research repository jira

Using Jira as a research repository, part one: pros & cons

I built a research repository in Jira and wanted to get my process down in writing for those in the same boat I was in: weighing the pros and cons of Jira without a guide.

UX repositories are critical, but selecting the right platform for your organization is not easy. Since I created our repository I have heard from many people wondering specifically about using Jira and whether it can work despite not being designed as a research repository.

I wanted to get my process down in writing for those in the same boat I was in: weighing the pros and cons of Jira without a guide.

This article is two parts: in Part One I share our selection process, in Part Two our steps for creating the actual Jira project. I hope you find something useful here and it saves you some time.

Why a research repo?

When I joined my current organization I found there was really valuable research data already coming in from our user base through multiple feedback channels. But if it didn’t find its way into a current project it was just getting lost. We were not only losing opportunities to know our products and users better, but we were also wasting time (and frustrating stakeholders) by asking them the same questions again and again times.

A repository for our research data was clearly needed. We set out to research and build a solution.

Without a repository we were losing opportunities to know our products and users better, and wasting time asking the same questions over and over again.

Our goal was to support continuous user research, build a repository of “timeless” data that would increase in value and usefulness over time, and make it easily searchable and available to all members of the team.

Part One: Why we selected Jira for our research repository

It’s an exciting time to do User Research. There is so much innovation happening right now and new tools coming on the market. At the same time the field is still rather new and there is no established user research taxonomy (though it’s one of the topics the wonderful Research Ops project is trying to address). Every organization that goes down this road is in some ways forging their own new path.

Selecting the right platform for a repository, one that will serve your organization over the long term, is not easy. Kate Towsey curates this great list of tools , and it’s a wonderful place to get started thinking about your software needs, but even this list has limited options for research repositories.

In the end, it’s just a database

One important point to keep in mind is that a research repository is a database, pure and simple. It might be bedazzled with features and options, but at it’s heart its a big ol’ table. There are a lot of software options for creating a database table (an excel document or custom sql among them), the question is simply how to make sure you have the fields you need, that it’s manageable for your team, and you can create the views that give you insight into the data.

Our decision table

There is a lot to weigh when selecting the software for your organization’s research repository. How much data will you eventually store, and how quickly will it be coming in? What is the technical expertise — and size — of the team who will be managing the repo? What custom needs does your organization have? And what is your budget?

We asked all those questions and more, as well as considering the deliverables we would need to extract from the data. Who will be reading it, what kinds of questions will they want to answer, and how quickly can they glean that information?

We explored many software options in our quest for the right fit. Below is our decision table with the “Final 7” software options that made the cut for more testing:

Jira: the imperfect best choice

Ultimately Jira emerged as the best — if imperfect — fit for our research repository. The strongest draw for our team was distributed access to the data: the entire organization is already heavily invested in Jira for handling software tickets. We all use the platform on a daily basis, reducing barriers to shared entry.

Here is how Jira held up against our most important criteria:

Cost: Jira was a good fit for our organization on cost because we were already using it for software development tracking. No additional cost.

Data security: Jira cloud encrypts all their data and uses industry-standard accounts management.

Will it be sustainable by a small UX team? We felt we would be able to harness our existing experience using Jira — and it’s integrations with other software — to get more out of this tool with a small team.

Will it integrate well into our workflow? Because of our existing Jira use for software development this was a yes.

Distributed access to data: This was the strongest point for us, and ultimately the reason why we chose Jira. Our entire team is already invested in, and interacts daily with, the Jira interface. Switching to a different project to view relevant research data is a fairly easy step, even for a busy designer or developer.

If the data isnt seen when it’s needed — by the people that need it — then it’s useless, no matter how great the software or how well the data is organized. Using Jira would bring the data closer to the teams that need it.

Creating actionable items: Another important benefit was the ability to turn insights from the UX repo into actionable backlog items right within Jira. They would immediately be seen by our development team in a language native to their workflow, no further translation necessary.

Stability: Similar to data security, we felt secure in Atlassian’s size and category dominance.

Export/Import data: Especially at this early stage in the development of Research Ops, import/export functions will help you preserve your data beyond any one software solution. Its also a huge timesaver when working with large data sets.

Directly contact users: Jira does not have this capability, even with marketplace addons. I havn’t yet found a good solution that offers both research repo and CRM functions at a high level, it’s the unicorn of UX repos I suppose. We opted for separate solutions.

AI-assisted insights: We also ended up not meeting this criteria. Nice, but not a dealbreaker)

Is the software UX focused? Jira is not UX focused, we had to bend it to our will, but it ultimately did what we needed. I share our tips in detail in the second part of this article; They might save you time.

Data types: Jira met our primary need for storing atomized and qualitative feedback. We found our quantitative data had a shorter lifespan than descriptive feedback so that was not our primary focus.

Data source fidelity: We can use Jira’s linking function to link back to original observations in bug and feature tickets. Linking back to the original research right within the ticket provides further context for developers, as well as validation. Jira’s linking function is a simple way to chip away at the discovery-knowledge gap.

If you think Jira is a good fit for your team’s research repository but arent familiar with customizing a Jira project, Part two of this article shares a step-by-step of how we created our user research repository.

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The UX Research Repository Landscape: What You Need to Know

Check out our comprehensive guide to choosing a research repository that suits your specific needs, with expert advice from research practitioners.

Welcome to our comprehensive guide to choosing a UX research repository that suits your organization’s needs. Grab a cup of tea , then dive into this treasure trove of priceless information and expert advice from research practitioners .

If you need evidence that research matters, look closely at the device you’re reading this on. Whether it’s Android, iOS or Windows (or Linux, we don’t discriminate), every detail of the user experience is likely steeped in research, and the titans of tech invest heavily in UX research each year.

Despite research’s growing importance, researchers today still grapple with age-old problems. User interviews take hours on end to tag properly and distill into key themes. New hires inherit a complex puzzle as they try to piece together fragmented findings across an organization. Without a central platform to elevate insights, user feedback and the value of research are drowned out for prospective audiences.

User research continues to be time- and resource-intensive. If only there were a solution to rid us of the dreaded drudgery of research…

Enter the UX research repository.

Summary of the UX Research Repository Landscape

• What is a research repository?
• Why you need a research repository
• How to organize a research repository
• Essential research repository features
• Choosing a research repository in 2023
• Benefits of a modern research repository tool
• Research repositories: Getting started

What is a Research Repository?

A research repository is a central archive for organizing and storing research, insights and user information. Think of a research repository as an encyclopedia, exclusively made up of a company’s findings — it brings all user research in one place so that you can easily conduct , analyze , organize and share customer insights across the organization.

A common misconception is that a research repository serves researchers exclusively. This couldn’t be farther from the truth — since research influences most departments within a company, a UX research repository acts as a knowledge bank for the entire organization.

So what type of knowledge goes into a research repository? The concept of ‘atomic research’ breaks it down into these four components:

At the end of the day, researchers provide a service for end users and key decision makers. Research repositories help you consolidate data, unearth patterns and trends across studies old and new, and facilitate informed business decisions.

What is the Difference Between a Database and a Repository?

A database is a structured collection of data organized into tables of rows and columns. Using a database management system, you can access, retrieve, update and query the data. Databases usually store data for a specific purpose, such as a CRM tool housing customer data. A database offers security and protection for confidential information. 

A repository is a collection of elements, typically files and resources. It functions as a centralized warehouse to house a company’s knowledge. Repositories are used when data is complex, unstructured and non-relational. Researchers prefer a repository when their datasets are large and dynamic, making it easier for collaboration.

UX Research Repository Examples

Many universities, government-owned entities and other institutions make their research repositories available to the public. 

There’s far too many to list here, but we’ll share a few examples:

Here’s a list of open repositories published by Springer Nature Group .  And here’s a research repository market map by our friends at Wonder .

Why You Need a UX Research Repository

Research seeks to identify customer needs, behaviors and goals to create better products and experiences for users. Repositories allow for easy mining and learning from insights, and bring efficiency to the research process. Let’s flip this around and see what industry professionals say happens when you don’t have a research repository in place:

Organizational Silos

Whether they know it or not, every department conducts different types of research, amassing various forms of data in the process. Calls, surveys, social media posts and informal conversations (to name a few) all reveal customer perspectives. Usually, knowledge within departments remains just that – within departments. Seldom communicated across the company, information becomes siloed and insights are lost before they see the light of day. Lou Rosenfeld, founder of Rosenfeld Media, cautions that organizational silos lead to an incomplete and unbalanced understanding of customers and inhibit new learnings. He uses the fable of the elephant and the blind men to illustrate the importance of consolidating different perspectives to see the bigger picture.

Knowledge and Insight Burial

Ever download a useful file and forget where you saved it on your computer? Months go by and you can’t remember the file name or path — you spend hours trying to search by keyword, to no avail. The file has fallen into the dreaded black hole — just a microcosm of what happens with research files too.

The more data you create that doesn’t end up in a repository, the more data you ultimately lose. A centralized and organized space makes it easy to unearth and extract insights, avoiding the infernal black hole.

Effort Duplication

Silos and lost insights lead to wasted time and effort. New researchers inevitably ask questions that have already been answered or looked into. Without means to access studies and the conclusions drawn from them, efforts are repeated and the perceived value of research suffers as a result. To keep track of various research initiatives, Gina Rahn, Director of User Experience & Design at LINQ leverages a research roadmap , keeping everyone on the same page. Research roadmaps provide project details and how they tie back to overarching business goals. A quick glance at the roadmap enables you to take stock of studies previously conducted, and ones that need to be undertaken. Repositories coupled with research roadmaps promote organization-wide awareness of research initiatives and insights.

Under-informed Decision-making

According to Pawana Burlakoti, Head of Product at S&P Global, not consulting a research repository at the outset has dire consequences down the line. She’s adamant that you need validation at the beginning and during the course of your work. Pawana champions discovery research at S&P Global, which provides justification on whether to invest time and resources into something or not. Housing this information in a repository helps bring transparency around decision making and allocation of resources.

Regardless of the size of your company and stage of its life cycle, a research repository can help you avoid these unwanted scenarios. A real no-brainer. 

How to Organize a Research Repository

We’ve established that a repository is table stakes for anyone who collects customer data. So what types of data goes into a research repository?

Two kinds of people will access the repository for the above data — producers (researchers) and consumers (stakeholders). It’s important to consider the needs and navigation of all parties while organizing your repository. There isn’t a one-size-fits-all approach, but the guidelines below will show you how to set up your research repository for success.

Roles & Regulations

First provide ownership — who will own and manage the repository? They act as gatekeepers for the rest of the organization. Define roles by establishing who will use and access the repository on a regular basis — decision-makers, product managers, designers, developers, power users such as researchers and view-only users. Establish ground rules on correct usage of the repository and document them. Adherence is key to maintaining an organized repository.

Information Architecture

Make sure you’ve conducted some research before you start thinking about organizing your data. It gives you an idea of how to structure your repository with appropriate taxonomy and metadata for your files. Taxonomy is nothing but a naming convention for your files and data. Stick to a consistent taxonomy and create a guide for new users to follow.

Tag your data! We can’t stress that enough. Tagging converts unstructured data into smaller, semi-structured nuggets. This makes it more manageable, easier for you to digest and analyze the most granular items. When tagging, the simpler the better. Tagging is an ongoing process, one you’ll continue to refine as you go along. Don’t create new tags without normalizing the existing set. Click here to learn more about tagging your data using Marvin.

Maintenance Mode

Research repositories are living artifacts. Routinely update and maintain your repository to keep it organized. Devote time periodically for upkeep so that your repository remains easily accessible and searchable for users across your organization.

Head over here for more tips on how to structure and supercharge your research repository.

Relevant Elements in a Research Repository

Two kinds of elements live in a research repository — input and output. 

Input consists of the information for planning and conducting research. Output is the by-product of research, in raw or polished form (reports etc). Information collected in user research can be disparate and difficult to organize. 

Marvin to the rescue! Below, we created categories for elements that make up a research repository.

Infrastructure

Infrastructure consists of the background information needed to understand and use the repository. This helps guide researchers through the right processes when undertaking a research project. Infrastructure tends to be higher level documentation, not paying heed to everyday tasks and timelines. 

Research infrastructure includes:

• Mission and vision. Outlines the goals of the research team. Any viewer will immediately understand the research team’s capabilities. This includes what the team does, why they do it and what can be requested of them.
• Methodology. Helps new researchers understand and how to carry out their work. Listing best practices and techniques ensures that they conduct research effectively. They understand how data is stored and collected, and why a particular method is used.
• Templates and Tools. Represents any artifacts that help in conducting and analyzing research data. Guides help users understand how to use the research repository software. These include surveys, interview scripts or discussion guides, protocols, reports and analysis, and participant consent forms for studies.

Research Planning

Winning teams use a Research Roadmap .

A research roadmap communicates a path to solving customer problems uncovered during research, and it should closely align with the product roadmap. It informs viewers how research goals tie into an organization’s strategic goals. Roadmaps outline an action plan to accomplish a company’s goals. 

A detailed research roadmap must include:

• Projects. Communicates which projects are ongoing and in the pipeline. Allows viewers to prioritize based on importance. Project descriptions outline overall goals breaking these down into individual, everyday tasks.
• Schedules. Identifies what’s being examined and which research method is being used. Includes the date, time, location of a study, so that anyone can ask to join, or can view findings once it’s completed.
• Administrative Information. Contains details about company policies. It includes the funding details of research projects. Staffing and contributors for each project are established here. Includes the technology used and its interoperability with the company’s existing software stack. This maximizes the opportunity for exchange and reuse of information.
• Requests. Tracks research requests, which is especially important for larger organizations. This list allows people to see what’s already asked for, so they can make an informed decision to either leverage existing data or conduct a fresh research project.

Data & Insights

Over to the output of research. These nuggets of data inform user personas, user journey maps and research in general:

• Reports. Summarize methodology, findings and recommendations from a concluded research study. 
• Insights. The detailed findings from a research study. Despite findings being included in reports, standalone insights help other researchers discover and use relevant nuggets in future projects. 
• Transcriptions & Recordings. The bulk of a UX researcher’s time is spent in interviews or analyzing interviews. Making the interviews available and searchable helps others access these files in the future.
• Notes & Artifacts. Any notes or other items collected during the research process. They help enable an understanding of what researchers uncovered in the past. Newbies can incorporate this information when planning a new project.

Essential Research Repository Features

What functionality do you need in a research repository? How do you discern between the essentials, and ‘nice to haves’? Each company prioritizes certain requirements, however some functions are non-negotiable. To make life easier, we’ve come up with a handy acronym to recall the laundry list of features to look out for in a research repository tool:

‘SAAS ASPIRE’

Remember it this way: You have certain aspirations for your research repository software (as a service).

These are listed in no particular order of importance ( other than giving you a catchy acronym ).

If you’ve ever been asked, “What do we know about X?” or “Have we got any data on X?”, this feature is for you. The ability to search and filter by keyword, or slice and dice your data enables quick discovery, consolidates insights and saves time. This increases the importance of the tagging exercise (above). A visually appealing and engaging search feature helps too. 😉

Insights must be easily retrievable from the research repository. If I want to find out more about what customers said about Product A, I should be able to quickly search for “Product A” and “customer reviews”, for instance. Many platforms require people to have a separate login to access and simply view data or recordings. Tasked with creating a new account merely to view files, we’d rather not. A call for some simplicity, please.

Silly as this may sound, a repository that only houses customer insights is a bit dated. Ideally, you want a tool that enables you to import different forms of data for deeper analysis. Marvin and numerous other tools have the capacity to house qualitative and quantitative data. This avoids constantly jumping from one analysis tool to another. All your analysis in one place. 

Perhaps the most important feature — we introduced organizational silos and the data vacuum above. Disseminating insights elevates the user voice within an organization, bringing everyone on the same page. Sharing text is one thing, but sharing data in its original formats (table, above) is compelling. Moreover, at companies where research is a new practice, sharing communicates its value to non-researchers. 

Artificial Intelligence (AI)

Bill Gates recently said that the advent of AI is as revolutionary as the graphical user interface, used to power mobile phones and computers. As we grapple with something that might eventually replace us, it becomes even more crucial to be able to leverage this key technology moving forward. AI has a host of applications within a UX research repository – it can help transcribe interview recordings, summarize lengthy transcripts and so much more. Your choice of repository wouldn’t be future proof and forward thinking if it didn’t have at least some AI capabilities. 

Privacy is a fundamental human right. Corporations that have tracked and sold our data (a la Cambridge Analytica ) are now being forced to double down, due to emerging data and privacy legislation. Information housed in a repository is highly sensitive and must be anonymized, protecting users. Look out for adherence to one (or more) set of standards from this list . Better safe than sorry.

Path Traceability

Connect insights to raw data. For the sake of our acronym, we cheated by adding ‘path’, but it only drives our point home further. Refer to the atomic research diagram above. If presented with purely insights, without how they were arrived at or deduced, decision makers are certain to question their validity and reliability. Linking raw data (any format from table, above) to an insight illustrates how we arrived at a certain conclusion and enables viewers to make their own deductions, given the information presented.

Integrations

Standing alone, repositories are of little use. Companies use a host of applications and platforms such as a CRM, project management and an ERP system. You might use Slack for messaging, Notion for documentation and Qualtrics for quantitative analysis. A key feature of a repository is the ability to talk to apps that you already use regularly. Marvin’s seamless integration with Zoom turns your research repository into a UX powerhouse. Explore all of Marvin’s integrations here .

Real-time Efficiency

Video is the preferred format of choice for qualitative data collection. It’s more interactive and can reveal non-verbal cues such as body language, genuineness (although some might have a solid poker face!), tone and expressions. Unlike most tools, Marvin transcribes interviews or calls as they unfold, freeing up your time to stay engaged and concentrate on these non-verbal cues. Use the time stamped LiveNotes feature to collaborate with your team and take important notes as you conduct interviews. This makes revisiting insights and tagging a breeze.

Ease-of-Use

Last, but certainly not least. A repository tool must have an intuitive design and user-friendly interface. Learning the ropes should be quick and easy. We pointed out earlier that a repository is not exclusively for researchers — product managers carry out their own research and key decision makers will likely rely on the tool for vital information. It must be straightforward for different personas to navigate through the various functions. We’ve spoken to umpteen users who were turned off other tools due to the complexity in navigation. Self-serve is the name of the game.

Ultimately, it’s up to you and internal stakeholders to gauge requirements and prioritize mandatory features for your repository. Every listed feature is important, with anything over and above it a ‘nice to have’. Admittedly, we didn’t leave much wiggle room.

How to Choose a Research Repository

Given the rather exhaustive feature checklist above, what are your choices when looking for a research repository? The way we look at it, you have two approaches to take when deciding on a repository tool:

• Homegrown – repurpose generic and free software. Why pay for something that you can get for free?
• Purpose-built – spring for a dedicated research repository tool. You get what you pay for.

Two very different schools of thought — let’s explore the first option in greater detail. 

Homegrown Approach to Building a UX Repository

The following software can be fashioned into a makeshift UX research repository tool.

The Cons of Using a Generic Research Repository

You’re spoiled for choice with applications or tools when taking the homegrown approach. And it will save you money as you build a custom solution that’s tailored to your company’s needs. But reader beware, you may find some major drawbacks when repurposing a generic tool into your UX research repository:

• Feature Compromise : Does your repurposed software tick all the boxes from our SAAS ASPIRE list? Highly unlikely — you’re going to have to make certain concessions somewhere.
• Scalability: Bear in mind, ‘free’ tools wouldn’t exist if they didn’t have paid versions as well. The moment you scale or add complexity, the ‘free’ element of these applications disappears and you have to spend money to keep up with continually growing scale or features. That’s how they get you.
• Inefficiency: Time is money. The price you pay with heavy customization is time. It’s the fundamental economic concept of opportunity cost. What’s the cost of the time spent creating the research repository infrastructure vs. the time saved if you opt for a dedicated tool?

The homegrown makeshift route certainly gets the job done, but you must continually evaluate whether it’s to your satisfaction. With database tools like Notion, trying to make qualitative data fit into a quantitative format is a classic case of “square peg, round hole.” 

The issue with a generic tool is that customization time and effort is high, and you don’t always end up with features that you really need. Don’t fall into the mousetrap of customizing an application consuming so much of your time, that it eventually reduces your overall productivity. We’re full of metaphors today — using freeware is like using anything but a hammer to get a nail in the wall. It might work, but not nearly as effectively as the real thing.

List of 8 UX Research Repository Tools

Organizations of all sizes turn to specialized research repository tools rather than building a resource from scratch. So how do you choose from the wide array of research repository tools that were listed above?

We’ve ( obviously ) got you covered. With research repositories aplenty, here’s a shortlist of the eight most popular choices:

We saved the best for first. 

Marvin is the only AI-powered research repository that automates your data analysis. Marvin houses ALL your research (both qualitative and quantitative) in one centralized location. It integrates seamlessly with applications that designers know and loved such as Figma, Miro, Confluence and Qualtrics. 

Speaking of integrations, supercharge your research with Marvin’s videoconferencing workflow, which transcribes calls from Zoom, Microsoft Teams and Google Meet so you can focus on the person in front of you. 

Marvin’s AI creates time-stamped notes from transcripts. Gloss over the highlights and delve deeper whenever you want. No more sifting through hours of interview footage.

The first-of-its kind survey engine lets you automatically analyze thousands of responses in minutes. This type of analysis used to take weeks of manual work.

Create stunning visualizations and string together interview clips to create powerful artifacts. Once stored, you can easily share these insights across the organization, helping you truly democratize research and make user-centric decisions.

Marvin’s Ask AI is a ChatGPT-esque search engine that enables you to search across all your customer knowledge. Make connections across projects to create a well-defined understanding of your users. 

User information is sacred. Scrub out any faces and remove any personally identifiable information from videos and transcripts. Marvin is HIPAA, SOC2 and GDPR compliant.  With Marvin, your user data is always protected. 

The crème de la crème of research repositories. Save time, and dive deeper into your analysis with Marvin. 

2. Aurelius

This research repository platform allows you to import various file formats such as audio, video, notes and spreadsheets. Leverage its Zapier integration to automate tasks. Global tagging allows you to analyze data across the repository and unearth insights. 

When you add recommendations to key insights, Aurelius automatically builds an editable report for you. Share this report with any Aurelius user. 

An AI-powered product management platform that also serves as a repository (They call it the ‘Idea Box’). Chisel’s AI features allow you to synthesize feedback in bulk for more efficient analysis. 

Built-in features such as surveys and roadmaps help you get to the root of user problems. Target the right users by using their panel management software. Use different demographic filters to recruit the right participants. 

Condens helps you structure your user data before storing it for analysis. Condens has extensive features that help you recognize patterns, create artifacts and tag files efficiently. 

Collaborate with peers on projects simultaneously and view modifications in real-time. Share insights with various stakeholders without sending across heavy files. 

5. Dovetail

Dovetail is a customer insights hub that enables the collection, storage and analysis of research data. Capture user feedback from a variety of sources, then tag or label it to help catalog historical data. 

Dovetail uses pattern recognition to identify problems before they get out of hand. It is designed to fit into a researcher or designer’s process after they have conducted a round of customer interviews or received feedback from users.

EnjoyHQ , now a part of UserTesting, is a centralized location for customer insights. It has unlimited data storage and transcription (when you opt in for a paid pan). It enables insight sharing across a company.

UserTesting and UserZoom share data with EnjoyHQ effortlessly. Other helpful features include feedback management, keyword tracking and qualitative comparative analysis.

An all-in-one platform that includes user testing, panel and recruitment and of course, a repository. Maze has different product offerings for various industries, such as financial services, technology and enterprises. 

Maze is a centralized research platform that helps you manage projects and workflows. Use templates from their gallery to build reports and deliverables that you can share with stakeholders. Automate report creation to visualize and identify patterns in data. 

A research repository tool for small businesses. UserBit uses AI automations to generate insights from tagged data. AI can also scan and tag your data automatically. 

Create customized reports and post research findings on the Discovery portal so other stakeholders can view your work. 

Benefits of a Modern Research Repository Tool

Above, we discussed the first of two different paths you can take when choosing your software. If you’re still reading, you likely chose not to explore the makeshift homegrown options. You clearly understand the value of supporting your research team with the best dedicated research repository tool.

Making research for everyone at your organization easier should be a priority. It will save you valuable time, resources and effort.

Speaking of, we’ll save you plenty of time, resources and effort right now with a short but comprehensive round-up:

• G2’s Top User Research Repositories ( based on real user reviews)
• A Thorough Comparison of Every User Research Repository Tool (from 2023)

3 Research Repository Mistakes to Avoid

Why do research repositories fail? Several factors contribute to repository adoption.

Here are three of the biggest pitfalls to consider when implementing your research repository: 

1. Buy-in & Onboarding Failure

Change is hard. People aren’t usually pumped to work with new tools. They need convincing. To get buy-in, explain to your stakeholders why a repository is needed and how it will benefit the whole business. Describe how centralized knowledge enhances collaboration between teams, reduces data silos and eradicates repetitive research. Once you choose a tool, getting people to use it requires another gargantuan effort. Spend time training people how to correctly use and contribute to the repository. (Far better than letting them run wild and having to clean up after them.

2. Wrong Tool Selection

Don’t bring a knife to a gunfight… or a supercomputer to a gunfight. The wrong tool fails to showcase the true value of research. It’s essential to keep your organization’s needs in mind as you choose the right one. Choose a tool that’s user-friendly and not complex, so people won’t get turned off using it. Future-proof your choice by addressing current needs and considering possible future ones. Leverage the fact that most tools have a free trial period. Try before you buy.

3. Ownership

If you’re expecting a UX research repository to solve all your problems, you’re in trouble. Role ambiguity leads to a lack of ownership on UX recommendations. Post-implementation, someone must take accountability since it requires ongoing efforts to maintain and improve the repository’s functionality. Roles must be clearly defined and guidelines followed — someone must constantly oversee these efforts.

Research Repositories: Getting Started

Not sure where to begin? Our panel of experts has their say on how to begin implementing and utilizing your research repository.

Unlock Internal Knowledge

Before jumping into using your repository, the first step is leveraging your existing knowledge base. Gina Rahn has seen numerous acquisitions take place during her time at LINQ, a K-12 educational software company. Whether new peers call it research or something else, they’re likely sitting on valuable information and knowledge. Gina tackled this problem head on — by treating coworkers as users, she was able to unearth utilizable insights from her internal research. 

Read more about how Gina employs design thinking using Marvin.

In a similar vein, Lou Rosenfeld recommends conducting an ethnographic study of your organization. Not only does it get everyone up to speed with research efforts, it enables a company-wide understanding of what research brings to the table. All these valuable internal insights go into your research repository.

Broadcast Your Findings

“You have to be your own marketer — you’re doing the work, sharing it, broadcasting it up and down.” These words of wisdom are from Claire Rowell, Lattice’s first researcher. 

Researchers like Claire often begin as one-person teams, so they must quickly perfect the art of communication. A research repository tool that facilitates easy sharing is a god-send for solitary researchers like Claire. The benefit of sharing insights across the organization is twofold — it elevates the voice of the user and simultaneously communicates the value of research. Claire shared more great advice for sole researchers beginning their journey.

Gina circulates a quarterly newsletter that informs everyone in the company of various research initiatives and developments. Colleagues tune in to video and sound bites from their users, fostering excitement around the product. This keeps the most important stakeholder at the forefront of everyone’s thoughts.

Orchestrate a Culture Shift

Easy enough, right? Sarcasm aside, to get buy-in from other teams and stakeholders it helps to give them access to the repository. Claire alludes to the fact that Marvin’s self-serve gets everyone energized about using an interesting repository tool. 

Learn more about how Claire and her colleague Jared use Marvin to create a research-driven culture at Lattice.

At S&P Global, Pawana is clear that the research culture dynamic must be conducive to risk taking – ‘fail fast, fail early’. Inevitably, researchers will explore some questions that have a dead end, prompting no further action. The repository acts as a question bank for these studies from yesteryear, ensuring that no efforts are duplicated down the line.

Twilio research leaders involve as many peers as possible throughout the research process. The idea is to empower them to conduct some form of their own research, ensuring everyone is laser focused on solving the customer problem.

Putting It All into Perspective

Research repositories are vital to a company leveraging its internal and acquired knowledge over time. Unlike its quantitative counterpart, processing qualitative data is convoluted and cumbersome. Qualitative data tends to be text-heavy — there aren’t many visualizations such as graphs. Sifting through volumes of text must be effortless and painless.

In looking for a research repository tool, you must consider the needs of users outside of the research team when making your decision. It must be easy to use for product teams, designers, developers, engineers and decision makers alike within your organization. Users must be able to search and navigate through the repository with ease.

To optimize information architecture, you need to treat your repository implementation as a UX project in itself, a constantly evolving proposition that you continue to refine. In our opinion, using a makeshift tool is the equivalent of bringing a knife to a gunfight (we told you — we’ve got the metaphors down) . You want a UX research repository that checks all the feature boxes (and there are plenty!)… one that’s built for scale and easy to use.

Frequently Asked Questions (FAQs)

Here are some frequently asked questions about research repository:

What is a Scientific Repository?

A scientific repository is a collection of data that is collected and stored with the intention of using the materials for future research. Scientific repositories house research and supporting documentation at various levels of granularity. 

Researchers interact with a scientific repository in three ways:

• Primary collection or aggregation of information
• Storage, maintenance and distribution of repository information
• Secondary use or analysis of information

Scientific repositories allow research to be preserved over time so others can refer to and use existing work or findings.

What is the Role of Research Repositories in Research?

Research repositories act as a single source of truth for a company. This centralized knowledge bank houses all the data collected through research efforts.

Research repositories support the research function in three ways:

• Storage & Organization. Researchers can upload files in various formats from a variety of sources as they collect more data about their users. They must organize data before beginning their analysis.
• Analysis. Once stored, researchers can query the collected user data. Searchability is a function of a repository that enables them to interrogate the entire data library. They group items into themes and create tags to derive insights. Traceability (or path traceability) enables them to trace these insights back to raw data.
• Sharing. A repository makes data shareable across teams in an organization. Various stakeholders can benefit from insights derived from research. It enables others to validate research findings. This increases the transparency and trust in research work. Making data freely available enables others to build on a company’s foundational knowledge.

What is the Value of a Research Repository?

Research repositories help store and organize information obtained from UX research for analysis. A research repository provides value to an organization in several ways:

• Allows everyone in an org to find and track information easily. 
• Surfaces insights from research that can drive key decisions about the business’s growth and direction moving forward. 
• Makes research widely available and consumable across an organization. Stakeholders can access and analyze this data at any time.
• Offers a single source of truth. Avoids information becoming siloed within departments and people duplicating research efforts. 
• Identifies potential areas of future research and lets others expand on existing research.

Overall, a research repository streamlines the work of the research team. Insights from a repository help inform decision-making. A centralized source of knowledge helps eradicate departmental silos and research repetition. 

Well-defined research repositories increase collaboration across an organization and create awareness of the research function’s value. Set up a free demo and see how to centralize your research with Marvin today.

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Research repository: solving your organization’s research problems

User research is siloed within departments

The same research is repeated over and over

Research reports go unread by stakeholders

Cumulatively scaling datasets don't lead to cumulatively scaling knowledge

Throughout this blog post, we’ll dive into these problems and discuss how a research repository can help and the principles that make for a great research repository solution .

.css-1nrevy2{position:relative;display:inline-block;} User research is siloed within departments

Along with the user research team, almost all teams within an organization conduct some form of customer research, even if they don’t explicitly call it that. Product managers interview users, designers test prototypes, salespeople talk to leads, support tracks topics, marketing facilitates focus groups, HR run feedback surveys, and customer success run  Net Promoter Score  surveys.

These functions and teams all do user research differently, analyzing their data with different tools, and publish mountains of data, reports, and updates across a variety of formats and products. Stakeholders and consumers struggle to find what’s relevant to them—the signal in the noise; the needle in the haystack.

Often, when a new researcher joins a product team, they go off, do some research, and come back with the same insights and findings that are already known. It takes months (years, even!) of experience to build the necessary context and to get to tangibly meaningful insights that have the power to effect change and be force multipliers in an organization.

Tenured employees already know this and grow skeptical of a research team that tells them things they already know. Over time, thanks to the same research being repeated, and the same conclusions echoed, the effectiveness and credibility of the research discipline within your organization is slowly eroded.

Sherif Mansour  is a distinguished product manager at  Atlassian  with over 10 years of experience working on products like  Jira  and  Confluence . He reflects that:

One of the key challenges we’ve seen is how to help new team members build a shared understanding of the key insights that existing team members have already realized. The cost of re-learning is expensive, especially in growing organizations.

Because research is stored in a variety of formats, tools, and silos throughout the organization, there’s no way for anyone to quickly get up to speed on what is already known. Searching through years of unorganized archives of reports, documents, and presentations to build context is an impossible task.

Lastly, when that researcher leaves the company, they take a lot of undocumented knowledge of your customers with them—hopefully not to a competitor.

Reports go unread by stakeholders

Written reports and presentations are the ‘go-to’ format for sharing user research insights, but unfortunately, there’s no standard for how they’re produced or what content they should contain, and every researcher structures them differently.

These kinds of reports are usually inaccessible to everyone in the organization: they’re shared spontaneously over email and chat or lost in Google Drive or Dropbox. There isn’t a clear place for people to go to learn about your customers. You’re lucky if these reports are read, and you’re even luckier if any action is actually taken as a consequence of them.

Back in 2005,  Jakob Nielsen  from  Nielsen Norman Group  highlighted the pain of finding usability testing reports in his article  Archiving Usability Reports :

When people have to search for usability reports, they’ll often fail—or they won’t even know what to look for because there’s no single place that lists all available usability results. Even worse, if past project owners are the only source of results, you risk losing valuable institutional memory when these individuals leave the company or get reassigned.

Another detriment of traditional research reports is that they’re usually disconnected from the raw data and evidence that led to the formulation of the report in the first place. It’s difficult for stakeholders to understand how a researcher came to a particular insight, because there’s often no way to dive into the details of a specific usability test, interview, or survey response. This lack of traceability leaves stakeholders spending time poking holes in the research or methodology, instead of taking action on them.

Standard research reports also often lack any features that allow you to track engagement. PDFs don’t have read-receipts, and there are no easy ways to measure the impact research is having in your organization.

Worst of all, of the researchers we spoke to, none of them actually enjoy creating these reports. They find themselves spending more time designing and formatting internal reports for stakeholders, rather than actually talking to customers and users. The best workaround we’ve seen is reusable templates for research reports.

Research data and customer feedback comes in many shapes and sizes, including surveys, quotes, interview notes, video recordings, industry trend reports, social media posts, app reviews, and more. Researchers rely on all this information to synthesize research findings, usually in the form of a research report. Typically, this research lives in a file storage system like Google Drive or Dropbox or a wiki like Confluence or Notion.

Organizing and curating this ever-growing collection of data is relatively simple for a small organization. However as companies grow, the systems used to store customer research don’t scale and end up requiring significant administration to maintain. Someone has to ensure all the files are searchable, appropriately restricted, and tidy.

Inevitably, the repository becomes unwieldy and difficult to use. This creates the opposite of the intended effect—people stop using stored research and the total sum of an organization’s customer research leads to less customer knowledge.

Why a research repository?

Most organizations with a user research function acutely feel the pain of the problems above. If you don’t yet, it’s likely you will in the future as you scale design and research. Much of the pain can be eased through a thoughtful approach for how research data and insights are captured, analyzed, standardized, archived, and shared.

Imagine a ‘Wikipedia’ for your organization’s customer knowledge: a centralized, searchable database of research and insights that the entire company leverages to make better decisions. A single source of truth that empowers stakeholders to engage with research and fosters a culture of research across your organization. Designers, product managers, and developers effortlessly pull up insights that answer common questions and, in one click, can explore the evidence—and understand the context—that led to those insights.

A  research repository  is just that—one central place, or source of truth, where people in your organization can go to find the latest insights from your research team.

Learn how they did it

The characteristics of a successful research repository

We’ve talked to user researchers, designers, and product managers across a variety of organizations, and we’ve settled on five key characteristics that lead to the successful adoption of a research repository. We believe all successful repositories are  retrievable ,  approachable ,  traceable ,  accessible , and  secure .

Retrievable

Searching and finding research insights should be effortless. Members of the product team should be able to easily find answers to their questions, self-serve, without needing to write complex queries or spreadsheet formulas. Insights should be easily filtered and segmented by attributes important to your organization, like segment, country, market, demographic, or even  NPS . Researchers need to be able to conduct secondary research by easily retrieving prior research and insights and feed that into current research projects.

Approachable

A research repository should be approachable not only for user researchers, but also for other members of the product team like designers, product managers, developers, and stakeholders like founders or executives.

Creating insights needs to be simple and delightful—your team needs to be bought in and want to use your repository, and they won’t if the experience is complicated, clunky, or slow. Stakeholders want to consume research insights in a lightweight, quick, and beautiful way, without needing to read multi-page reports or presentations. Anyone should be able to easily “remix” previous research and leverage an organization’s cumulative customer knowledge to make informed product decisions.

Successful research repositories aren’t just a collection of disconnected insights or recommendations. They also need to provide a path back to the raw research data which led to the insights in the first place. Research findings should be connected to the source material that the researcher interpreted to inform a particular insight. References to raw research data or ‘evidence’ enable stakeholders to see where an insight came from and understand the original context of the research method.

Someone should be able to look back on a user research insight from years ago, review the evidence, and determine if it’s still relevant or has been interpreted correctly based on what is now known. Researchers should be able to look back to see if new insights could be developed from research data that was collected previously.

A repository needs to empower your organization to leverage customer research data and insights, and for this to happen your entire team needs access. New people who join your organization should be given access on day one.

You shouldn’t have to worry about managing access permissions for folders in Drive or Dropbox – the ideal research repository should be ‘open by default’. Team members should deep-link to your living repository over email and chat as the source of truth, rather than send around presentations or reports as static attachments.

As a research repository will act as the single source of truth for your organization’s customer knowledge, it’s likely it will include personal information and potentially sensitive data from a range of industries.

For your research repository to be approved by your security, legal, and information technology teams, you’ll need to consider where customer data will be stored, what the processes are for retention and deletion, if data is encrypted or anonymized, and what security practices and policies are in place.

If your organization has customers in the European Union, you’ll need to ensure that your research repository is compliant with the  General Data Protection Regulation (GDPR) .

Starting a research repository

So you’re convinced and want to start building a research repository in your organization. How do you get started? Aside from working out the  governance and operations  that will support how people use and interact with your repository internally, the most critical decision is selecting a tool or platform for your research repository.

Flexible and generic tools

Most organizations start their research repository journey by assembling existing tools that are already used internally, typically because they’re accessible and inexpensive to set up. Teams cobble together faux research repositories with wikis like  Confluence  or  Sharepoint , spreadsheets and databases like  Excel  or  Airtable , issue-tracking tools like  Jira  and  Trello , and storage tools like  Google Drive  or  Dropbox .

As an example of using a flexible tool as a research repository solution, the folks at  GitLab  have used their own product as a repository for their UX research insights.  Sarah Jones , UX Research Manager at GitLab  describes their repository :

Instead of reports and slide decks, we use  issues to document key findings  from research studies. Each insight is supported with evidence, typically in the form of a video clip or statistical data. We use GitLab’s related issues functionality to connect insights which were revealed during the same research study.

As everyone at GitLab has access and knows how to use the product, this approach has been successful for them. However, most research organizations don’t have the luxury of working on a product that can be manipulated in this way, and flexible solutions almost always inevitably fail in the long term for a variety of reasons:

Searching and retrieving insights from these tools is cumbersome – search functionality is complex, limited, and unintuitive. In the case of file storage tools like Dropbox and Google Drive, searching within files is usually not possible.

Insights are static and disconnected from the original research data. Recordings, transcripts, notes, and participant information has to be stored across many different tools and the evidence that supports an isolated insight is lost.

They’re not fit for purpose. Flexible, horizontal tools aren’t designed for research and use unopinionated terminology like cells, sheets, rows, and records instead of concepts that are research-friendly like insights.

We often see people come to  Dovetail  as a purpose-built research repository solution after trying to build a repository using tools that aren’t built for that specific purpose.

Building a custom repository in-house

Unsatisfied with flexible, generic tools that aren’t fit for purpose, organizations with well-resourced research teams often look to design and build their own research repository in-house. Large enterprises like  Microsoft ,  WeWork , and  Nasdaq  have all shared details of their own purpose-built research repository solution.

Microsoft’s research team have built their own repository called the  Human Insights System (HITS) . As  Matt Duignan , Principal User Research Manager at Microsoft explains, to help scale HITS across the entire Microsoft organization without losing the integrity of their data, they designed for letting people find insights while retraining context:

If a user were to take an insight out of context, say to make an argument in favor of a new product feature, HITS makes it possible for everyone involved to look at the supporting evidence and come to a fuller understanding of what the context implies.

The design of HITS enables research to be brought into conversations and make product decisions informed by customer data and evidence.

Q&A with Matt Duignan from Microsoft’s Human Insight System

Similarly, WeWork built their own research repository solution internally, and  Tomer Sharon , then the Head of User Experience at WeWork, announced the Polaris research repository in his article  Democratising UX .

Following the article, an ‘open-source’ version of Polaris was  released as a template on Airtable . Unfortunately, the researchers we’ve spoken to who have tried to create a research repository with this template have not had success, for the same reasons why tools like Confluence, Airtable, and Dropbox don’t make good research repositories.

Creating WeWork’s Polaris research repository in Dovetail

With enough resources, building your own research repository can work since it can be tailored to specific needs and processes. However, given the complexity in building a bespoke research repository solution and the ongoing maintenance commitment, even large organizations rarely opt to invest in an internal solution.

Why we built Dovetail

We built Dovetail to be the platform for your organization’s user research, considering principles of  retrievability ,  approachability ,  traceability ,  accessibility, and  security  from the ground up. With our platform, researchers, analysts, designers, and product managers can store user research data in one place, analyze qualitative data to discover patterns and insights, and share research findings with the rest of their organization.

Our  team  has decades of combined experience working in product teams at  Atlassian ,  Canva ,  Intercom , and  Microsoft . We’ve all seen first-hand the challenges that come with managing customer knowledge and insights, and we’re passionate about helping teams understand their customers, make better decisions, and do great work.

Search, segment, and retrieve data

We’ve built an appreciation of how important it is to enable stakeholders to self-serve customer data and research insights. Researchers are usually stretched thin relative to their counterparts in engineering, product management, and design, and insights need to be scaled across the entire organization.

We’ve built powerful, intuitive filter and segmentation controls that enable people to easily  retrieve  research data and customer insights. Research data can also be enriched with contextual information: demographic data like name, age, location; contact details like email address and phone number; properties like persona, company, or license; and even someone’s  Net Promoter Score .

Approachable and enjoyable

A focus for us is making sure Dovetail is  approachable  and enjoyable to use. We know a lot of research software isn’t particularly intuitive, especially academic qualitative data analysis suites like  MAXQDA ,  NVivo , and  Dedoose . While very powerful, these QDA tools are complex and beyond the reach of most commercial researchers and stakeholders.

We try to make it easy for people to analyze unstructured data, create insights and embed references to raw data, and making insight reports look good by default.

Embed evidence to your raw data

In his article on  Microsoft’s Human Insights Library , Matt Duignan talks about “real-time curation” as a way to encourage participation in the research library / repository, to avoid the problem of reports being deferred to the end of the process:

Someone needs to synthesize insights in a way that optimizes for durability and reuse across time. But for researchers under pressure, it can be tempting to defer this work.

Rather than running out of time to turn insights into durable, standardized reports, an insights repository should instead organically evolve over time, with  traceability  back to the original source material and context.

Because Dovetail has features to help with analyzing common research methods like interviews, usability testing, and surveys, it allows you to maintain traceability through embedded references to notes, quotes, tags, photos, videos, recordings, and more.

Access for your entire organization

We don’t want  our pricing  to inhibit the effectiveness of research teams within organizations. To make Dovetail  accessible  to everyone, we’ve been intentional about offering unlimited, free viewer accounts for people in the organization to view research data, read insights, and comment. This means that our customers only pay for researchers that actively contribute data, analysis, and insights.

This pricing model has accelerated the consumption of research in our customer’s organizations. Gemma Sherwood,  Intrepid Group ’s UX Manager has  shared with us  that their UX team has now turned their attention to other departments like Marketing and Insights to get them involved in their research repository:

Our broader goal is for the Insights and Marketing departments to utilize Dovetail as a searchable research library to improve their decisions and ground them in customer experience.

We’ve also invested in features that  allow anyone with an email address  at your organization to join your Dovetail workspace without needing to be invited and the ability to  share your projects and insights  with others who don’t yet have an account.

Secure, and private by design

We make  security  and data privacy foundational principles of everything we do, and we recognize the importance of adhering to regulations to advance information security and data privacy, including the  GDPR .

We’ve chosen proven third party cloud providers, take regular data backups and test recovery, run penetration testing, encrypt all data at rest and in transit, conduct static code analysis and third-party vulnerability scanning, sanitize our logs, secure individual customers at the database level, and  many other cloud security techniques .

The future of research repositories

We think more and more organizations that talk to customers and leverage customer data to improve their products and services are increasingly frustrated with the pains of storing, retrieving, and sharing insights from user research. We believe that a thoughtfully considered user research repository is critical to mitigating this pain and unlocking the potential of customer research in organizations worldwide.

In Dovetail, we think we’ve built a solid foundation on our principles of  retrievability , approachability , traceability , accessibility , and security . Our team is motivated to make Dovetail the obvious platform for your user research and insights.

We’re at the beginning of this journey. We’ve got more to learn from our customers, and  many exciting features planned  for the future. If you’re interested trying a research repository in your organization, we’d encourage you to give Dovetail a go and  sign up for a free trial —we’d love to hear your feedback!

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Research Repositories 101

July 5, 2024 2024-07-05

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As a research function scales, managing the growing research-related body of knowledge becomes a challenge. It’s common for research insights to get lost in hard-to-find reports. When this happens, research efforts are sometimes duplicated. Enter research repositories: an antidote to some of these common growing pains.

In This Article:

What is a research repository, what is included in a research repository, tools for research repositories, research-repository types, helpful features for successful adoption, 4 steps for creating a research repository.

A research repository is a central place where user-research artifacts and outputs are stored so that they can be accessed by others in the organization.

Storing user research centrally in a repository provides the following benefits:

• Insight can be quickly found because research outputs are stored in one place (rather than distributed across many platforms or team spaces).
• Teams can track findings and observations over time and across studies, helping to uncover themes that might not be identified from one study alone.
• Research efforts are not duplicated, as teams can learn from or build on research performed by others.

Creating and maintaining a research repository is often the responsibility of a ResearchOps function.

When successfully implemented, a research repository can be a helpful tool in increasing the UX maturity of an organization, because it makes insights about users accessible to many people.

Research repositories often house (or link out to) the following items:

• Research reports capture what happened and what was learned in the research study. A research report usually includes overarching themes, detailed findings, and sometimes recommendations.
• Research insights are the detailed findings acquired from each research study. While insights also appear in reports, saving them as their own entities makes them easier to see and address.
• Study materials, such as research plans and screeners, allow team members to learn how research insights were gathered and easily replicate a study method.
• Recordings, clips, and transcriptions make user data easily accessible. Summarizing and transcribing each video allows teams to search for keywords or specific information.
• Raw notes and artifacts from research sessions might be useful for future analysis and can sometimes be easier to read or process than a full transcript or video recording.

Of course, there could be other items included in your repository. There’s no hard rule on what belongs in a research repository. In some organizations, research repositories also store data coming from sources other than user-research studies — for example,  customer support-emails, notes from customer-advisory groups, or market research. When choosing what to include in a repository, consider the needs of your team and repository users.

Research repositories can be built and hosted in many different tools. Choose a tool that your team (and any colleagues who need to use the repository) can easily access or use.

According to our survey, the most popular tools for research repositories across organizations were:

• Collaboration tools (such as Confluence and Sharepoint) are often already used in many organizations. Since teams and stakeholders can easily access them, they become a natural starting place for many research repositories.
• User-research tools (such as Dovetail and EnjoyHQ) are used by researchers to transcribe and tag video recordings and perform qualitative data analysis . Many of these tools have repository features, making them an obvious repository choice.
• Database tools (such as Notion and Airtable) are often used by teams that already work with databases for product management. Database tools allow for easy cataloging of research projects, deliverables, and insight.

A research repository can take many forms and is often dependent on the tool chosen for the job.

Some repositories act as glorified document libraries, where research reports and study materials are filed away in a specific folder structure. These are common when repositories are housed within collaboration platforms like Sharepoint or Confluence.

Other research repositories are searchable indexes or databases of research findings. These are common when teams pursue atomic research — where knowledge is broken down into “nuggets” or key insights.

Each type of research repository has advantages and disadvantages (as shown in the table below). The main tradeoff is insight discoverability versus effort needed to add to the repository . Folder libraries are easy to contribute to and manage, but insights are less discoverable. On the other hand, insight databases are hard to contribute to and manage but provide easy access to research insights.

Of course, a research repository could include both an insights database and a research-document library. For example, an insights database could link to a folder structure containing all the research documentation from the study where the insight originated.

Getting people to contribute and use a research repository can be challenging. Regardless of the tool and type of repository you pursue, here are five attributes that make research repositories easy to use and adopt.

Easy to Access

The tool you use for your repository should be easy to access, use, and learn by teams and stakeholders. A new tool that is unfamiliar or that is hard to learn could stop people from accessing or contributing to your repository.

Flexible Permissions

The right people should have access to the right data. For most organizations, the research repository should not be publicly accessible since research could involve proprietary designs or cause reputational damage. If the repository stores session recordings or identifiable participant data, the right people in your organization should have access to those assets to ensure that participant data is handled appropriately .

Intuitive Navigation or Tags

People should be able to easily find and discover research. If it is too difficult for stakeholders and teams to locate research, they will give up.

If your repository is a document library, folders should be labeled and organized sensibly. If you are using a database or user-research platform, then create clear and useful global tags, to help contributors label their research and people find specific research-related information.

Repository users should be able to search by specific keywords (such as user groups, products, or features) to quickly find research insight. A strong and reliable search feature is often essential.

Exportable, Shareable, and Integrated

Sharing or exporting insight from the repository is important if research is to be disseminated widely. For example, if the repository tool supports integrations with other platforms, research snippets from the repository can be easily shared to Slack or MS Teams channels.

Step 1: Gain Buy-in

People won’t adopt a research repository if they don’t understand its value. Clearly present your arguments for the repository, including what teams might gain from having one. Gaining buy-in for the initiative and tool is especially important if you need to procure budget to purchase a specialized tool. You may need to show the return on investment (ROI) .

Step 2: Do Your Research

Do research before choosing a tool or structure for your repository. Treat the process of developing a repository like building a new product. Start with some discovery and take a user-centered approach.

Some helpful questions to explore:

• How do teams currently do research? What tools do they use?
• How do teams write up or share research insights currently? What works? What doesn’t?
• What questions do stakeholders ask researchers or teams when requesting research insights?
• What counts as research? What kind of research insights need to be stored and socialized?
• Which tools do researchers or teams have access to? What tools seem familiar and are easy to adopt?

If you are procuring a new tool for your repository, your research might include evaluating available tools to learn about their capabilities, pricing models, and constraints. You can also utilize free trials and demos and perform a trial run or private beta test with a new tool to find out what works.

Step 3: Start Simple and Iterate

When creating a tagging taxonomy for your repository, start with a few broad tags rather than getting too granular and specific. This approach will ensure that there aren’t too many tags to learn or apply. The tagging taxonomy may need to change over time as more research and contributors are added to the repository. It’s easier to make iterations if you have a small set of tags.

Consider testing your proposed tagging taxonomy or navigational structure. Methods like tree testing and card sorting can uncover the best labels, tags, or folder structures.

When thinking about adding content to a new repository, start simple. Instead of migrating all research (and research types) in one go, consider importing the most common or most useful items. Use this as a test run to refine the contribution process and structure for your repository.

Step 4: Onboard and Advocate

The key to successful adoption is a plan for onboarding and change management. Don’t expect the tool to be adopted straight away. Change aversion is common with any new process, design, or tool. Teams and stakeholders may need constant reminders or encouragement to use the repository. You may also need to run training sessions to help people learn how to use it and get value out of it.

Research repositories store and organize UX research, making research insights widely available and easy to consume throughout an organization. When creating a research repository, research available tools, gain feedback from researchers and teams who would use it, and plan to iterate after launch.

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When you sign up to the Atlassian Research Group, we’ll ask a few questions about you. Your answers will help make sure you get invited to research that’s relevant to you.

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Using Jira for Requirements Management

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Platform notice: Server and Data Center only. This article only applies to Atlassian products on the Server and Data Center platforms .

Support for Server* products ended on February 15th 2024 . If you are running a Server product, you can visit the Atlassian Server end of support announcement to review your migration options.

*Except Fisheye and Crucible

While JIRA has been developed primarily as an issue and project tracker out of the box, you can use JIRA for requirements management in conjunction with Confluence.  We will review how Atlassian uses our products for this purpose, as well as provide some relevant resources for further information. 

Atlassian's Usage

Atlassian uses a public instance for our requirements management through feature requests and voting on our  public issue tracker . 

For internal discussion, we use  Confluence  for general requirements gathering and project discussion on a Confluence page. We then utilize Confluence and JIRA's integration to create issues from those requirements pages; allowing us to view both the requirements content in line with the JIRA issues/tasks which correspond to the project . The wiki allows our developers to edit the requirements as needed while making it easy for developers and stakeholders to stay up to speed.

Issue Level Requirements

You're able to create a JIRA issue type specifically for requirements with its own workflow, custom fields and reporting. Sub-tasks offer a quick way to add and manage your requirements, and you can link related requirements together or with feature requests.

Using Confluence

Confluence integrates seamlessly with JIRA, allowing you to track your requirements in JIRA, linked to your corresponding project documentation in Confluence.  To facilitate documenting your requirements, Confluence ships with a Blueprint template for requirements writing:   Product Requirements Blueprint .  

Apps and Integrations with Other Tools

Prefer to customize your Atlassian products? The  Atlassian Marketplace  has dozens of Requirements Management  apps which can easily be tailored to your workflow. A few you might consider checking out:

• R4J – Requirements Management for JIRA
• RMsis - A Requirement Management Extension for JIRA

Requirements Yogi

See all the  Requirements Management apps  in  Atlassian Marketplace .

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The JIRA Repository Dataset: Understanding Social Aspects of Software Development

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Information & Contributors

Bibliometrics & citations.

• Ploscă T Curiac C Curiac D (2024) Investigating Semantic Differences in User-Generated Content by Cross-Domain Sentiment Analysis Means Applied Sciences 10.3390/app14062421 14 :6 (2421) Online publication date: 13-Mar-2024 https://doi.org/10.3390/app14062421
• Das Swain V Gao L Mondal A Abowd G De Choudhury M (2024) Sensible and Sensitive AI for Worker Wellbeing: Factors that Inform Adoption and Resistance for Information Workers Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems 10.1145/3613904.3642716 (1-30) Online publication date: 11-May-2024 https://dl.acm.org/doi/10.1145/3613904.3642716
• Aburakhia A Alshayeb M (2024) A Machine Learning Approach for Classifying the Default Bug Severity Level Arabian Journal for Science and Engineering 10.1007/s13369-024-09081-8 49 :9 (13131-13148) Online publication date: 13-May-2024 https://doi.org/10.1007/s13369-024-09081-8
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Index Terms

General and reference

Cross-computing tools and techniques

Social and professional topics

Professional topics

Management of computing and information systems

Project and people management

Software and its engineering

Software creation and management

Software development process management

Software notations and tools

Software configuration management and version control systems

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Information, published in.

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Ryerson University, Canada

• Program Chair:

University of Birmingham, UK

• Publications Chair:

University of Oulu, Finland

Association for Computing Machinery

New York, NY, United States

Publication History

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• Affective Analysis
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• Mining software repository
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• 59 Total Citations View Citations
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• Shafiq S Mayr‐Dorn C Mashkoor A Egyed A (2024) Balanced knowledge distribution among software development teams—Observations from open‐ and closed‐source software development Journal of Software: Evolution and Process 10.1002/smr.2655 Online publication date: 13-Feb-2024 https://doi.org/10.1002/smr.2655
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• Khalajzadeh H Shahin M Obie H Agrawal P Grundy J (2023) Supporting Developers in Addressing Human-Centric Issues in Mobile Apps IEEE Transactions on Software Engineering 10.1109/TSE.2022.3212329 49 :4 (2149-2168) Online publication date: 1-Apr-2023 https://dl.acm.org/doi/10.1109/TSE.2022.3212329
• von der Mosel J Trautsch A Herbold S (2023) On the Validity of Pre-Trained Transformers for Natural Language Processing in the Software Engineering Domain IEEE Transactions on Software Engineering 10.1109/TSE.2022.3178469 49 :4 (1487-1507) Online publication date: 1-Apr-2023 https://dl.acm.org/doi/10.1109/TSE.2022.3178469
• Diamantopoulos T Nastos D Symeonidis A (2023) Semantically-enriched Jira Issue Tracking Data 2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR) 10.1109/MSR59073.2023.00039 (218-222) Online publication date: May-2023 https://doi.org/10.1109/MSR59073.2023.00039
• Coremans B Klomp A Rukmono S Krüger J Fahland D Chaudron M (2023) Process Mining from Jira Issues at a Large Company 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME) 10.1109/ICSME58846.2023.00055 (425-435) Online publication date: 1-Oct-2023 https://doi.org/10.1109/ICSME58846.2023.00055
• Krasniqi R Do H (2023) Towards semantically enhanced detection of emerging quality-related concerns in source code Software Quality Journal 10.1007/s11219-023-09614-8 31 :3 (865-915) Online publication date: 17-Feb-2023 https://dl.acm.org/doi/10.1007/s11219-023-09614-8

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Requirements management in Jira - the basics pt.1

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Katarzyna Kornaga _Deviniti_

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Use advanced search with Jira Query Language (JQL)

The advanced search is the most powerful and flexible way to search for your issues in Jira. You can use the Jira Query Language (JQL) to specify criteria that cannot be defined in the quick or basic searches. For example, you can use the ORDER BY clause in a JQL query to search for issues and display them in an ascending or descending order.

JQL is for everyone: developers, testers, agile project managers , and business users. However, you need to know how to construct structured queries using JQL to use this feature.

• What is advanced search in Jira Cloud?

Optimize your searches with advanced search in Jira Cloud and learn how to construct precise queries in JQL.

• JQL functions

Learn how to use JQL functions for advanced searching in Jira.

Learn how to use JQL fields for advanced searching in Jira.

• JQL developer status

Track your development progress with JQL developer status in advanced searching.

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Learn how to use JQL keywords for advanced searching in Jira.

JQL operators

Learn how to use JQL operators for advanced searching in Jira.

Search for Advanced Roadmaps custom fields in JQL

Search for issues with custom issue fields used in Advanced Roadmaps with JQL.

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