors independently. The results were compared, and the differences found were discussed to make a final decision. In this phase, three articles were removed. Ten articles were selected to conduct the analysis and answer the research questions of this SLR. Fig 1 summarizes the data extraction procedure through a PRISMA flow.

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https://doi.org/10.1371/journal.pone.0295417.g001

3.3. Data extraction and analysis

Three authors analyzed the articles for data extraction, including sample characteristics, country, setting, independent and outcome variable(s), data analysis procedures, and main findings. These data were synthesized in Table 4 .

A thematic analysis was conducted to identify the dimensions of PMGs’ competencies and PS criteria used in the included articles, following the procedures proposed by Nowell et al. [ 68 ]:

• Familiarization with the data . The authors read and analyzed the content of each article.
• Generation of initial code s. Each author generated a list of competencies and PS criteria extracted from each article. The resulting lists were compared and matched to get a final version.
• Creation of themes . Categories were created by grouping similar competencies and PS criteria. Each of the authors carried out this process individually. The resulting lists were compared and matched to get a final version as in the previous step.
• Definition and naming of themes . Once the final list of competencies and PS were obtained and the main categories were defined, each category was named based on theoretical foundations. This process was carried out jointly by the three authors.

When studying topics such as PMGs’ competencies, an important issue is how authors support their choice regarding what competencies to include in their work. This decision is important since it shapes the structure of the research field. Thus, a citation network analysis (CNA) was carried out to map the structure of the PMGs’ competencies research field. In CNA, research documents serve as nodes, and the connections between them are represented by citations [ 69 ]. CNA is a practical approach for identifying contributions to a specific topic and uncovering relationships within the scholarly literature, thereby revealing patterns of influence and collaboration [ 70 ]. In this SLR, the ten included articles relied on citations of prior works to select the pertinent PMGs’ competencies. These cited references were used to build a network representing the relevant frameworks in the included articles. The citation network was generated using the visNetwork package in RStudio.

4.1. Study characteristics

The main characteristics of the articles included in this SLR are shown in Table 1 . Data were collected from 11 countries across five regions: Asia, Europe, North America, Oceania, and South America. Notably, Pakistan emerged as the most prolific country, with five papers published between 2010 and 2022, followed by the USA ( n = 2) and Brazil ( n = 2). Most studies were published within the last five years ( n = 9). Out of the ten articles, eight were published in journals categorized in the Q1 ( n = 5) and Q2 ( n = 3) impact quartiles. In terms of study design, most articles employed a purely quantitative approach ( n = 8), while two utilized mixed methods. For instance, Sampaio et al. [ 71 ] conducted a systematic review to identify the competencies to be included in their subsequent questionnaire, while Podgórska and Pichlak [ 72 ] employed a mixed-method approach comprising semi-structured interviews and a survey questionnaire.

https://doi.org/10.1371/journal.pone.0295417.t001

4.2. Project managers’ competencies

4.2.1. the most influential theoretical frameworks..

The majority of articles ( n = 9) included in the SLR employed an existing framework to identify the PMGs’ competencies that were examined in their empirical analyses. However, in the study conducted by Sampaio et al. [ 71 ], a comprehensive literature review was undertaken to determine the specific competencies that should be considered for testing their impact on PS.

A CNA was conducted to explore the interrelationships among the ten articles included in this SLR and to identify the most influential frameworks for defining and determining the PMGs’ competencies. Fig 2 visually represents the articles included in the SLR as square nodes and the studies that have contributed to conceptualizing PMGs’ competencies as circle nodes. The size of each node reflects the number of citations it has received. The diagram layout was arranged such that the most frequently cited studies are positioned in the center, while less frequently cited ones are placed towards the periphery. A summary of the most influential works in PMGs’ competencies is provided below.

Notes. Square nodes represent the articles in the SLR ( n = 10), while circle nodes denote the studies that contributed to conceptualizing PMGs’ competencies. The number of citations gives the size of the node.

https://doi.org/10.1371/journal.pone.0295417.g002

Four articles included in this SLR [ 39 , 72 , 73 , 75 ] employed a common framework developed by Dulewicz and Higgs [ 79 ]. This framework encompasses 15 leadership competencies categorized into three dimensions: intellectual competencies (critical analysis and judgment, vision and imagination, strategic perspective), managerial competencies (managing resources, engaging communication, empowering, developing, achieving), and emotional competencies (self-awareness, emotional resilience, intuitiveness, interpersonal sensitivity, influence, motivation, conscientiousness). Additionally, two articles [ 15 , 77 ] drew upon Clarke’s [ 80 ] study, which identified four main PMGs’ competencies: communication, teamwork, attentiveness, and managing conflict. Other frameworks utilized in the SLR articles were proposed by Sunindijo [ 81 ], Katz [ 82 ], Nguyen and Hadikusumo [ 83 ], and Ofori [ 84 ]. These frameworks shared common elements, emphasizing the significance of communication, leadership, managing emotions, and interpersonal relationships as essential competencies for PMGs. Notably, the Project Manager Competency Development Framework [ 12 ] and the Individual Competence Baseline for Project Management [ 13 ] were among the most cited institutional frameworks employed in the SLR articles.

4.2.2. Categorization of project managers’ competencies.

Several common competencies were identified based on the review of competencies reported in each article. These competencies were categorized into four dimensions based in previous studies [ 11 , 31 , 85 ], as presented in Table 2 : cognitive, personal, social, and sustainability. It should be noted that not all competencies were consistently referred to by the same name across the included articles. Therefore, the names used to denote a specific competence in each article are listed in the third column of Table 2 .

https://doi.org/10.1371/journal.pone.0295417.t002

4.3. Project success criteria

Previous literature has traditionally focused on PS measures related to cost, time, and quality. However, the findings of the SLR indicate a growing tendency to incorporate a broader range of success criteria. Table 3 presents a categorization of the different success criteria reported in the included articles.

https://doi.org/10.1371/journal.pone.0295417.t003

The first dimension pertains to the impact on stakeholders, encompassing clients, users, providers, the project team, and other relevant parties. While stakeholder impact is commonly assessed through satisfaction measures, some studies consider alternative indicators such as the acceptability of the product, perceived benefits [ 73 ], or the fulfillment of stakeholder expectations [ 74 ]. Less frequently addressed are measures related to the impact on the organization, for which two criteria were identified: (i) visible short-term improvements in organizational outcomes or performance [ 73 , 75 , 76 ], and (ii) long-term improvements, such as the development of new technologies or the initiation of future projects [ 39 , 72 , 75 ]. Additional criteria related to the project management process were identified, encompassing project performance, achievement of the project’s primary objectives, other self-defined criteria related to project management, and compliance with procedures, safety regulations, and environmental standards. Project performance indicators include the traditional metrics of cost, time, and quality of the project’s deliverables [ 39 , 72 ].

4.4. Empirical analysis of the relationship between project managers’ competencies and project success

Table 4 presents a comprehensive overview of the research methods and results employed in the included studies. Several studies conducted correlational analyses to examine the relationship between competencies and various PS criteria [ 71 , 72 , 75 ], as well as overall PS [ 15 ]. Regression analysis was a common method to assess the predictive impact of PMGs’ competencies on PS criteria in the selected articles [ 39 , 72 , 74 , 75 ]. Additionally, some studies [ 73 , 74 , 76 , 78 ] employed structural equation modeling (SEM) or partial least squares (PLS) to analyze the predictive effect of PMGs’ competencies, modeled as second-order constructs, on PS.

https://doi.org/10.1371/journal.pone.0295417.t004

4.4.1. Relationship between cognitive competencies and project success.

Cognitive competencies encompassed creativity, decision-making, and strategic perspective. Findings from two studies revealed a positive correlation between creativity and various PS criteria, such as accomplishing project objectives, project efficiency, user satisfaction [ 71 ], and suppliers’ satisfaction [ 72 ]. While creativity significantly predicted project efficiency, its effect on achieving project objectives and user satisfaction was not statistically significant [ 71 ]. Two studies included in the SLR [ 39 , 72 ] provided evidence concerning the relationship between strategic perspective and PS. Firstly, Müller and Turner [ 39 ] found that this competence influences project efficiency and self-defined success criteria. Secondly, Podgórska & Pichlak [ 72 ] reported that strategic perspective is significantly associated with all the analyzed PS criteria except for project efficiency and self-defined success criteria. Regarding the decision-making competence, Müller and Turner [ 39 ] did not identify any significant predictive effects of this competence. However, Podgórska and Pichlak [ 72 ] observed significant positive correlations between decision-making and all the PS criteria, with the highest coefficients observed for self-defined success criteria, end-user satisfaction, and satisfaction of other stakeholders.

4.4.2. Relationship between personal competencies and project success.

Personal competencies included emotional intelligence, results orientation, and conscientiousness. Among these competencies, emotional intelligence has received significant attention in the included studies. Out of the ten studies, eight explored the relationship between emotional intelligence and PS. The evidence revealed direct and significant predictive effects of emotional intelligence on various PS criteria, such as end-user satisfaction [ 71 ], achievement of project objectives [ 39 ], and overall PS [ 15 ].

Regarding results orientation, Sampaio et al. [ 71 ] demonstrated that this competence had a predictive effect on project efficiency. Correlational analysis revealed a higher correlation between this competence with PS criteria related to user satisfaction [ 71 ] and satisfaction of other stakeholders [ 72 ]. The conscientiousness competence was examined in the studies conducted by Müller and Turner [ 39 ] and Podgórska and Pichlak [ 72 ]. This competence emerged as a significant predictor of team satisfaction and the achievement of project objectives [ 39 ]. Furthermore, the effects of conscientiousness could vary depending on the type and complexity of the project [ 72 ].

4.4.3. Relationship between social competencies and project success.

Based on the articles included in this review, social competencies, such as communication, leadership, interpersonal relations, conflict management, and teamwork, tend to be associated with PS. Leadership has been extensively studied in the project management literature and was addressed in seven out of the ten articles included in this review. Correlational analysis revealed that leadership shows significant associations with nearly all PS criteria, being its highest correlation with the user satisfaction criterion [ 71 , 72 ]. Regarding its predictive effect on PS, Sampaio et al. [ 71 ] reported a non-significant effect of this competence on some criteria, such as achieving project’s purpose, project efficiency, and stakeholders’ satisfaction, while other studies found a significant effect on team satisfaction criterion [ 39 ] and an overall PS measure [ 15 , 74 ].

Regarding communication, correlational analysis showed that this competence is highly correlated with stakeholders’ satisfaction criterion [ 71 , 72 ]. Maqbool et al. [ 15 ] found that communication had the strongest correlation with a general measure of PS among all competencies included in their study. The predictive effect of this competence on PS was confirmed by Lima and Quevedo-Silva [ 77 ], Khan et al. [ 78 ] and Podgórska and Pichlak [ 72 ]. However, Sampaio et al. [ 71 ] and Müller and Turner [ 39 ] reported non-significant effects of communication of PS criteria.

Interpersonal relations showed significant positive associations with PS criteria, with the strongest coefficients on achieving project’s purpose [ 72 ]. Müller and Turner [ 39 ] found that this competence has a significant predictive effect on other stakeholders’ satisfaction criteria, while two studies [ 77 , 78 ] reported its predictive effect on a general PS measure. Finally, significant positive associations of conflict management and teamwork with PS were reported by Maqbool et al. [ 15 ]. However, its predictive effect on individual PS criteria were not estimated on any of the included articles.

4.4.4. Relationship between sustainability competencies and project success.

According to Elmezain et al. [ 74 ], the capacity to demonstrate integrity, sincerity, and authenticity, and to inspire confidence and trust in others, is relevant for achieving PS. The authors emphasized that PMGs who possess integrity play a crucial role in the advancement of any project. Similarly, Sampaio et al. [ 71 ] highlighted ethics, conceptualized as transparency, integrity, and honesty, as the most significant competence for achieving PS in terms of goal attainment.

5. Discussion

This SLR examined the evidence pertaining to the relationship between PMGs’ competencies and PS. The analysis of the included studies yielded three key findings. Firstly, six distinct clusters of authors were identified, each contributing to the conceptualization and identification of PMGs’ competencies. Secondly, the conceptualization of PS has evolved from a traditional approach centered around criteria such as time, cost, and quality, to a more comprehensive, holistic, and multidimensional perspective. Lastly, through thematic analysis, a total of 12 competencies, organized into four dimensions, were identified as potential determinants of PS. Notably, the most significant competencies associated with PS were found within the personal and social dimensions. A brief discussion of these findings is presented below.

In relation to the first finding, this SLR identified six distinct clusters of authors whose work influenced the competence frameworks utilized in the included articles. These clusters represented conceptualizations proposed by scholars and reputable PM institutions. The in-depth content analysis revealed that the frameworks proposed by Dulewicz and Higgs [ 79 ] and Clarke [ 80 ] were the most prevalent among the examined articles. Conversely, frameworks developed by Sunindijo [ 81 ], Ofori [ 84 ], and Nguyen and Hadikusumo [ 83 ] were comparatively less frequently employed. Additionally, the PMI [ 12 ] emerged as a key institutional point of reference for identifying the competencies required in a PMG. For instance, Lima and Quevedo-Silva [ 77 ] and Maqbool et al. [ 15 ] studies adopted Clarke’s [ 80 ] framework, which was based on the PMI’s [ 12 ] (2017b) list of competencies. Elmezain et al. [ 74 ], who cited Sunindijo et al. [ 81 ] as their framework source, incorporated several competencies defined by the PMI [ 5 ], although the majority of these were technical.

Regarding the second finding, the articles examined in this SLR provided support for the view that PS should be understood as a multidimensional construct. This finding aligns with a recent study by Ika and Pinto [ 54 ] that revisited the conceptualization of PS. The results of this review indicate that project performance, encompassing time, cost, and quality, emerged as the most commonly considered criterion of success across all the articles. However, a significant number of the included articles also acknowledged additional criteria, leading to the identification of three dimensions of PS. The first dimension refers to the impact on stakeholders and includes criteria related to the satisfaction of various project stakeholders, including clients, users, suppliers, and the project team, among others. The second dimension focuses on the impact of the project on the organization, comprising both short- and long-term improvements. Lastly, the third dimension is related with the general management of the project. This dimension encompasses aspects such as project performance, which includes the traditional "iron triangle" of time, cost, and quality, as well as the achievement of project objectives, adherence to project-defined criteria, and compliance with safety and environmental protocols and regulations. This conceptualization supports the multidimensional nature of PS. However, as noted by Ika and Pinto [ 54 ], it is important to highlight that the majority of the included articles overlooked the inclusion of sustainability criteria. Among the entire sample of studies, only one [ 76 ] out of ten explicitly addressed compliance with safety and environmental regulations as a criterion of success.

The findings of this SLR have provided insights into the competencies that exhibit a significant relationship with PS. Specifically, the articles included in this review extensively examined competencies associated with the personal and social dimensions, such as leadership, communication, and emotional intelligence. These competencies have been extensively studied in previous literature [ 18 , 86 ], and their impact on PS was explored in the majority of the reviewed articles. Conversely, the influence of other competencies, such as ethics, received less attention and was not extensively explored. Moreover, the empirical evidence gathered in this review suggests that the effect of project management competencies on PS may vary depending on several factors. For instance, the type of project was found to be a significant factor influencing the relationship between competencies and PS [ 72 ]. Furthermore, individual and organizational factors were identified as potential mediating variables that could affect the relationship between competencies and PS [ 73 ]. These findings highlight the complexity and contextual nature of the relationship between competencies and PS. Next, a brief discussion will be presented to shed light on how these identified competencies can contribute to enhancing PS.

Leadership competence was one of the most studied competencies that improve PS. Although a few of the studies included in this SLR [ 71 , 73 ] reported that it does not have a significant effect on PS, a great number of the studies [ 15 , 39 , 72 , 74 , 76 ] suggested that PMGs’ leadership, conceived as their capacity to influence, empower and develop others, has a positive effect on PS. This finding agrees with the existing literature that has examined its influence on PS [ 87 – 90 ]. The development of competencies such as leadership allows PMGs to motivate their teams to be more productive [ 91 ], to show outstanding performance beyond expectations [ 89 ], to enhance team cohesion and engagement [ 92 ], to foster knowledge transfer across project teams [ 89 ], among other positive behaviors that would impact on projects’ outcomes.

The articles included in this SLR demonstrate a significant and positive relationship between communication and PS [ 15 , 72 , 77 , 78 ], in agreement with previous research findings [ 93 , 94 ]. The significance of this competence lies in its impact throughout various stages of a project [ 94 ]. Effective communication between PMGs and the project team’s members allows better collaboration [ 95 ], encourages knowledge sharing [ 96 ], and enhances the team’s motivation a sense of inclusivity [ 94 ], which contribute to the overall achievement of PS.

The influence of emotional intelligence on PS was assessed in most of the articles included in this SLR. Although some studies reported a non-significant relationship between emotional intelligence [ 71 , 73 , 77 ], there was evidence supporting a positive association between these two variables [ 15 , 39 , 72 , 75 ]. PMGs with high emotional intelligence are more likely to establish stronger relationships with their teams, thereby improving communication, clarity of mission, and support, ultimately enhancing PS [ 21 ]. In addition, the development of this competence allows PMGs to adequately regulate their emotions in complex situations, promoting positive behaviors such as empathy, respect, and leadership. These behaviors contribute to their ability to address challenges successfully and ensure higher PS [ 97 , 98 ].

Regarding the influence of PMGs’ ethics, a positive relationship was identified between this competence and PS criteria, particularly goal achievement [ 71 ]. Ethics has been acknowledged as a driving force for the advancement of the PM profession [ 48 ] and an essential competence that PMGs should possess [ 99 , 100 ]. However, empirical evidence on the impact of ethics on PS remains limited. Some related terms, such as honesty, integrity, and transparency [ 71 , 74 ], or ethical thinking [ 100 ], ethical decision-making, and ethics sensitivity have been addressed in previous studies. However, its effect on PS has rarely been estimated and reported. The evidence found on ethics in this SLR was obtained from information systems and construction projects. Future studies could explore the influence of this competence in different industries and countries.

6. Limitations and strengths

While this review contributes with some insights to the PM literature, it is important to mention its limitations. Firstly, the time frame of the review from 2010 to 2022 may have resulted in the exclusion of relevant articles that explore the relationship between PMGs’ competencies and PS. It is possible that some studies conducted outside this timeframe may provide further insights into the topic. Secondly, the use of specific search terms such as “competence,” “competency,” “competences,” “competencies,” “skill,” and “skills” may have excluded other studies [ 86 , 88 ] that examined the impact of different competencies individually. Including an exhaustive list of competencies in the search strings could have introduced significant heterogeneity into the reviewed articles, potentially limiting the ability to provide a comprehensive review of the existing literature.

Despite these limitations, this SLR makes several notable contributions to the PM discipline. First, it fills a gap in the existing literature by synthesizing available empirical evidence on the relationship between PMGs’ competencies and PS. Second, the review conducts a thematic analysis and adopts a holistic perspective to categorize the PMGs’ competencies that are associated with PS. Third, this review highlights the primary authors and PM institutions that have significantly influenced the conceptualization of PMGs’ competencies. Four, the review examines the criteria used to measure PS in the included articles and organizes them into three dimensions, offering a nuanced understanding of the multifaceted nature of PS measurement.

7. Conclusions

The present SLR extends the literature in project management concerning the influence of PMGs’ competencies on PS. Despite the growing interest in addressing the role of PMGs’ competencies to achieve higher success, to the best of our knowledge, there is a lack of systematic reviews that present an analysis of the available evidence on the relationship between PMGs’ competencies on PS. To fill this gap in the literature, this SLR analyzed the existing evidence regarding this relationship. Three main conclusions can be derived from the findings of this review. First, the existing literature has primarily explored the influence on PS of PMGs’ competencies from the personal and social dimensions, such as leadership, communication, and emotional intelligence. Second, PS is a multidimensional construct that comprises three main dimensions: impact on stakeholders, impact on the organization, and general project management. Third, the available data suggested that greater levels of PMGs’ competencies are associated with improved PS. These findings may support scholars and managers to understand the mechanisms through which individual characteristics, such as competencies, may allow PMGs to achieve better outcomes.

This SLR contributes to the existing literature in the PM discipline by offering a comprehensive synthesis of empirical evidence, providing a thorough overview of the current state of knowledge regarding the relationship between PMGs’ competencies and PS. In addition, this SLR identifies key contributors and sources of knowledge in the field, offering a valuable reference point for further research and exploration. The study also offers a review on how PS is conceptualized and measured. Moreover, it presents a classification of PMGs’ competencies that influence PS. Through a thematic analysis of the competencies examined in the included articles, this categorization provides valuable insights into the emphasis placed on different types of competencies. It highlights the significant attention given to personal and social competencies, while pointing out the relatively limited exploration of sustainability, cultural, or digital competencies [ 85 ].

Supporting information

S1 checklist. prisma 2020 checklist..

https://doi.org/10.1371/journal.pone.0295417.s001

S1 Table. Inclusion and exclusion criteria used in the SLR.

Notes: PMG = Project manager, PS = Project success.

https://doi.org/10.1371/journal.pone.0295417.s002

S2 Table. Quality assessment criteria scoring guide.

https://doi.org/10.1371/journal.pone.0295417.s003

S3 Table. Quality assessment results.

Notes: QC1 = Research questions; QC2 = Study design; QC3 = Sample representativeness; QC4 = Response rate; QC5 = PMG’s competencies measurement; QC6 = PS measurement; QC7 = Statistical analysis; QC8 = Results; QC9 = Statistical significance; QC10 = Conclusions; SLR = Systematic literature review.

https://doi.org/10.1371/journal.pone.0295417.s004

S4 Table. Brief description of the Project Managers’ competencies in included articles.

https://doi.org/10.1371/journal.pone.0295417.s005

S5 Table. Brief description of the project success criteria in included articles.

https://doi.org/10.1371/journal.pone.0295417.s006

• View Article
• Google Scholar
• 12. Project Management Institute. Project Manager Competency Development Framework. 3rd ed. Newtown Square (PA): Project Management Institute, Inc.; 2017.
• 13. International Project Management Association. Individual Competence Baseline for Project, Programme and Portfolio Management (Version 4.0.). Zurich: International Project Management Association; 2015.
• PubMed/NCBI
• 33. Iriarte C, Bayona Orè S. Soft Skills for IT Project Success: A Systematic Literature Review. In: Mejia J, Muñoz M, Rocha Á, Quiñonez Y, Calvo-Manzano J, editors. Trends and Applications in Software Engineering. Cham: Springer International Publishing; 2018. pp. 147–158. https://doi.org/10.1007/978-3-319-69341-5_14
• 34. Goleman D, Boyatzis R, McKee A. Primal Leadership: Unleashing the Power of Emotional Intelligence. Boston: Harvard Business Press; 2013.
• 35. Boyatzis R. The Competent Manager: A Model for Effective Performance. New York: John Wiley & Sons; 1982.
• 60. Shenhar AJ, Dvir D. Reinventing project management: the diamond approach to successful growth and innovation. Boston: Harvard Business Review Press; 2007.
• 65. Crawford L. Measuring Performance. In: Turner R, editor. Gower Handbook of Project Management. 5th ed. New York: Routledge; 2014. pp. 105–120.
• 85. Ochoa P, Jáuregui K, Gomes T, Ruiz B, Lasio V. Las competencias laborales en el mercado de profesionales de América Latina: ¿Qué destrezas demandarán las empresas del futuro en Chile, Colombia, Ecuador y el Perú? Lima: ESAN Ediciones; 2018.

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• v.20; 2019 Oct 25

Managing Ideas, People, and Projects: Organizational Tools and Strategies for Researchers

Samuel pascal levin.

1 Beverly, MA 01915, USA

Michael Levin

2 Allen Discovery Center at Tufts University, Suite 4600, 200 Boston Avenue, Medford, MA 02155-4243, USA

Primary Investigators at all levels of their career face a range of challenges related to optimizing their activity within the constraints of deadlines and productive research. These range from enhancing creative thought and keeping track of ideas to organizing and prioritizing the activity of the members of the group. Numerous tools now exist that facilitate the storage and retrieval of information necessary for running a laboratory to advance specific project goals within associated timelines. Here we discuss strategies and tools/software that, together or individually, can be used as is or adapted to any size scientific laboratory. Specific software products, suggested use cases, and examples are shown across the life cycle from idea to publication. Strategies for managing the organization of, and access to, digital information and planning structures can greatly facilitate the efficiency and impact of an active scientific enterprise. The principles and workflow described here are applicable to many different fields.

Graphical Abstract

Information Systems; Knowledge Management

Introduction

Researchers, at all stages of their careers, are facing an ever-increasing deluge of information and deadlines. Additional difficulties arise when one is the Principal Investigator (PI) of those researchers: as group size and scope of inquiry increases, the challenges of managing people and projects and the interlocking timelines, finances, and information pertaining to those projects present a continuous challenge. In the immediate term, there are experiments to do, papers and grants to write, and presentations to construct, in addition to teaching and departmental duties. At the same time, however, the PI must make strategic decisions that will impact the future direction(s) of the laboratory and its personnel. The integration of deep creative thought together with the practical steps of implementing a research plan and running a laboratory on a day-to-day basis is one of the great challenges of the modern scientific enterprise. Especially difficult is the fact that attention needs to span many orders of scale, from decisions about which problems should be pursued by the group in the coming years and how to tackle those problems to putting out regular “fires” associated with the minutiae of managing people and limited resources toward the committed goals.

The planning of changes in research emphasis, hiring, grant-writing, etc. likewise occur over several different timescales. The optimization of resources and talent toward impactful goals requires the ability to organize, store, and rapidly access information that is integrated with project planning structures. Interestingly, unlike other fields such as business, there are few well-known, generally accepted guidelines for best practices available to researchers. Here we lay out a conceptual taxonomy of the life cycle of a project, from brainstorming ideas through to a final deliverable product. We recommend methods and software/tools to facilitate management of concurrent research activities across the timeline. The goal is to optimize the organization, storage, and access to the necessary information in each phase, and, crucially, to facilitate the interconnections between static information, action plans, and work product across all phases. We believe that the earlier in the career of a researcher such tools are implemented and customized, the more positive impact they will exert on the productivity of their enterprise.

This overview is intended for anyone who is conducting research or academic scholarship. It consists of a number of strategies and software recommendations that can be used together or independently (adapted to suit a given individual's or group's needs). Some of the specific software packages mentioned are only usable on Apple devices, but similar counterparts exist in the Windows and Linux ecosystems; these are indicated in Table 1 (definitions of special terms are given in Table 2 ). These strategies were developed (and have been continuously updated) over the last 20 years based on the experiences of the Levin group and those of various collaborators and other productive researchers. Although very specific software and platforms are indicated, to facilitate the immediate and practical adoption by researchers at all levels, the important thing is the strategies illustrated by the examples. As software and hardware inevitably change over the next few years, the fundamental principles can be readily adapted to newer products.

Software Packages and Alternatives

A Glossary of Special Terms

Basic Principles

Although there is a huge variety of different types of scientific enterprises, most of them contain one or more activities that can be roughly subsumed by the conceptual progression shown in Figure 1 . This life cycle progresses from brainstorming and ideation through planning, execution of research, and then creation of work products. Each stage requires unique activities and tools, and it is crucial to establish a pipeline and best practices that enable the results of each phase to effectively facilitate the next phase. All of the recommendations given below are designed to support the following basic principles:

• • Information should be easy to find and access, so as to enable the user to have to remember as little as possible—this keeps the mind free to generate new, creative ideas. We believe that when people get comfortable with not having to remember any details and are completely secure in the knowledge that the information has been offloaded to a dependable system and will be there when they need it, a deeper, improved level of thinking can be achieved.
• • Information should be both organized hierarchically (accessible by drill-down search through a rational structure) and searchable by keywords.
• • Information should be reachable from anywhere in the world (but secure and access restricted). Choose software that includes a cell phone/tablet platform client.
• • No information should ever be lost—the systems are such that additional information does not clog up or reduce efficiency of use and backup strategies ensure disaster robustness; therefore, it is possible to save everything.
• • Software tools optimized for specific management tasks should be used; select those tools based on interoperability, features, and the ability to export into common formats (such as XML) in case it becomes expedient someday to switch to a newer product.
• • One's digital world should be organized into several interlocking categories, which utilize different tools: activity (to-dos, projects, research goals) and knowledge (static information).
• • One's activity should be hierarchically organized according to a temporal scale, ranging from immediate goals all the way to career achievement objectives and core mission.
• • Storage of planning data should allow integration of plans with the information needed to implement them (using links to files and data in the various tools).
• • There should be no stored paper—everything should be obtained and stored in a digital form (or immediately digitized, using one of the tools described later in this document).
• • The information management tasks described herein should not occupy so much time as to take away from actual research. When implemented correctly, they result in a net increase in productivity.

The Life Cycle of Research Activity

Various projects occupy different places along a typical timeline. The life cycle extends from creative ideation to gathering information, to formulating a plan, to the execution for the plan, and then to producing a work product such as a grant or paper based on the results. Many of these phases necessitate feedback to a prior phase, shown in thinner arrows (for example, information discovered during a literature search or attempts to formalize the work plan may require novel brainstorming). This diagram shows the product (end result) of each phase and typical tools used to accomplish them.

These basic principles can be used as the skeleton around which specific strategies and new software products can be deployed. Whenever possible, these can be implemented via external administration services (i.e., by a dedicated project manager or administrator inside the group), but this is not always compatible with budgetary constraints, in which case they can readily be deployed by each principal investigator. The PIs also have to decide whether they plan to suggest (or insist) that other people in the group also use these strategies, and perhaps monitor their execution. In our experience, it is most essential for anyone leading a complex project or several to adopt these methods (typically, a faculty member or senior staff scientist), whereas people tightly focused on one project and with limited concurrent tasks involving others (e.g., Ph.D. students) are not essential to move toward the entire system (although, for example, the backup systems should absolutely be ensured to be implemented among all knowledge workers in the group). The following are some of the methods that have proven most effective in our own experience.

Information Technology Infrastructure

Several key elements should be pillars of your Information Technology (IT) infrastructure ( Figure 2 ). You should be familiar enough with computer technology that you can implement these yourself, as it is rare for an institutional IT department to be able to offer this level of assistance. Your primary disk should be a large (currently, ∼2TB) SSD drive or, better, a disk card (such as the 2TB SSD NVMe PCIe) for fast access and minimal waiting time. Your computer should be so fast that you spend no time (except in the case of calculations or data processing) waiting for anything—your typing and mouse movement should be the rate-limiting step. If you find yourself waiting for windows or files to open, obtain a better machine.

Schematic of Data Flow and Storage

Three types of information: data (facts and datasets), action plans (schedules and to-do lists), and work product (documents) all interact with each other in defining a region of work space for a given research project. All of this should be hosted on a single PC (personal computer). It is accessed by a set of regular backups of several types, as well as by the user who can interact with raw files through the file system or with organized data through a variety of client applications that organize information, schedules, and email. See Table 2 for definitions of special terms.

One key element is backups—redundant copies of your data. Disks fail—it is not a question of whether your laptop or hard drive will die, but when. Storage space is inexpensive and researchers' time is precious: team members should not tolerate time lost due to computer snafus. The backup and accessibility system should be such that data are immediately recoverable following any sort of disaster; it only has to be set up once, and it only takes one disaster to realize the value of paranoia about data. This extends also to laboratory inventory systems—it is useful to keep (and back up) lists of significant equipment and reagents in the laboratory, in case they are needed for the insurance process in case of loss or damage.

The main drive should be big enough to keep all key information (not primary laboratory data, such as images or video) in one volume—this is to facilitate cloning. You should have an extra internal drive (which can be a regular disk) of the same size or bigger. Use something like Carbon Copy Cloner or SuperDuper to set up a nightly clone operation. When the main disk fails (e.g., the night before a big grant is due), boot from the clone and your exact, functioning system is ready to go. For Macs, another internal drive set up as a Time Machine enables keeping versions of files as they change. You should also have an external drive, which is likewise a Time Machine or a clone: you can quickly unplug it and take it with you, if the laboratory has to be evacuated (fire alarm or chemical emergency) or if something happens to your computer and you need to use one elsewhere. Set a calendar reminder once a month to check that the Time Machine is accessible and can be searched and that your clone is actually updated and bootable. A Passport-type portable drive is ideal when traveling to conferences: if something happens to the laptop, you can boot a fresh (or borrowed) machine from the portable drive and continue working. For people who routinely install software or operating system updates, I also recommend getting one disk that is a clone of the entire system and applications and then set it to nightly clone the data only , leaving the operating system files unchanged. This guarantees that you have a usable system with the latest data files (useful in case an update or a new piece of software renders the system unstable or unbootable and it overwrites the regular clone before you notice the problem). Consider off-site storage. CrashPlan Pro is a reasonable choice for backing up laboratory data to the cloud. One solution for a single person's digital content is to have two extra external hard drives. One gets a clone of your office computer, and one is a clone of your home computer, and then you swap—bring the office one home and the home one to your office. Update them regularly, and keep them swapped, so that should a disaster strike one location, all of the data are available. Finally, pay careful attention (via timed reminders) to how your laboratory machines and your people's machines are being backed up; a lot of young researchers, especially those who have not been through a disaster yet, do not make backups. One solution is to have a system like CrashPlan Pro installed on everyone's machines to do automatic backup.

Another key element is accessibility of information. Everyone should be working on files (i.e., Microsoft Word documents) that are inside a Dropbox or Box folder; whatever you are working on this month, the files should be inside a folder synchronized by one of these services. That way, if anything happens to your machine, you can access your files from anywhere in the world. It is critical that whatever service is chosen, it is one that s ynchronizes a local copy of the data that live on your local machine (not simply keeps files in the cloud) —that way, you have what you need even if the internet is down or connectivity is poor. Tools that help connect to your resources while on the road include a VPN (especially useful for secure connections while traveling), SFTP (to transfer files; turn on the SFTP, not FTP, service on your office machine), and Remote Desktop (or VNC). All of these exist for cell phone or tablet devices, as well as for laptops, enabling access to anything from anywhere. All files (including scans of paper documents) should be processed by OCR (optical character recognition) software to render their contents searchable. This can be done in batch (on a schedule), by Adobe Acrobat's OCR function, which can be pointed to an entire folder of PDFs, for example, and left to run overnight. The result, especially with Apple's Spotlight feature, is that one can easily retrieve information that might be written inside a scanned document.

Here, we focus on work product and the thought process, not management of the raw data as it emerges from equipment and experimental apparatus. However, mention should be made of electronic laboratory notebooks (ELNs), which are becoming an important aspect of research. ELNs are a rapidly developing field, because they face a number of challenges. A laboratory that abandons paper notebooks entirely has to provide computer interfaces anywhere in the facility where data might be generated; having screens, keyboards, and mice at every microscope or other apparatus station, for example, can be expensive, and it is not trivial to find an ergonomically equivalent digital substitute for writing things down in a notebook as ideas or data appear. On the other hand, keeping both paper notebooks for immediate recording, and ELNs for organized official storage, raises problems of wasted effort during the (perhaps incomplete) transfer of information from paper to the digital version. ELNs are also an essential tool to prevent loss of institutional knowledge as team members move up to independent positions. ELN usage will evolve over time as input devices improve and best practices are developed to minimize the overhead of entering meta-data. However, regardless of how primary data are acquired, the researcher will need specific strategies for transitioning experimental findings into research product in the context of a complex set of personal, institutional, and scientific goals and constraints.

Facilitating Creativity

The pipeline begins with ideas, which must be cultivated and then harnessed for subsequent implementation ( Altshuller, 1984 ). This step consists of two components: identifying salient new information and arranging it in a way that facilitates novel ideas, associations, hypotheses, and strategic plans for making impact.

For the first step, we suggest an automated weekly PubCrawler search, which allows Boolean searches of the literature. Good searches to save include ones focusing on specific keywords of interest, as well as names of specific people whose work one wants to follow. The resulting weekly email of new papers matching specific criteria complements manual searches done via ISI's Web of Science, Google Scholar, and PubMed. The papers of interest should be immediately imported into a reference manager, such as Endnote, along with useful Keywords and text in the Notes field of each one that will facilitate locating them later. Additional tools include DevonAgent and DevonSphere, which enable smart searches of web and local resources, respectively.

Brainstorming can take place on paper or digitally (see later discussion). We have noticed that the rate of influx of new ideas is increased by habituating to never losing a new idea. This can be accomplished by establishing a voicemail contact in your cell phone leading to your own office voicemail (which allows voice recordings of idea fragments while driving or on the road, hands-free) and/or setting up Endnote or a similar server-synchronized application to record (and ideally transcribe) notes. It has been our experience that the more one records ideas arising in a non-work setting, the more often they will pop up automatically. For notes or schematics written on paper during dedicated brainstorming, one tool that ensures that nothing is lost is an electronic pen. For example, the Livescribe products are well integrated with Evernote and ensure that no matter where you are, anything you write down becomes captured in a form accessible from anywhere and are safe no matter what happens to the original notebook in which they were written.

Enhancing scientific thought, creative brainstorming, and strategic planning is facilitated by the creation of mind maps: visual representations of spatial structure of links between concepts, or the mapping of planned activity onto goals of different timescales. There are many available mind map software packages, including MindNode; their goal is to enable one to quickly set down relationships between concepts with a minimum of time spent on formatting. Examples are shown in Figures 3 A and 3B. The process of creating these mind maps (which can then be put on one's website or discussed with the laboratory members) helps refine fuzzy thinking and clarifies the relationships between concepts or activities. Mind mappers are an excellent tool because their light, freeform nature allows unimpeded brainstorming and fluid changes of idea structure but at the same time forces one to explicitly test out specific arrangements of plans or ideas.

Mind Mapping

(A and B) The task of schematizing concepts and ideas spatially based on their hierarchical relationships with each other is a powerful technique for organizing the creative thought process. Examples include (A), which shows how the different projects in our laboratory relate to each other. Importantly, it can also reveal disbalances or gaps in coverage of specific topics, as well as help identify novel relationships between sub-projects by placing them on axes (B) or even identify novel hypotheses suggested by symmetry.

(C) Relationships between the central nervous system (CNS) and regeneration, cancer, and embryogenesis. The connecting lines in black show typical projects (relationships) already being pursued by our laboratory, and the lack of a project in the space between CNS and embryogenesis suggests a straightforward hypothesis and project to examine the role of the brain in embryonic patterning.

It is important to note that mind maps can serve a function beyond explicit organization. In a good mapped structure, one can look for symmetries (revealing relationships that are otherwise not obvious) between the concepts involved. An obvious geometric pattern with a missing link or node can help one think about what could possibly go there, and often identifies new relationships or items that had not been considered ( Figure 3 C), in much the same way that gaps in the periodic table of the elements helped identify novel elements.

Organizing Information and Knowledge

The input and output of the feedback process between brainstorming and literature mining is information. Static information not only consists of the facts, images, documents, and other material needed to support a train of thought but also includes anything needed to support the various projects and activities. It should be accessible in three ways, as it will be active during all phases of the work cycle. Files should be arranged on your disk in a logical hierarchical structure appropriate to the work. Everything should also be searchable and indexed by Spotlight. Finally, some information should be stored as entries in a data management system, like Evernote or DevonThink, which have convenient client applications that make the data accessible from any device.

Notes in these systems should include useful lists and how-to's, including, for example:

• • Names and addresses of experts for specific topics
• • Emergency protocols for laboratory or animal habitats
• • Common recipes/methods
• • Lists and outlines of papers/grants on the docket
• • Information on students, computers, courses, etc.
• • Laboratory policies
• • Materials and advice for students, new group members, etc.
• • Lists of editors, and preferred media contacts
• • Lists of Materials Transfer Agreements (MTAs), contract texts, info on IP
• • Favorite questions for prospective laboratory members

Each note can have attachments, which include manuals, materials safety sheets, etc. DevonThink needs a little more setup but is more robust and also allows keeping the server on one's own machine (nothing gets uploaded to company servers, unlike with Evernote, which might be a factor for sensitive data). Scientific papers should be kept in a reference manager, whereas books (such as epub files and PDFs of books and manuscripts) can be stored in a Calibre library.

Email: A Distinct Kind of Information

A special case of static information is email, including especially informative and/or actionable emails from team members, external collaborators, reviewers, and funders. Because the influx of email is ever-increasing, it is important to (1) establish a good infrastructure for its management and (2) establish policies for responding to emails and using them to facilitate research. The first step is to ensure that one only sees useful emails, by training a good Bayesian spam filter such as SpamSieve. We suggest a triage system in which, at specific times of day (so that it does not interfere with other work), the Inbox is checked and each email is (1) forwarded to someone better suited to handling it, (2) responded quickly for urgent things that need a simple answer, or (3) started as a Draft email for those that require a thoughtful reply. Once a day or a couple of times per week, when circumstances permit focused thought, the Draft folder should be revisited and those emails answered. We suggest a “0 Inbox” policy whereby at the end of a day, the Inbox is basically empty, with everything either delegated, answered, or set to answer later.

We also suggest creating subfolders in the main account (keeping them on the mail server, not local to a computer, so that they can be searched and accessed from anywhere) as follows:

• • Collaborators (emails stating what they are going to do or updating on recent status)
• • Grants in play (emails from funding agencies confirming receipt)
• • Papers in play (emails from journals confirming receipt)
• • Waiting for information (emails from people for whom you are waiting for information)
• • Waiting for miscellaneous (emails from people who you expect to do something)
• • Waiting for reagents (emails from people confirming that they will be sending you a physical object)

Incoming emails belonging to those categories (for example, an email from an NIH program officer acknowledging a grant submission, a collaborator who emailed a plan of what they will do next, or someone who promised to answer a specific question) should be sorted from the Inbox to the relevant folder. Every couple of weeks (according to a calendar reminder), those folders should be checked, and those items that have since been dealt with can be saved to a Saved Messages folder archive, whereas those that remain can be Replied to as a reminder to prod the relevant person.

In addition, as most researchers now exchange a lot of information via email, the email trail preserves a record of relationships among colleagues and collaborators. It can be extremely useful, even years later, to be able to go back and see who said what to whom, what was the last conversation in a collaboration that stalled, who sent that special protocol or reagent and needs to be acknowledged, etc. It is imperative that you know where your email is being stored, by whom, and their policy on retention, storage space limits, search, backup, etc. Most university IT departments keep a mail server with limited storage space and will delete your old emails (even more so if you move institutions). One way to keep a permanent record with complete control is with an application called MailSteward Pro. This is a front-end client for a freely available MySQL server, which can run on any machine in your laboratory. It will import your mail and store unlimited quantities indefinitely. Unlike a mail server, this is a real database system and is not as susceptible to data corruption or loss as many other methods.

A suggested strategy is as follows. Keep every single email, sent and received. Every month (set a timed reminder), have MailSteward Pro import them into the MySQL database. Once a year, prune them from the mail server (or let IT do it on their own schedule). This allows rapid search (and then reply) from inside a mail client for anything that is less than one year old (most searches), but anything older can be found in the very versatile MailStewardPro Boolean search function. Over time, in addition to finding specific emails, this allows some informative data mining. Results of searches via MailStewardPro can be imported into Excel to, for example, identify the people with whom you most frequently communicate or make histograms of the frequency of specific keywords as a function of time throughout your career.

With ideas, mind maps, and the necessary information in hand, one can consider what aspects of the current operations plan can be changed to incorporate plans for new, impactful activity.

Organizing Tasks and Planning

A very useful strategy involves breaking down everything according to the timescales of decision-making, such as in the Getting Things Done (GTD) philosophy ( Figure 4 ) ( Allen, 2015 ). Activities range from immediate (daily) tasks to intermediate goals all the way to career-scale (or life-long) mission statements. As with mind maps, being explicit about these categories not only force one to think hard about important aspects of their work, but also facilitate the transmission of this information to others on the team. The different categories are to be revisited and revised at different rates, according to their position on the hierarchy. This enables you to make sure that effort and resources are being spent according to priorities.

Scales of Activity Planning

Activities should be assigned to a level of planning with a temporal scale, based on how often the goals of that level get re-evaluated. This ranges from core values, which can span an entire career or lifetime, all the way to tactics that guide day-to-day activities. Each level should be re-evaluated at a reasonable time frame to ensure that its goals are still consistent with the bigger picture of the level(s) above it and to help re-define the plans for the levels below it.

We also strongly recommend a yearly personal scientific retreat. This is not meant to be a vacation to “forget about work” but rather an opportunity for freedom from everyday minutiae to revisit, evaluate, and potentially revise future activity (priorities, action items) for the next few years. Every few years, take more time to re-map even higher levels on the pyramid hierarchy; consider what the group has been doing—do you like the intellectual space your group now occupies? Are your efforts having the kind of impact you realistically want to make? A formal diagram helps clarify the conceptual vision and identify gaps and opportunities. Once a correct level of activity has been identified, it is time to plan specific activities.

A very good tool for this purpose, which enables hierarchical storage of tasks and subtasks and their scheduling, is OmniFocus ( Figure 5 ). OmniFocus also enables inclusion of files (or links to files or links to Evernote notes of information) together with each Action. It additionally allows each action to be marked as “Done” once it is complete, providing not only a current action plan but a history of every past activity. Another interesting aspect is the fact that one can link individual actions with specific contexts: visualizing the database from the perspective of contexts enables efficient focus of attention on those tasks that are relevant in a specific scenario. OmniFocus allows setting reminders for specific actions and can be used for adding a time component to the activity.

Project Planning

This figure shows a screenshot of the OmniFocus application, illustrating the nested hierarchy of projects and sub-projects, arranged into larger groups.

The best way to manage time relative to activity (and to manage the people responsible for each activity) is to construct Gantt charts ( Figure 6 ), which can be used to plan out project timelines and help keep grant and contract deliverables on time. A critical feature is that it makes dependencies explicit, so that it is clear which items have to be solved/done before something else can be accomplished. Gantt charts are essential for complex, multi-person, and/or multi-step projects with strict deadlines (such as grant deliverables and progress reports). Software such as OmniPlanner can also be used to link resources (equipment, consumables, living material, etc.) with specific actions and timelines. Updating and evaluation of a Gantt chart for a specific project should take place on a time frame appropriate to the length of the next immediate phase; weekly or biweekly is typical.

Timeline Planning

This figure shows a screenshot of a typical Gantt chart, in OmniPlan software, illustrating the timelines of different project steps, their dependencies, and specific milestones (such as a due date for a site visit or grant submission). Note that Gantt software automatically moves the end date for each item if its subtasks' timing changes, enabling one to see a dynamically correct up-to-date temporal map of the project that adjusts for the real-world contingencies of research.

In addition to the comprehensive work plan in OmniFocus or similar, it is helpful to use a Calendar (which synchronizes to a server, such as Microsoft Office calendar with Exchange server). For yourself, make a task every day called “Monday tasks,” etc., which contains all the individual things to be accomplished (which do not warrant their own calendar reminder). First thing in the morning, one can take a look at the day's tasks to see what needs to be done. Whatever does not get done that day is to be copied onto another day's tasks. For each of the people on your team, make a timed reminder (weekly, for example, for those with whom you meet once a week) containing the immediate next steps for them to do and the next thing they are supposed to produce for your meeting. Have it with you when you meet, and give them a copy, updating the next occurrence as needed based on what was decided at the meeting to do next. This scheme makes it easy for you to remember precisely what needs to be covered in the discussion, serves as a record of the project and what you walked about with whom at any given day (which can be consulted years later, to reconstruct events if needed), and is useful to synchronize everyone on the same page (if the team member gets a copy of it after the meeting).

Writing: The Work Products

Writing, to disseminate results and analysis, is a central activity for scientists. One of the OmniFocus library's sections should contain lists of upcoming grants to write, primary papers that are being worked on, and reviews/hypothesis papers planned. Microsoft Word is the most popular tool for writing papers—its major advantage is compatibility with others, for collaborative manuscripts (its Track Changes feature is also very well implemented, enabling collaboration as a master document is passed from one co-author to another). But Scrivener should be seriously considered—it is an excellent tool that facilitates complex projects and documents because it enables WYSIWYG text editing in the context of a hierarchical structure, which allows you to simultaneously work on a detailed piece of text while seeing the whole outline of the project ( Figure 7 ).

Writing Complex Materials

This figure shows a screenshot from the Scrivener software. The panel on the left facilitates logical and hierarchical organization of a complex writing project (by showing where in the overall structure any given text would fit), while the editing pane on the right allows the user to focus on writing a specific subsection without having to scroll through (but still being able to see) the major categories within which it must fit.

It is critical to learn to use a reference manager—there are numerous ones, including, for example, Endnote, which will make it much easier to collaborate with others on papers with many citations. One specific tip to make collaboration easier is to ask all of the co-authors to set the reference manager to use PMID Accession Number in the temporary citations in the text instead of the arbitrary record number it uses by default. That way, a document can have its bibliography formatted by any of the co-authors even if they have completely different libraries. Although some prefer collaborative editing of a Google Doc file, we have found a “master document” system useful, in which a file is passed around among collaborators by email but only one can make (Tracked) edits at a time (i.e., one person has the master doc and everyone makes edits on top of that).

One task most scientists regularly undertake is writing reviews of a specific subfield (or Whitepapers). It is often difficult, when one has an assignment to write, to remember all of the important papers that were seen in the last few years that bear on the topic. One method to remedy this is to keep standing document files, one for each topic that one might plausibly want to cover and update them regularly. Whenever a good paper is found, immediately enter it into the reference manager (with good keywords) and put a sentence or two about its main point (with the citation) into the relevant document. Whenever you decide to write the review, you will already have a file with the necessary material that only remains to be organized, allowing you to focus on conceptual integration and not combing through literature.

The life cycle of research can be viewed through the lens of the tools used at different stages. First there are the conceptual ideas; many are interconnected, and a mind mapper is used to flesh out the structure of ideas, topics, and concepts; make it explicit; and share it within the team and with external collaborators. Then there is the knowledge—facts, data, documents, protocols, pieces of information that relate to the various concepts. Kept in a combination of Endnote (for papers), Evernote (for information fragments and lists), and file system files (for documents), everything is linked and cross-referenced to facilitate the projects. Activities are action items, based on the mind map, of what to do, who is doing what, and for which purpose/grant. OmniFocus stores the subtasks within tasks within goals for the PI and everyone in the laboratory. During meetings with team members, these lists and calendar entries are used to synchronize objectives with everyone and keep the activity optimized toward the next step goals. The product—discovery and synthesis—is embodied in publications via a word processor and reference manager. A calendar structure is used to manage the trajectory from idea to publication or grant.

The tools are currently good enough to enable individual components in this pipeline. Because new tools are continuously developed and improved, we recommend a yearly overview and analysis of how well the tools are working (e.g., which component of the management plan takes the most time or is the most difficult to make invisible relative to the actual thinking and writing), coupled to a web search for new software and updated versions of existing programs within each of the categories discussed earlier.

A major opportunity exists for software companies in the creation of integrated new tools that provide all the tools in a single integrated system. In future years, a single platform will surely appear that will enable the user to visualize the same research structure from the perspective of an idea mind map, a schedule, a list of action items, or a knowledge system to be queried. Subsequent development may even include Artificial Intelligence tools for knowledge mining, to help the researcher extract novel relationships among the content. These will also need to dovetail with ELN platforms, to enable a more seamless integration of project management with primary data. These may eventually become part of the suite of tools being developed for improving larger group dynamics (e.g., Microsoft Teams). One challenge in such endeavors is ensuring the compatibility of formats and management procedures across groups and collaborators, which can be mitigated by explicitly discussing choice of software and process, at the beginning of any serious collaboration.

Regardless of the specific software products used, a researcher needs to put systems in place for managing information, plans, schedules, and work products. These digital objects need to be maximally accessible and backed up, to optimize productivity. A core principle is to have these systems be so robust and lightweight as to serve as an “external brain” ( Menary, 2010 )—to maximize creativity and deep thought by making sure all the details are recorded and available when needed. Although the above discussion focused on the needs of a single researcher (perhaps running a team), future work will address the unique needs of collaborative projects with more lateral interactions by significant numbers of participants.

Acknowledgments

We thank Joshua Finkelstein for helpful comments on a draft of the manuscript. M.L. gratefully acknowledges support by an Allen Discovery Center award from the Paul G. Allen Frontiers Group (12171) and the Barton Family Foundation.

• Allen D. Revised edition. Penguin Books; 2015. Getting Things Done: The Art of Stress-free Productivity. [ Google Scholar ]
• Altshuller G.S. Gordon and Breach Science Publishers; 1984. Creativity as an Exact Science: The Theory of the Solution of Inventive Problems. [ Google Scholar ]
• Menary R. MIT Press; 2010. The Extended Mind. [ Google Scholar ]

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The 10 Project Management Knowledge Areas (PMBOK)

What do you need to know to succeed at project management? Everything! While there’s some truth to that joke, this answer can be narrowed down by looking at the project management knowledge areas as defined in the Project Management Body of Knowledge (PMBOK), a book by the Project Management Institute (PMI), which compiles the fundamental concepts of project management .

What Are the Project Management Knowledge Areas?

The project management knowledge areas can be simply defined as the key aspects of project management that should be overseen by project managers so they can plan, schedule, track and deliver projects successfully with the help of the project team and project stakeholders.

Each of these project management knowledge areas needs to be managed throughout the five project life cycle phases, which are project initiation, project planning, project execution, monitoring and controlling, and project closing. These are the chronological phases that every project goes through, also referred to as project management process groups in PMI’s PMBOK.

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The PMBOK knowledge areas take place during any one of these process groups. You can think of the process groups as horizontal, while the knowledge areas are vertical. The knowledge areas are the core technical subject matter, which is necessary for effective project management.

The 10 Project Management Knowledge Areas

Here’s an overview of each of the 10 knowledge areas of project management, including a brief description of the key project management documents needed to control each of them. All of these project documents are part of the project management plan which includes information about all knowledge areas of project management.

1. Project Integration Management

Project integration management can be simply defined as the framework that allows project managers to coordinate tasks, resources, stakeholders, changes and project variables. Project managers can use different tools to make sure there are solid project integration management practices in place. For example, the project management plan is important for project integration because it works as a roadmap for the project to reach a successful end. Once created, the project plan is approved by stakeholders and/or sponsors before it’s monitored and tracked by the project management team.

Project management software, like ProjectManager , is ideal for project integration management because it’s an online platform that project managers can use to create a project plan, oversee project management knowledge areas and collaborate with their teams online. Choose between online Gantt charts, kanban boards, project calendars and other project management views to plan, schedule and track your projects. ProjectManager also has project reporting features that allow project managers to create project reports they can share with project stakeholders to keep them informed.

The project integration area also includes the directing and managing of the project work, which is the production of its deliverables. This process is monitored, analyzed and reported on to identify and control any changes or problems that might occur.

Also, any change control will be carried out. That might require request forms, approval from stakeholders and/or sponsors or another admin. This area is also part of the project closure at the end of the project.

2. Project Scope Management

Project scope management is one of the most important project management knowledge areas. It consists of managing your project scope, which refers to the work that needs to be executed in a project. To manage your project scope , you’ll need to build a project scope management plan, a document where you’ll define what will be done in your project.

To start building your scope management plan , begin by writing a scope statement. This statement is anything from a sentence to a bulleted list that’s comprehensive to reduce major project risks. Another part of this area is a work breakdown structure (WBS), which is a graphic breakdown of project work.

Validate scope during the project, which means making sure that the deliverables are being approved regularly by the sponsor or stakeholder. This occurs during the monitoring and controlling process groups and is about accepting the deliverables, not the specs laid out during planning.

The scope statement is likely going to change over the course of the project to control the scope, such as if a project falls behind schedule.

3. Project Time Management

Project time management involves estimating your project duration, creating a project schedule and tracking the project team’s progress to ensure the project is completed on time. To do so, the first thing to do is to define your project scope to identify the tasks that should go into your project schedule.

Those project tasks are then put in an order that makes sense, and any dependencies between them are noted. These dependencies are then determined to be either finish-to-start (FS), finish-to-finish (FF), start-to-start (SS) or start-to-finish (SF). This is mostly for larger projects.

With the tasks now sequenced, the project resources required for each must be estimated and assigned. The duration of each task is also determined at this point. All of this leads to a schedule by first determining the critical path and float for each task. You should use project management tools like Gantt charts , kanban boards or project calendars to place the tasks on a timeline, and then work on resource leveling to balance resource usage. Once the project schedule is made, plans to control the schedule are necessary. Earned value management is performed regularly to make sure that the actual plan is proceeding as planned.

4. Project Cost Management

This project management knowledge area involves estimating project costs to create a project budget . To do so, you’ll need to use cost-estimating tools and techniques to make sure that the funds cover the project expenses and are being monitored regularly to keep stakeholders or sponsors informed.

As with other project management knowledge areas, the cost management plan is the document where you’ll explain the method to establish the budget, which includes how and if it will change and what procedures will be used to control it. Each project task will have to be estimated for cost , which means including all resources such as labor, materials, equipment and anything else needed to complete the task.

5. Project Quality Management

A project can come in on time and within budget, but if the quality isn’t up to standard, then the project is a failure. This means that quality management is one of the most critical project management knowledge areas. Your project management plan should include a quality management plan section that specifies the quality control and quality assurance guidelines for your project.

Therefore, to control quality, the deliverables must be inspected to ensure that the standards outlined in the quality management plan are being met.

6. Project Human Resource Management

The project team is your most important resource, so it’s crucial to assemble the best team and make sure they’re happy. But also you need to track their performance to ensure that the project is progressing as planned. A human resource management plan identifies the roles and requirements for those positions, as well as how they fit into the overall project structure.

After you’ve determined the project roles , it’s time to fill those positions and acquire a project team. This can be done in-house by drawing from other departments in the organization, getting new hires or a combination of both. The team needs development, possibly training and other things that’ll make them viable for the project.

Managing the project team is an ongoing responsibility of the project manager. The team is monitored to make sure they’re working productively and that there are no internal conflicts, so everyone is satisfied.

7. Project Communications Management

All knowledge areas of project management are important, but communication management might be paramount as it informs every aspect of the project. Communications inform the team and stakeholders, therefore the need to plan communications management is a critical step in any project.

It’s at this point that the dissemination of communications is determined, including how it’s done and with what frequency. Target who needs what and when. Also, note how communications will occur when issues such as changes arise in the project.

Manage the communications when the project is executed to make sure it runs as planned. This also involves controlling communications by reviewing their effectiveness regularly and adjusting as needed.

8. Project Risk Management

Risk management plans identify how the risks will be itemized, categorized and prioritized. This involves identifying risks that might occur during the execution of the project by making a risk register .

Perform qualitative risk analysis after the biggest risks have been identified and classified by likelihood and impact. Then prioritize them. Then perform quantitative analysis according to their impact on the project, such as its budget, schedule, etc.

Now you’ll need to plan risk responses . If those risks in fact become issues, then a response needs to have been written in advance, with an owner who can make sure the risk is properly identified and handled. Controlling risk involves regularly reviewing the risk register and crossing off those risks that are no longer going to impact the project.

9. Project Procurement Management

This project management knowledge area deals with outside procurement, which is part of most projects, such as hiring subcontractors. This will impact on the budget and schedule. Procurement management planning starts by identifying the outside needs of the project and how those contractors will be involved.

Now conduct those procurements by hiring the contractors, which includes a statement of work , terms of reference, request for proposals and choosing a vendor. You’ll want to control the procurement process by managing and monitoring, and then closing the contracts once the work has been done to everyone’s satisfaction.

10. Project Stakeholder Management

The stakeholders must be happy, as the project has been created for their needs. Therefore, they must be actively managed like any other part of the project. To start, identify the stakeholders through stakeholder analysis and find out what concerns they have. It’s not always easy, but it’s a crucial part of starting any project.

Now plan stakeholder management , which means listing each stakeholder and prioritizing their concerns and how they might impact the project. This will lead to managing stakeholders’ expectations to make sure their needs are met and that you’re in communication with them.

Throughout the project, you’ll want to control stakeholder engagement by determining if the stakeholders’ needs are being addressed. If not, figure out what changes need to be made to either satisfy those needs or adjust the expectations.

Project Management Knowledge Areas vs. Project Management Process Groups

Now that we have a better understanding of what the project management knowledge areas are, let’s explore the differences between them and other similar project management concepts.

We’ve discussed the project management knowledge areas and they’re related to the project management process groups , but they’re not the same thing. The project management knowledge areas are guidelines for the technical side of running a project.

The project management process groups, on the other hand, work with the project management knowledge areas to run the project. The project management process groups are the five main phases of a project: initiating, planning, executing, monitoring and controlling and closing.

Project Management Knowledge Areas vs. Project Management Skills

Again, the project management knowledge areas are how the project is managed. They offer various methods to get work planned, managed, tracked, etc. Project management skills , like process groups, work together with the knowledge area. For example, many of the project management skills are technical, or hard, skills. These include those key knowledge area disciplines from planning to risk and everything in between.

But project management skills go beyond technical skills. These are called soft skills and include things such as being a good leader, having strong communication skills and facilitating collaboration. While these skills are often harder to teach, they’re no less important to the success of the project. Project managers need to be problem-solvers, manage their time wisely, be organized and have critical thinking skills or all the hard skills in the world won’t deliver a successful project.

ProjectManager Helps You Apply the Project Management Knowledge Areas

Project management knowledge areas need powerful tools to be implemented throughout the project’s life cycle. ProjectManager is award-winning project management software that has the features you need to plan, manage and track your project in real time. Our task management, risk management and resource management features give project managers and their teams the tools they need to deliver their projects on time and within budget.

Use Multiple Project Management Views

Every project has a diverse team working together for the same goals, but not necessarily using the same tools. When you’re applying all the project management knowledge areas, you need diversity. That’s why our software gives project managers robust online Gantt charts to plan and schedule their projects while teams can choose between task lists and kanban boards. Stakeholders, who don’t need to get into the weeds of the project, can view progress on calendars. All project views update simultaneously in real time so everyone is on the same page.

Monitor With Real-Time Project Tracking

The project management knowledge areas require monitoring and control to work. You can’t expect the executed project to align with the project plan; you need to review and revise as needed. That is why our software has a variety of tracking tools. You can get a high-level overview of the project with our real-time dashboard , which automatically tracks time, cost and more with easy-to-read graphs and charts. Also, there’s no time-consuming setup required as with other software. We also have secure timesheets to monitor your team’s progress on their tasks and a color-coded workload chart that makes it easy to balance workload and keep teams productive and working at capacity.

Create Project Reports in Minutes

Another tool to track progress and performance is our customizable reports . You can get more data than from the dashboard by generating a report in only a couple of keystrokes. Get reports on project or portfolio status, workload, timesheets, variance and much more. All reports can be filtered to focus on only what you want to see. Then they can be shared in a variety of formats to keep stakeholders informed.

Project management knowledge areas bring a project to life, but life can be chaotic and complex, which is why project managers need a tool to help manage all these moving parts of a project. ProjectManager is online project management software with real-time dashboards and Gantt charts to monitor the project accurately throughout its many phases. See how it can help you manage your projects by taking this free 30-day trial.

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More From Forbes

Project managers: skills and traits that make good ones great.

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Guiding a tech project from start to finish entails staying on top of seemingly endless details, decisions and data (and sometimes, detours). From making sure progress is achieved on time and on budget to keeping stakeholders updated to ensuring teams work together smoothly—and much more—project managers are constantly keeping multiple balls in the air, and if they drop one, a project can quickly go off the rails.

Even though theirs is not a simple job, the very best project managers can make the jobs of their teammates much easier. Below, 20 members of Forbes Technology Council discuss the skills and traits that elevate a good project manager to a great one and why these characteristics are so impactful.

1. Strong Written And Verbal Communication

High-quality communication, in all its forms, is one skill effective project managers must have and improve on. Communication must be objective, timely and complete, whether written or verbal. Meetings with team members, one-on-one discussions, presentations, announcements, technical reports and emails are all instances of essential communication resources for a successful project manager. - David William Silva , Algemetric

2. Asking ‘Why?’ (A Lot)

A great project manager will embrace their inner toddler, asking “why?” a lot. If someone wants to add a feature, asking “why?” will help determine if it is in or out of scope. If someone is pushing a deadline, asking “why?” will help determine if deploying more resources or swapping dependencies will alleviate the challenge, or if indeed a deadline change is needed. - Patti Mikula , Hackworks Inc .

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3. Leadership And Problem-Solving Skills

In project management, effective leadership and problem solving are the most important skills. A project manager must not only inspire and guide their own team, but also inspire confidence through their conviction in the client’s vision. Possessing a problem-solving mindset is crucial to navigating uncertainties and unexpected challenges, which is at the core of every successful project. - Shraddha Thanawala , Remiges Technologies P Ltd

4. High Emotional Intelligence

Tech skills may dazzle, but teams thrive on humanity. Project managers with emotional intelligence have a galvanizing effect on their teams and the organization. They don’t just crack whips louder; they inspire ownership and camaraderie. Teams unleash discretionary effort when they are led not by authority but by authenticity. - HK Bain , Digitech Systems, LLC

5. An Understanding Of How The Role Differs From That Of A Program Manager

It’s important to understand the difference between a program manager and a project manager. A program manager’s role is more strategic, and their work is tied to meeting business and organizational goals. On the other hand, a project manager is really incentivized to focus on the delivery of a project. Both roles are necessary and have similar guiding principles, but the differences are significant. - Scott Sumner , Medidata - Dassault Systémes

6. The Ability To Anticipate Issues

A key characteristic of a highly effective project manager is the ability to anticipate issues and plan proactively for the future. This foresight enables them to mitigate risks and keep projects on track. Execution is the key KPI. - Saif Sultan , Volos Portfolio Solutions, Inc .

7. An Agile Mindset

Highly effective project managers embrace an agile mindset. This means delivering clear communication of business objectives while allowing teams the space to determine how to achieve those goals. This is how project managers can encourage creative problem solving among their teams, allowing them to iterate and adapt as needed, which ultimately leads to fulfilled teams. - Mark Lorion , Tempo Software

8. An Unbiased Focus On Progress

Project managers should provide unbiased updates to management, cross-functional teams and executive leadership on a weekly basis. Highlight what is working well and call out what needs management’s attention. An ideal project manager leverages the technical leadership available to them to resolve issues in a scalable way. - Ravi Bandlamudi , AtoB

9. A Willingness To Dive Deep

Undoubtedly, a crucial trait of a great project manager is the ability and willingness to dive deep. This doesn’t come down to domain-specific skills or technical capability; rather, it’s the application of analytical thinking to resolve issues and uncover opportunities. It requires good instincts to know when to do a deep dive, which items need attention to be resolved and which representative set of successful items to observe to know what “good” looks like. - Elliott Cordo , Data Futures

10. Resilience

Inevitably, projects will encounter roadblocks. Project managers need resilience to push through challenges. A strong project manager builds on trust and clear communication with the team so that they can navigate challenges effectively, adapt quickly and support each other to keep the project on track. - Ruhbir Singh , Tatvic

11. The Ability To Unite Teams

An exceptional project manager is skilled in communication, adept at conveying clear information and actively listens. They effectively tailor the project’s vision to diverse audiences. The ability to unite various teams across the organization to work toward a shared goal and ensure each member understands their role in achieving the overarching vision of the project is crucial. - Rahil Shah , Zomentum (Pactora Inc.)

12. ‘Empathetic Precision’

In my experience, one characteristic of a highly effective project manager is “empathetic precision"—that is, the ability to relate to the needs of team members while maintaining a relentless focus on zero variation from the budgeted cost and time. Empathy allows them to build strong relationships, foster collaboration and address challenges effectively, all while ensuring the project is completed without deviation from the roadmap. - Sandy Hardikar , Network Science Ltd.

13. Rigorous Focus

A project manager has so much to do. They must empower and uplift the team, make complicated things simple so they can be understood by everyone, get quick approvals if needed, set and monitor KPIs, maintain a strong project rhythm, and more. All of this requires constant, rigorous focus. - Rosalba Carandente , Baker Hughes

14. Accountability

Given its linear job description, the project manager role seems straightforward, but there are definitely qualities that set a great PM apart from a mediocre one. One such quality is accountability—a feeling of ownership of a project that goes beyond the tasks required to deliver it. When a PM becomes the “mini CEO” of a project, they use high-level critical thinking to resolve challenges before they happen. - Antony Demekhin , Tuney

15. A Commitment To Advocating For Business Users

When a project—for example, an AI solution—has a team whose members include both technical and business users, the project manager should make sure that the business users are heard and understood rapidly at every step and that the final product delivered reflects the business users’ feedback about specifics, such as the data used, variables, KPIs and so on. - Zehra Cataltepe , TAZI AI

16. Being Detail-Oriented

The best project managers that we have hired were extremely detail-oriented. This is crucial when managing a product, because there are typically many moving parts. Staying organized and paying attention to details ensures products are delivered on time and within budget. - Trent Hoerr , FPFX Tech

17. A Knack For Sales

A highly effective skill in project management is clear and concise communication, which is crucial for team coordination and stakeholder alignment. I’d also say that I’ve seen proficiency in sales complement this by enabling effective leadership, persuasive negotiations and client relationship building, all of which contribute to project success. - Jeremy Vaughan , Start Left Security

18. The Ability To Bridge Business Needs And Technology

The best CEOs come from project management. Great PMs bridge business needs and technology by speaking both languages and establishing strong rapport with both groups. The best PM is the company’s demo god, has the top five customers’ numbers in their phone, and takes engineering out for a beer once a quarter. - Ari Kahn , Bridgeline Digital

19. Taking The Success Of Each Project Personally

Amazing project managers take success very personally. Driven to make positive contributions, they see each project as a chance to strive toward self-actualization and reach their full potential. As a result, they push themselves to take full ownership and minimize any chance of failure. A successfully completed project is often a testament to the project manager’s desire for personal fulfillment. - Hamid Farooqui , Sogolytics

20. Curiosity

In my experience, one crucial characteristic of a highly effective project manager is curiosity. A curious project manager continuously seeks new insights, solutions and approaches, fostering innovation and adaptability, which are key to project success. - Patrick Emmons , DragonSpears, Inc.

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Why do managers go home every night, with a full briefcase, feeling badly about what they didn’t get done that day, instead of feeling good about what they did get done?

This is the question that started the research program that eventually led to the establishment of Effective Managers TM , an organization dedicated to helping managers be more effective.

Too often, organizations can inadvertently put roadblocks in the way of managers – sometimes the very systems that are put in place to help managers actually hinder them in unintended ways. Opinions abound on how to improve performance, but no published research exists that quantifies manager effectiveness and the drivers that reinforce or constrain effectiveness.

The Telfer School of Management, University of Ottawa, and Effective Managers TM partnered to undertake ground breaking research investigating managerial effectiveness in the workplace. This research explored new aspects of the management literature.

The research study closed at the end of 2013. Nearly 200 managers, representing nearly 2,000 manager-subordinate relationships from eight organizations (private sector, not for profit and government) participated in the Effective Managers TM research project. The results are now being written up for management sciences journals.

Managers report they are operating at just over 55% effectiveness.

They are attending meetings they shouldn’t attend, reading emails they shouldn’t have to read, fighting jurisdictional battles they shouldn’t have to fight, and duplicating work also assigned elsewhere.

The bottom line is that, through research, we have an understanding of the actual effectiveness of managers. On average managers feel they are operating at just 55% effectiveness. That is an ineffectiveness ratio of over 2 days a week! Managers identified that they spend just over 20% of their time doing work that is not part of their job. In addition, they spend nearly 25% of their time doing work that could (we would say should) be delegated to an administrative support position.

Here are some of the key findings:

• Manager effectiveness is very highly correlated with clarity of delegated accountability, and the degree to which managers “feel” they are accountable.
• Over 1/3 of managers are not clear about what their managers hold them accountable for.
• Only 1/3 of managers don’t feel they are in conflict situations in the workplace.
• Organizational learning measures are very highly correlated to organization effectiveness.
• Less than 1/3 of managers believe that the corporate performance management system works.
• Less than 1/2 of managers are delegated clear objectives

How Would Your Organization Stack Up?

You don’t have to wait for the published journals. Participation in the Manager Effectiveness TM Survey is now available to any organization, in English or French, at a very reasonable price point. A 94-question confidential survey has been developed to gather data directly from managers, who can log on to a secure web site to provide their direct input on these measures. Traditional employee surveys require all employers to participate. With this survey, a CEO can get the results with an investment of 20 – 30 minutes of each manager’s time.

Email Dwight to discuss further.

Accountability measure.

The research shows that Accountability is very highly correlated with manager effectiveness. Accountability is at the heart of managerial leadership. It is important that employees have a clear understanding of what they are being held accountable for and how their outcomes will contribute to the success of their organization. Accountability is also correlated with team and organization effectiveness.

Accountability has two dimensions:

• Clarity of Accountability – the degree to which managers are clear about the accountability and authority that has been delegated to them. As an organizational measure, this means thinking about how well the organization can translate accountability for output from the strategic plan through the CEO down to each individual manager in the organization. This measure correlates highly with a managers’ perceived self-effectiveness.
• Felt Accountability – the degree to which managers feel they are accountable. Felt accountabilities can be related to being accountable to a manager for work, or it could be other things that are not real accountabilities, but feel like accountabilities, such as responsibilities to customers, to stakeholders, to peers, and so on.

To understand the disconnect, and how organizations have gone so wrong, it is important to realize that Accountability actually has two dimensions. First, what is the clarity of the accountability and authority that has been delegated to managers? For instance, if I am a manager, am I clear about not only what my manager is holding me accountable for, but also the authority I have for doing my work?

We call this the Clarity of Accountability dimension. As an organizational measure, this means thinking about how well the organization can translate accountability for output from the strategic plan, through the CEO, down to each individual manager in the organization. This measure correlates highly with a managers’ perceived self-effectiveness.

The second dimension of accountability is Felt Accountability . This concept has been written about in management sciences literature. It refers to the degree to which an individual feels he or she is accountable. It could be related to being accountable to a manager for work, or it could be other things that are not real accountabilities, but feel like accountabilities. Examples of Felt Accountability include:

• relationships with customers
• relationships with peers
• project work
• self-held beliefs

In all of these examples, these are not real accountabilities because managers are not held to account by a specified other that has the authority to hold them to account. Nevertheless, they can be quite distracting if the managers of managers do not take them into account when setting the context for doing work. Felt Accountability , interestingly, scores much higher than Clarity of Accountability .

This reinforces the perspective that people care about their work and want to do well.

 The question is not whether managers feel accountable. They do.

The question is whether they feel accountable for the right things. This is the manager’s job – to be clear about those things for which they will hold their subordinates to account.

Other Measures

A series of seven measures are correlated with Accountability in organizations. These are important to understand, as they provide the insight into root causes that can constrain or improve accountability in the workplace.

Workflow – The extent to which managers perceive work flowing smoothly across the organization. This measure assesses the extent to which managers perceive work flowing smoothly across the organization. If managers don’t understand their accountability and authority with respect to peers in other parts of the organization, they will gravitate towards “I’ll just do it myself – it’s easier”. Work tends to happen within distinct organizational units. If work does not flow smoothly across the organization, it can lead to misunderstandings and duplication of effort, both of which are counter to Manager Effectiveness.

Fewer than 40% of managers surveyed felt that work flowed smoothly across their organizations.

Organizational Learning  – The extent to which individuals in the organization learn from others, share, experiment and transfer knowledge. This measure describes the relationship between effective organizational learning with other organizational factors, and its direct impact on the effectiveness of managers. Organizations continually face challenges in managing their knowledge assets. To the extent that organizations are better at managing and transferring knowledge, one would expect that managers would be more effective. The data reinforces these concepts with high correlations between Organizational Learning and Clarity of Accountability, and a high correlation with Manager Effectiveness directly. High degrees of organizational learning were correlated with high accountability.

Role Conflict – The degree of conflict that managers experience in their day to day work. This measure assesses the degree of conflict that managers experience in their day to day work. One would expect that in organizations where there is a lack of clarity of accountability, that there would be increased role conflict. The data did show this to be the case, as these two measures are very highly negatively correlated. Role conflict was high; almost half of managers agreed with statements that described conflict situations

Corporate Systems – Providing support to managers for doing their work. Organizations have in place organization-wide systems that are intended to support employees in their work. These systems also have organizational objectives. For example, Finance must provide certain information to the Board and to the CEO in a timely way for the effective management and governance of the organization. Finance also provides support to employees, such as provision of expenditures against budgets, processing expense accounts, and so on. What often happens is that the systems that have been put in place, or should be put in place to support management don’t get the attention they deserve from the CEO and executive management. The balance between serving the organization and supporting the manager can become skewed, often to the point where managers see the support system as an overall burden instead of a support. Managers almost universally feel that corporate systems do not provide the appropriate amount of support, and that they are skewed toward the organization as a whole rather than designed to support managers in their work.

Manager’s Manager Capability – The extent to which managers feel that their manager is capable. The immediate question one might ask is: What is the role of managers of managers? The CEO manages Vice Presidents, Vice Presidents manage Directors, and so on. In each of these cases, the manager of the managers would seem to have an important role in terms of the delegation of accountability to their subordinate managers. If a manager is not capable at doing her / his job, the subordinate manager is less likely to receive the clarity required to be effective at his / her job. Managers, in general, feel that their own managers are capable. Although there is room for improvement, this is positive. The managerial chain in organizations is critical to effective delegation. And as we have seen earlier in this report, clarity of accountability has significant room for improvement. If a manager is not capable at doing her / his job, the direct report manager is less likely to receive the Clarity of Accountability required to be effective at his / her job. Similarly, if the manager does not perceive that their manager is capable, they will not have the degree of Felt Accountability necessary for effectiveness. High manager’s manager capability was correlated to high accountability.

Interdependence – How much managers depend on other managers in parts of the organization to do their work. Interdependence is a measure that explores the reliance of individuals on others, in other parts of the organization, for success in their work. Interdependence in and of itself isn’t a positive or a negative factor – it is an indicator of a certain state in organizations. Some organizations, by their nature, require a greater independence of their managerial workforce for production and delivery of products and services. High interdependence indicates that managers rely highly on managers in other parts of the organization for success in their work..

Team and Organizational Effectiveness – The effectiveness of both teams and the organization as a whole.

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A domain-specific lexicon for improving emergency management in gas pipeline networks through knowledge fusing.

1. Introduction

• We developed a specialized domain-specific lexicon for emergencies in gas pipeline networks after extensively reviewing the literature and consulting with field experts. To our knowledge, this is the first lexicon specifically focused on this area.
• We trained a Chinese pre-trained model specifically for emergencies in gas pipeline networks, successfully extracting semantic nuances from substantial domain-specific data.
• We introduced a hybrid method that enhances the traditional TF-IDF technique with deep learning to incorporate domain knowledge more effectively. Initially, statistical methods filtered out less relevant terms, followed by deep learning to further develop and enhance the lexicon with detailed domain knowledge.

2. Materials and Methods

2.1. data collection and processing, 2.1.1. standard collection and terminology extraction, 2.1.2. risk inventory collection and processing, 2.1.3. domain data collection and processing, 2.2. candidate word set construction, 2.3. domain-specific bert fine tuning, 2.4. lexicon expansion, 3.1. candidate words, 3.2. expanded lexicon, 3.3. impact analysis, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Inside China’s 2023 Natural Gas Development Report. Available online: https://www.energypolicy.columbia.edu/inside-chinas-2023-natural-gas-development-report/ (accessed on 9 May 2024).
• Zheng, D.; Zhang, J.; Liu, Z.; Liu, Q.; Liu, C.; Yao, W.; Li, M. Effects of Pipeline Pressure on Diffusion Characteristics of Leaked Natural Gas in Tunnel Space. ACS Omega 2023 , 8 , 10235–10241. [ Google Scholar ] [ CrossRef ]
• Wang, W.; Mou, D.; Li, F.; Dong, C.; Khan, F. Dynamic Failure Probability Analysis of Urban Gas Pipeline Network. J. Loss Prev. Process Ind. 2021 , 72 , 104552. [ Google Scholar ] [ CrossRef ]
• Li, J.; Yan, M.; Yu, J. Evaluation on Gas Supply Reliability of Urban Gas Pipeline Network. Eksploat. Niezawodn.—Maint. Reliab. 2018 , 20 , 471–477. [ Google Scholar ] [ CrossRef ]
• Tian, F.-J.; Chen, J.K.C. Ranking the Social-Impact Factors for Major Security Emergency of Oil and Gas Pipelines in Urban. In Proceedings of the 2016 Portland International Conference on Management of Engineering and Technology (PICMET), Honolulu, HI, USA, 4–8 September 2016; pp. 2067–2076. [ Google Scholar ] [ CrossRef ]
• Varsegova, E.; Dresvyannikova, E.; Osipova, L.; Sadykov, R. Damage Areas during Emergency Depressurization of a Gas Pipeline. E3S Web Conf. 2019 , 140 , 06007. [ Google Scholar ] [ CrossRef ]
• Heidarysafa, M.; Kowsari, K.; Barnes, L.; Brown, D. Analysis of Railway Accidents’ Narratives Using Deep Learning. In Proceedings of the 2018 International Conference on Big Data, Orlando, FL, USA, 17–20 December 2018; pp. 1446–1453. [ Google Scholar ] [ CrossRef ]
• Xu, H.; Li, Y.; Zhou, T.; Lan, F.; Zhang, L. An overview of the oil and gas pipeline safety in China. J. Ind. Saf. 2024 , 1 , 100003. [ Google Scholar ] [ CrossRef ]
• Song, X.Y.; Li, X.R.; Liang, Z.Q.; Li, R. Research on the Demand for Emergency Rescue Materials and the Optimization of Rescue Points in Gas Pipeline Leakage and Explosion. J. Saf. Environ. 2024 , 24 , 1136–1142. [ Google Scholar ] [ CrossRef ]
• Zhou, X.; Yang, D.; Chen, X.; Fang, L. Dynamic Evolution Computing of Leakage and Diffusion from Pipeline Gas and Risk Analysis. Int. J. Environ. Sci. Technol. 2023 , 20 , 6091–6102. [ Google Scholar ] [ CrossRef ]
• Chen, X.; Lin, W.; Liu, C.; Yang, F.; Guo, Y.; Li, X.; Yuan, S.; Reniers, G. An Integrated EDIB Model for Probabilistic Risk Analysis of Natural Gas Pipeline Leakage Accidents. J. Loss Prev. Process Ind. 2023 , 83 , 105027. [ Google Scholar ] [ CrossRef ]
• Parlak, B.O.; Yavasoglu, H.A. A Comprehensive Analysis of In-Line Inspection Tools and Technologies for Steel Oil and Gas Pipelines. Sustainability 2023 , 15 , 2783. [ Google Scholar ] [ CrossRef ]
• Shaukat, K.; Hameed, I.A.; Luo, S.; Javed, I.; Iqbal, F.; Faisal, A.; Masood, R.; Usman, A.; Shaukat, U.; Hassan, R.; et al. Domain Specific Lexicon Generation through Sentiment Analysis. Int. J. Emerg. Technol. Learn. (IJET) 2020 , 15 , 190–204. [ Google Scholar ] [ CrossRef ]
• Cheng, Y.; Huang, Y. Research and Development of Domain Dictionary Construction System. In Proceedings of the International Conference on Web Intelligence, Leipzig, Germany, 23–26 August 2017; Association for Computing Machinery: New York, NY, USA, 2017; pp. 1162–1165. [ Google Scholar ]
• Ren, W.; Zhang, H.; Chen, M. A Method of Domain Dictionary Construction for Electric Vehicles Disassembly. Entropy 2022 , 24 , 363. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kohita, R.; Yoshida, I.; Kanayama, H.; Nasukawa, T. Interactive construction of user-centric dictionary for text analytics. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, 5–10 July 2020; Jurafsky, D., Chai, J., Schluter, N., Tetreault, J., Eds.; Association for Computational Linguistics: Stroudsburg, PA, USA, 2020; pp. 789–799. [ Google Scholar ]
• Zhang, Y.; Li, B.; Lv, X.; Sun, N.; Tian, J.-J. Research on domain term dictionary construction based on Chinese Wikipedia. DEStech Trans. Comput. Sci. Eng. 2018 , 3 . [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Duan, J.; Wang, M.; Guan, Y.; Lin, Q. A method for building Chinese domain lexicon based on new words recommendation. In Proceedings of the 2022 3rd International Conference on Computer Science and Management Technology (ICCSMT), Shanghai, China, 18–20 November 2022; pp. 516–522. [ Google Scholar ]
• Sood, M.; Kaur, H.; Gera, J. Creating domain-based dictionary and its evaluation using classification accuracy. In Proceedings of the 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 17–19 March 2021; pp. 341–347. [ Google Scholar ]
• Han, N.; Wu, J.; Fang, X.; Teng, S.; Zhou, G.; Xie, S.; Li, X. Projective double reconstructions based dictionary learning algorithm for cross-domain recognition. IEEE Trans. Image Process. 2020 , 29 , 9220–9233. [ Google Scholar ] [ CrossRef ]
• Luo, X.; Deng, Z.; Yang, B.; Luo, M.Y. Pre-trained language models in medicine: A survey. Artif. Intell. Med. 2024 , 154 , 102904. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Devlin, J.; Chang, M.-W.; Lee, K.; Toutanova, K. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Minneapolis, MN, USA, 2–9 June 2019; Association for Computational Linguistics: Stroudsburg, PA, USA, 2019; pp. 4171–4186. [ Google Scholar ]
• Cui, Y.; Che, W.; Liu, T.; Qin, B.; Yang, Z. Pre-training with whole word masking for Chinese BERT. IEEE/ACM Trans. Audio Speech Lang. Process. 2021 , 29 , 3504–3514. [ Google Scholar ] [ CrossRef ]
• Rose, R.L.; Puranik, T.G.; Mavris, D.N.; Rao, A.H. Application of structural topic modeling to aviation safety data. Reliab. Eng. Syst. Saf. 2022 , 224 . [ Google Scholar ] [ CrossRef ]
• Na, X.; Ling, M.; Liu, Q.; Li, W.; Deng, Y. An improved text mining approach to extract safety risk factors from construction accident reports. Saf. Sci. 2021 , 138 , 105216. [ Google Scholar ]
• Yi, R.; Zhang, T.; Xing, X.; Ma, W.; Zhang, K.; Liu, W. Construction of a disaster and accident domain dictionary integrating standard knowledge. China Stand. 2022 , 15 , 88–94+117. [ Google Scholar ]
• Pillai, P.; Ryali, S.; Maniar, H.; Mangsuli, P.; Abubakar, A. NLP Applications in the Oil and Natural Gas Industry. In Proceedings of the Second International Meeting for Applied Geoscience & Energy, Houston, TX, USA, 28 August–1 September 2022; Society of Exploration Geophysicists and American Association of Petroleum: Houston, TX, USA, 2022; pp. 1956–1960. [ Google Scholar ] [ CrossRef ]
• Liu, G.; Boyd, M.; Yu, M.; Halim, S.Z.; Quddus, N. Identifying Causality and Contributory Factors of Pipeline Incidents by Employing Natural Language Processing and Text Mining Techniques. Process Saf. Environ. Prot. 2021 , 152 , 37–46. [ Google Scholar ] [ CrossRef ]
• Huang, J.; Chang, K.C.-C.; Xiong, J.; Hwu, W. Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana, Dominican Republic, 7–11 November 2021; Association for Computational Linguistics: Stroudsburg, PA, USA, 2021; pp. 1694–1703. [ Google Scholar ] [ CrossRef ]
• Abdoul Nasser, A.H.; Ndalila, P.D.; Mawugbe, E.A.; Emmanuel Kouame, M.; Arthur Paterne, M.; Li, Y. Mitigation of Risks Associated with Gas Pipeline Failure by Using Quantitative Risk Management Approach: A Descriptive Study on Gas Industry. J. Mar. Sci. Eng. 2021 , 9 , 1098. [ Google Scholar ] [ CrossRef ]
• International Organization for Standardization. Available online: https://www.iso.org/home.html (accessed on 31 July 2024).
• International Telecommunication Union. Available online: https://www.itu.int:443/zh/Pages/default.aspx (accessed on 31 July 2024).
• International Electrotechnical Commission. Available online: https://www.iec.ch/homepage (accessed on 31 July 2024).
• Standard for Safety Inspection of Urban Gas Facilities ; Zhejiang Provincial Department of Housing and Urban-Rural Development: Hangzhou, Zhejiang, 2020.
• Technical Specification for Trenchless Rehabilitation and Replacement Engineering of City Gas Pipe ; Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2011.
• Technical Specification for Leak Detection of City Gas Piping System ; Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2014.
• Technical Specification for Control of External Corrosion on Under-Ground Gas Pipeline of Steel in Area of Cities and Towns ; Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2014.
• Xu, H.; Liu, Y.; Shu, C.-M.; Bai, M.; Motalifu, M.; He, Z.; Wu, S.; Zhou, P.; Li, B. Cause Analysis of Hot Work Accidents Based on Text Mining and Deep Learning. J. Loss Prev. Process Ind. 2022 , 76 , 104747. [ Google Scholar ] [ CrossRef ]
• Deng, C.; Yu, H.; Fan, G.; Zhu, H. Sentiment Analysis of Chinese Texts for Gas Customer Service Hotline. J. East China Univ. Sci. Technol. Nat. Sci. Ed. 2019 , 45 , 140–147. [ Google Scholar ]
• Hu, J.; Huang, R.; Xu, F. Data mining in coal-mine gas explosion accidents based on evidence-based safety: A case study in China. Sustainability 2022 , 14 , 16346. [ Google Scholar ] [ CrossRef ]
• Zhang, B.; Yao, X.; Li, H.; Aini, M. Chinese Medical Named Entity Recognition Based on Expert Knowledge and Fine-Tuning Bert. In Proceedings of the 2023 IEEE International Conference on Knowledge Graph, ICKG, Shanghai, China, 1–2 December 2023; IEEE: New York, NY, USA, 2023; pp. 84–90. [ Google Scholar ]
• Babić, K.; Guerra, F.; Martinčić-Ipšić, S.; Meštrović, A. A comparison of approaches for measuring the semantic similarity of short texts based on word embeddings. J. Inf. Organ. Sci. 2020 , 44 , 231–246. [ Google Scholar ] [ CrossRef ]
• Steck, H.; Ekanadham, C.; Kallus, N. Is cosine-similarity of embeddings really about similarity? In Proceedings of the ACM on Web Conference 2024, Singapore, 13–17 May 2024; Association for Computing Machinery: New York, NY, USA, 2024; pp. 887–890. [ Google Scholar ]
• Wang, L.X. Research on the construction of a domain dictionary and its application in public safety event identification. J. Inf. Explor. 2020 , 02 , 13–20. [ Google Scholar ]
• Fan, H.W.; Fan, S.X.; Li, B.; Feng, C.Y.; Luo, H.M. Research on the construction method of professional dictionaries in the field of power dispatching. Electr. Power Inf. Commun. Technol. 2021 , 57 , 57–65. [ Google Scholar ] [ CrossRef ]
• Huang, J.Y.; Sun, R.Y. Construction of a dictionary in the field of commodity trading. J. Beijing Inf. Sci. Technol. Univ. (Nat. Sci. Ed.) 2022 , 71 , 71–75. [ Google Scholar ] [ CrossRef ]
• Chen, J.; Xi, N.L.; Li, J.M.; Wan, X.R. Construction of a sentiment dictionary in the field of education by integrating Skip-gram and R-SOPMI. J. Appl. Sci. 2023 , 870 , 870–880. [ Google Scholar ]
• Xu, Y.; Wei, W.; Wang, Z. Development of a Chinese Tourism Technical Word List Based on Corpus Analysis. In Chinese Lexical Semantics ; Springer: Singapore, 2024; pp. 405–419. [ Google Scholar ]
• Xu, Z. RoBERTa-Wwm-Ext Fine-Tuning for Chinese Text Classification. In Proceedings of the 2021 International Conference on Asian Language Processing (IALP), Singapore, 23–25 October 2021; pp. 216–220. [ Google Scholar ]
• National Gas Accident Analysis Report for the First Half of 2023 ; Urban and Rural Construction: Newcastle, South Africa, 2023; pp. 18–23.

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Share and Cite

Zhao, X.; Hu, Y.; Qin, T.; Wan, W.; Wang, Y. A Domain-Specific Lexicon for Improving Emergency Management in Gas Pipeline Networks through Knowledge Fusing. Appl. Sci. 2024 , 14 , 8094. https://doi.org/10.3390/app14178094

Zhao X, Hu Y, Qin T, Wan W, Wang Y. A Domain-Specific Lexicon for Improving Emergency Management in Gas Pipeline Networks through Knowledge Fusing. Applied Sciences . 2024; 14(17):8094. https://doi.org/10.3390/app14178094

Zhao, Xinghao, Yanzhu Hu, Tingxin Qin, Wang Wan, and Yudi Wang. 2024. "A Domain-Specific Lexicon for Improving Emergency Management in Gas Pipeline Networks through Knowledge Fusing" Applied Sciences 14, no. 17: 8094. https://doi.org/10.3390/app14178094

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