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- Herausgeber: Open Book Publishers
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
- Veröffentlichungsjahr: 2019
Effective Research Data Management (RDM) is a key component of research integrity and reproducible research, and its importance is increasingly emphasised by funding bodies, governments, and research institutions around the world. However, many researchers are unfamiliar with RDM best practices, and research support staff are faced with the difficult task of delivering support to researchers across different disciplines and career stages. What strategies can institutions use to solve these problems?
Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences and the organisational context, the authors of this book have created an essential resource for organisations looking to increase engagement with their research communities.
This handbook is a collaboration by research institutions, for research institutions. It aims not only to inspire and engage, but also to help drive cultural change towards better data management. It has been written for anyone interested in RDM, or simply, good research practice.
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ENGAGING RESEARCHERS WITH DATA MANAGEMENT
Engaging Researchers with Data Management
The Cookbook
Connie Clare, Maria Cruz, Elli Papadopoulou, James Savage, Marta Teperek, Yan Wang, Iza Witkowska, and Joanne Yeomans
https://www.openbookpublishers.com
© 2019 Connie Clare, Maria Cruz, Elli Papadopoulou, James Savage, Marta Teperek, Yan Wang, Iza Witkowska, and Joanne Yeomans
This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY 4.0). This license allows you to share, copy, distribute and transmit the text; to adapt the text and to make commercial use of the text providing attribution is made to the authors (but not in any way that suggests that they endorse you or your use of the work). Attribution should include the following information:
Connie Clare, Maria Cruz, Elli Papadopoulou, James Savage, Marta Teperek, Yan Wang, Iza Witkowska, and Joanne Yeomans, Engaging Researchers with Data Management: The Cookbook. Cambridge, UK: Open Book Publishers, 2019, https://doi.org/10.11647/OBP.0185
In order to access detailed and updated information on the license, please visit, https://doi.org/10.11647/OBP.0185#copyright
Further details about CC BY licenses are available at, https://creativecommons.org/licenses/by/4.0/
All external links were active at the time of publication unless otherwise stated and have been archived via the Internet Archive Wayback Machine at https://archive.org/web
Updated digital material and resources associated with this volume are available at https://doi.org/10.11647/OBP.0185#resources
Every effort has been made to identify and contact copyright holders and any omission or error will be corrected if notification is made to the publisher.
This is the eighth volume of our Open Report Series
ISSN (print): 2399-6668
ISSN (digital): 2399-6676
ISBN Paperback: 978-1-78374-797-9
ISBN Hardback: 978-1-78374-798-6
ISBN Digital (PDF): 978-1-78374-799-3
ISBN Digital ebook (epub): 978-1-78374-800-6
ISBN Digital ebook (mobi): 978-1-78374-801-3
ISBN XML: 978-1-78374-802-0
DOI: 10.11647/OBP.0185
Cover image: Photo by Johannes Groll on Unsplash, https://unsplash.com/photos/mrIaqKh9050
Cover design: Anna Gatti.
Contents
Acknowledgementsxi
Forewordxiii
I. Introduction2
II. Methodology6
III. How to Use this Cookbook10
CASE STUDIES14
1.
Research Data Management Policy: The Holy Grail of Data Management Support?
16
1.1.
Are You a Research Data Superhero? One Person Making a Big Difference at Makerere University
18
Changing the Mindset of Researchers
19
Never Overlook an Opportunity to Speak about RDM
20
How Fast Do Things Change?
22
Additional Resources
22
1.2.
Does a Policy Solve Everything? Policy as a Driver for Engagement at Leiden University
24
A Crown Is Merely a Hat that Lets the Rain In
25
Leiden’s Use of its RDM Policy to Prompt Discussion
25
‘One Size’ Does Not Fit All
26
Why Does this Kind of Engagement Take Time?
26
Continuing the Engagement with a Matrix of Support Services
27
2.
Finding Triggers for Engagement
32
2.1.
Taking Advantage of Existing Administrative Systems: MRC/CSO Social and Public Health Sciences Unit, University of Glasgow
34
Engagement as Early as Possible — The WHY
35
How Early Is Early? The HOW
35
Benefits for the Researcher — The WHAT
36
Looking Back, Does It Work?
38
2.2.
Engaging with Researchers through Data Management Planning at the University of Manchester
40
What Do You Learn from Checking So Many DMPs?
43
Avoiding Being a Victim of Your Own Success
44
2.3.
Timing Is Everything When It Comes to Engaging with Researchers at the University of Technology Sydney
46
3.
Engagement through Training
50
Where There’s a Will, There’s a Way
50
3.1.
Bring Your Own Data (B.Y.O.D.) Workshop at the University of Cambridge
52
A Helping Hand
53
A ‘B.Y.O.D.’ Invitation
53
Feedback for Future Learning
55
3.2.
Introducing Data Management into Existing Courses at the University of Minnesota
56
From Grassroots to Widespread Influence
57
A Lightweight Approach Makes for an Excellent Return on Investment
57
Create a Community to Make It Sustainable
59
3.3.
Engaging with RDM through a PhD Course on Academic Integrity and Open Science at UiT The Arctic University of Norway
60
Why PhDs?
61
What Works? Good Content and a Thoughtful Course Layout
61
Course Preparation is an Educational Process Itself
62
RDM Training as an Institutional Effort
63
3.4.
Open Courses at UiT The Arctic University of Norway
64
Opening the Door to RDM Training
65
Tips for Embedding Engagement in the Course Delivery
65
4.
Dedicated Events to Gauge Interest and Build Networks
68
4.1.
‘Dealing with Data’ Conference at the University of Edinburgh
70
Inviting Researchers to Explain How They Deal with Data
71
Hunting for a Good Theme
72
Manoeuvring to Broaden the Audience
72
4.2.
DuoDi: The ‘Days of Data’ at Vilnius University
74
Library Services from a Business Perspective
75
Success and the Need to Grow
75
4.3.
Let’s Talk Data: Data Conversations at Lancaster University
78
Little Time? Little Money?… But Still Want to Have a Community of Researchers Talking with Passion about Data? You Can Have It with Data Conversations!
79
So What’s the Recipe?
79
If You Want to Talk about Data, Allow Time for Talking
80
Community Building and Cultural Change
80
‘FAIL’ Means ‘First Attempt In Learning’
81
Additional Resources
81
4.4.
Starting New Data Conversations at Vrije Universiteit Amsterdam
82
Getting the Timing Right
83
Good Connections Mean a Lot
83
An Engaging Event Is Not the Same as Community Building
83
Keep Calm and Get Started
84
Additional Resources
85
4.5.
Talk to Understand Your Community Better: Informal Events at the Open University
86
Two Informal Events to Get Discussions Started
87
So What’s Next?
87
Advice for Others Who Want to Start
88
5.
Networks of Data Champions
90
Lack of Funding? Need More RDM Support? Build a Community-Based Model
90
5.1.
Data Champion Programme at the University of Cambridge
92
Establishing a Data Champions Network
93
Growth of a Community
93
What Does It Take to Become a Data Champion?
94
What’s in It for You?
95
The Challenges
95
5.2.
TU Delft Data Champions
98
The Glue that Holds the Community Together
99
Reward and Recognition: If They Make It ‘FAIR’ for Us, We Should Make It Fair for Them
99
Tweeting and Tagging
101
Final Thoughts and Future Steps
102
5.3.
Data Stewards at Wageningen University and Research
104
Meet the Team
105
From ‘Data Savvy’ to ‘Data Steward’
105
Measuring Cultural Change
106
6.
Dedicated Consultants to Offer One-to-One Support with Data
110
Subject-Specific Consultants Are an Add-On to ‘Traditional’ RDM Support at Large Institutions
110
‘Show Me the Money’
111
6.1.
Data Stewards at TU Delft: A Reality Check for Disciplinary RDM
112
Job Definition: Have Disciplinary Expertise in Data Management, Take Initiative and Be a People Person
113
Coordination Is Crucial to Create Operational Synergy
114
Institutional Support Is Needed for Implementation
114
6.2.
Cultural Change Happens One Person at a Time: Informatics Lab at Virginia Tech
116
Domain-Specific Consultants at the Informatics Lab
117
Research Background — A Double-Edged Sword?
118
Five Full-Time Employees Are Expensive — Are They Worth the Investment?
118
6.3.
Ever Heard of Five-Legged Sheep? Data Managers at Utrecht University Give Researchers a Leg-Up!
120
The Secret Ingredients Are People
122
7.
Interviews and Case Studies
126
7.1.
Showcasing Peers and their Good Practice: Researcher Interviews at Vrije Universiteit Amsterdam and Utrecht University
128
What Ingredients Do You Need to Get Started?
130
8.
Engage with Senior Researchers through Archiving
134
A Turnaround in Habit
134
8.1.
Soliciting Deposit and Preservation of University-Produced Research Data as Part of Broader Archives and Records Management Work
136
Don’t Forget about the Physical Data!
137
It’s about Shifting Perspectives
137
What the Future Holds
138
Confused about Where to Start? Foster Data Champions and Build upon Existing Services
138
8.2.
Starting at the End: Seniors’ Research Data Project at the UiT The Arctic University of Norway
140
What If You Start at the End?
141
How Do Senior Researchers Differ from Early-Career Researchers?
141
Targeting the Right People
142
Coming Out of Your Comfort Zone: A Tough Decision
142
Contributors144
List of Illustrations and Tables150
Acknowledgements
We would like to thank Alastair Dunning, Head of Research Data Services at TU Delft Library for sponsoring the book sprint.
We would also like to thank:
Alastair Dunning, Head of Research Data Services, TU Delft Library;
Raman Ganguly, University of Vienna, Central Computer Centre;
Lauren Cadwallader, Deputy Manager of Scholarly Communication (Research Data Management), Cambridge University Library;
Hilary Hanahoe, Secretary-General, Research Data Alliance;
Joeri Both, Head of Research Support, Vrije Universiteit Amsterdam;
Laurents Sesink, Head of Centre for Digital Scholarship, Leiden University Libraries;
Joshua Finnell, Associate Professor in the University Libraries, Colgate University Research Council, Colgate University; and
Martine Pronk, Academic Services Department Manager, and Iza Witkowska, Research Data Consultant, Utrecht University Library;
for contributing to the publishing costs of the book.
Foreword
Fig. I. Hilary Hanahoe, Secretary-General, Research Data Alliance, CC BY 4.0.
Research data management is no longer a new or unknown concept for today’s researchers, but nonetheless it can be intimidating. Many universities, institutes, organisations, and funding agencies have guidelines, mandates, and even policies around data management. But that does not make the task any less daunting; indeed it often adds a complicated layer of work and effort to data-producing research activities. Domain- and discipline-specific data comes in all sizes and forms, so specialised information is required to facilitate correct research data management. In addition, in recent years the very important and highly popular ‘FAIR’ principles1 have been brought into the picture.
Engaging Researchers with Data Management: The Cookbook has been compiled and edited by experts from the Research Data Alliance (RDA) to support anyone who helps researchers to understand and navigate their way around research data management and to find solutions. The RDA2 is an international forum building social and technical bridges to enable the sharing and re-use of research data. It offers open solutions to multiple stakeholders through outputs developed by focused Working Groups and Interest Groups. These groups are formed by volunteer experts from around the world and draw members from academia, the private sector and government. This publication is one such output.
The Libraries for Research Data Interest Group3 is one of over 85 RDA groups and has already produced the highly successful 23 Things: Libraries for Research Data.4 This output is an overview of the practical, free, online resources and tools that you can begin using today to incorporate research data management into your practice of librarianship. The document is available in twelve languages and a 23 Things programme has been created and adapted into more than six domain-specific scenarios.
The Cookbook is another wonderful output from this Interest Group and a concrete example of volunteer effort within the RDA community, as well as the continued contribution of the Libraries for Research Data Interest Group to RDA and the community at large.
Collaboration, cooperation and co-creation are the hallmarks of the RDA and the Cookbook team’s activities. I am very grateful to each and every member of the large team of editors, authors, illustrators and case-study contributors for their effort and expertise.
I sincerely hope that you, the readers, will be inspired and feel more engaged after reading this publication and, if you are a researcher, will join the cohort of colleagues who believe that research data management is not only less daunting than is generally believed, but also a win-win for your career.
Hilary Hanahoe
Secretary-General, Research Data Alliance
1 Mark D. Wilkinson et al., ‘The FAIR Guiding Principles for scientific data management and stewardship’, Scientific Data 3:160018 (2016), https://doi.org/10.1038/sdata.2016.18
2 Research Data Alliance, https://www.rd-alliance.org/
3 Libraries for Research Data Interest Group, https://www.rd-alliance.org/groups/libraries-research-data.html
4 Research Data Alliance, 23 Things: Libraries For Research Data, https://www.rd-alliance.org/group/libraries-research-data-ig/outcomes/23-things-libraries-research-data-supporting-output
I. Introduction
© Clare, Cruz, Papadopoulou et al., CC BY 4.0 https://doi.org/10.11647/OBP.0185.24
Good Research Data Management (RDM) is a key component of research integrity and reproducible research, and its value is increasingly emphasised by funding bodies, governments, and research institutions. However, discussions about data management and sharing are often limited to librarians, data professionals, and researchers who are already passionate about data stewardship and open science. In order to implement good RDM practice throughout research communities a cultural shift is necessary, and effective engagement with researchers, who are the main data producers and re-users, is essential for this shift to happen.
What Is this Book About?
This book contains 24 RDM case studies, each describing an innovative activity used by a research institution to engage with its researchers about research data. These case studies, collected from research institutions worldwide, illustrate the diversity of feasible initiatives that could be implemented in other institutional settings.
The aim of this book is to inspire and inform those responsible for RDM using activities that have already been implemented and reflected upon elsewhere, and to help drive overall cultural change towards better data management. Our focus is not on what constitutes good research data management, but rather how it can be effectively communicated to the research community.
Who Is this Book For?
This book has been written for anyone interested in RDM, or good research practice more generally. It will be particularly useful to those interested in how to effectively engage with researchers about research data management. This might include librarians, data managers, data stewards, archivists, members of ICT (Information and Communication Technology) departments, colleagues from legal and financial support, faculty management, senior executives at institutions, funders, policymakers, publishers, members of the commercial sector, and researchers at any career stage who want to change practices among their peers. In short, if you have read this far, then this book is for you.
Why Read this Book?
We hope that reading this book will:
inspire you to implement new activities to engage with researchers about research data;help you find the activities most suitable for your institutional setting (according to size, research profile, resources available for data management, target audience, etc.);inform you about the ease of implementing each case, identifying the specific challenges associated with them and possible tips to overcome these;give you a general overview of what other institutions around the world do to engage their researchers with research data;provide you with tangible suggestions for actions that you could present to senior management at your institution;stimulate collaboration. We hope that reading our case studies and learning about the initiatives adopted by contributing institutions will lead to new connections and cooperation.How Should I Read the Book?
However you want! We designed this book with a diverse audience in mind, and while some might be keen to read everything from beginning to end, others may decide to focus on a selection of the most relevant chapters or case studies. All of our case studies have been carefully selected for your interest, however, you might find our ‘How to Use This Cookbook’ infographic helpful to navigate the cases of most interest to you. This book is analogous to a cookbook in the sense that it presents each individual case study in a similar format to that of a recipe. Each case study contains a list of ‘key ingredients’, that is, the institutional context and key elements required to successfully implement the initiative, as judged by the people directly involved. For example, information on the number of researchers involved, the target audience, the cost and ease of its implementation are presented in comprehensible, visual manner so that the reader can easily understand and compare case studies.
How Did this Book Come About?
There are many interesting initiatives utilised by research institutions all over the world to effectively engage with their research communities about research data. Typically, those interested in RDM support and engagement learn about these diverse activities at conferences, by going to a talk from someone who implemented such an initiative and/or discussing it in person. In addition, some RDM units and institutional libraries may have blogs that report their ongoing activities, and well-connected individuals may pick up useful information directly through their networks. . But is this really the most effective way to share good practice? What about those who cannot attend conferences, or those who are just starting with RDM and don’t yet have established connections or know where to look online for more information? How do they get started?
With these concerns in mind, the authors, together with members of Research Data Alliance1 (and the Libraries for Research Data Interest Group2 in particular) decided to collect information from various institutions worldwide on how they engage researchers about managing their research data. The goal was to make this body of knowledge about good practice more readily available by collecting it into a book that would be more discoverable and accessible to the wider community of research data supporters. Our goal was to make it as easy as possible for others to get started supporting good practice in RDM, and rather than reinventing the wheel, facilitate the adoption and adaptation of existing methods from similar institutional settings. We hope you find this book as interesting to read, as we found collecting the information and putting it all together.3
II. Methodology
The aim of the project ‘Research Engagement with Data Management’ was to collect case studies from different organisations around the globe that focus on how to engage with the research community about research data management. By asking various questions about the models used and also about the organisational context, we created a useful resource for organisations that are looking to increase their engagement with their research communities.
In order to achieve this, we first designed and sent out a survey ‘Researcher Engagement with Data Management: What Works?‘ to 60 funders, 80 scientific institutions, and 28 relevant mailing lists worldwide, as well as social media channels including blogs and Twitter. The survey was open from 18 January until 14February 2019, and is available through Zenodo.4
Respondents were asked to think about which of their methods of researcher engagement would be of interest to other organisations. Each respondent was encouraged to mention as many initiatives used to engage researchers as they thought relevant, and to fill in the survey separately for each initiative. In addition, they were asked to characterise their research institution (number of researchers, number of PhD students, number of full-time employees providing data management support), as well as their engagement activity (target group, main drivers, activity cost, ease of implementation at a different institution) by responding to quantitative questions (see the survey template5 for the details of questions and possible answers). For example, to estimate the cost of running the activity, respondents were asked to select one of five ranked options, ranging from ‘inexpensive’ to ‘expensive’. Respondents were not asked to elaborate on their choices, or justify them.
We received 234 responses. Of these, 90 were complete and provided details describing the engagement activities, such as the activity objective, description, challenges and opportunities associated with the activity, etc. Responses that provided enough information to understand the activity were considered as valid responses and used for further selection of the most innovative activities.
The final selection of case studies was done by five volunteers. Each volunteer was asked to select 20 to 25 cases, which, based on their RDM knowledge and experience, looked innovative, inspiring and applicable to research institutions worldwide. There were no other criteria used for the selection process. To make sure that important engagement activities were not omitted from this study, the volunteers were also asked to suggest other innovative activities that they were aware of, but which were not submitted through the survey.
All cases selected by volunteers were used for the final selection. This selection was made based on the overlap between these five different lists. If a case study was listed on three or more of the five lists, it made it to the final list. In this way, 24 cases made it to this final list. Out of these, 17 were activities submitted via the survey and 7 were new activities. The list was discussed and approved, first by the five volunteers and afterwards by the entire project group.
In the next stage, we undertook hour-long interviews with ‘respondents’ of all shortlisted cases in order to collect missing information, quotes and photos. The interviews were recorded, transcribed and shared with the writing team.
To write the book, we organized a three-day ‘book sprint’ in The Hague, Netherlands. Six writers and two editors (one on-site and one working remotely), took part in the book sprint. Cases were grouped into eight themes, based on the main focus of the activity: policy, data management plans, training, events, community networks, dedicated consultants, interviews and data from senior researchers. All cases were divided between the writers, written up using the collected information, and then reviewed and edited with the help of the writers. By the end of the three days the first draft of the book was finished. After the book sprint, the editing work continued, and final versions of each case study were sent to respondents for their approval during the following week. Subsequently, the book was publicly shared for consultation, and editing continued on an ongoing basis in response to community feedback.6
III. How to Use this Cookbook
This infographic (Table I, left) has been designed to help you to navigate case studies of interest, and to select those most suitable for implementation within your research institution. Just like a cookbook recipe, we provide a list of ‘key ingredients’ in a graphical format: the elements you’ll need to successfully implement each initiative.
Table I. Graphical representation of the key ingredients of each case study, CC BY 4.0.
In addition, we also provide a table (Table II, below) with a quick overview of all case studies and recipes (ingredients) necessary to implement them. You can use this quick overview to navigate directly to cases which might be most relevant to the situation at your institution (for example, the amount of resources available to you to engage with researchers).
Table II. Overview of all cases and their key ingredients, CC BY 4.0.
Table II. (continued from previous page).
1 Research Data Alliance, https://www.rd-alliance.org/
2 Libraries for Research Data Interest Group, https://www.rd-alliance.org/groups/libraries-research-data.html
3 A blog post about the book sprint during which we wrote the Cookbook is available online: Connie Clare, ‘Book Sprint Success: A Team Writing Exercise for the Win’, 23 July 2019, https://www.rd-alliance.org/blogs/book-sprint-success-team-writing-exercise-win.html
4 Iza Witkowska, ‘The Survey Researcher Engagement with Data Management: What Works?’ (22 July 2019), Zenodo, http://doi.org/10.5281/zenodo.3345305
5 Ibid.
6 Draft book with full version and comment history available online: https://docs.google.com/document/d/1XnXJeOocmaz-xU0oTmMLpBXrcFTdHmBDQG8bHMq7_GY/
Case Studies
1. Research Data Management Policy: The Holy Grail of Data Management Support?
One of the easiest but most impactful ways to engage with researchers is to create awareness about the need for good Research Data Management (RDM) and then agree on what good RDM looks like. Upon this foundation many other services and activities can be built.
In this chapter, we introduce two case studies that demonstrate how engaging with researchers can create this foundation by:
Getting the concept of RDM accepted.Collaborating to define what is meant by good RDM and to agree a policy to achieve this.Following up with researchers to ensure the policy is implemented.Both case studies are relatively inexpensive to implement if enthusiastic and talented staff are available but require access to influential people or administrative support structures.
1.1. Are You a Research Data Superhero? One Person Making a Big Difference at Makerere University
Author: Joanne Yeomans
Contributor: Joseph Ssebulime
© Joanne Yeomans and Joseph Ssebulime, CC BY 4.0 https://doi.org/10.11647/OBP.0185.01
Makerere University demonstrates how one person can start engaging with researchers about data management before any formal institutional resources or services are in place.
Table 1.1, CC BY 4.0.
In September 2017, Joseph Ssebulime interviewed research staff at Makerere University about their views on sharing their research data. Every one of them saw sharing or even storing their data anywhere but on their own computer as a loss of control over their work and an unwelcome interference, so they were far from ready to discuss the possible implementation of a university policy for research data management. Less than two years later, Joseph is thinking about speaking to them again to see if their views are still the same. What has happened in that period that might have changed their mind?
Changing the Mindset of Researchers
After graduating in Records and Archives Management from Makerere University in 2015, Joseph was working in the university library as a Reference Librarian and searching for a topic for his Master’s study. He explained how his interest came about:
I came across Research Data Management (RDM) as a concept and realised that Makerere was lacking these services so I decided to research what RDM support meant, and then investigate the views of Makerere researchers about data sharing. I thought they would be interested in how their data could be looked after and re-used
Joseph sought out individuals who had published research papers in the previous five years and recorded interviews with them. ‘I was really surprised that they had no interest in changing their data management habits,’ he admitted. Astonished at the lack of enthusiasm for RDM services, he was unsure what to do next.
Luckily, an opportunity arose to speak with the Deputy Vice Chancellor (DVC) for Academic Affairs and, upon proposing that Makerere University needed to implement a data management policy, Joseph found in him a strong ally. They both believed that it is essential to start with a research data management policy as a foundation.
With the support of the DVC, Makerere University is at the beginning of its RDM policy journey. Maintaining engagement with the researchers is an important priority as this will help to ‘change their mindset’ by addressing their concerns and then finding infrastructure solutions that work for them.
Never Overlook an Opportunity to Speak about RDM
Joseph takes advantage of every occasion he can find to discuss the need for good RDM with researchers. He seeks opportunities at conferences and other university events to approach Makerere research staff and start a conversation about their data. His aim is to sensitize them to the need for good practice, so that the introduction of a policy and its associated procedures becomes easier. His personal enthusiasm drives him to continually look for opportunities to raise awareness about RDM whilst carrying out his job as a Reference Librarian.
Fig. 1.1.1 Conferences offer a great way to network with researchers: Joseph Ssebulime discusses data management with a conference participant at the University of Pretoria, August 2018. Photograph by Anthony Izuchukwu, CC BY 4.0.
At Makerere University there is no network drive, meaning that most researchers rely on their personal computer to store their work. A training session on ‘Backing up information online using Google Drive’ provided a valuable service for researchers as well as an ideal opportunity to talk with them more generally about RDM.
Another such opportunity arose during training on how to use the institutional preprint repository. ‘Open access’ is a well-known and accepted concept at Makerere University so it was natural to run training sessions on uploading articles to the repository, and these sessions are well-attended. Because some publishers now also require authors to publish the data underlying their article, Joseph can include some data management topics in this training session and use it as another chance to talk about RDM.
Social media is another obvious way to reach people at the university, and Facebook posts are effective in helping to raise awareness about RDM.
Fig. 1.1.2 Poster showing a visual representation of the RDM Roadmap for Makerere University used to raise publicity and start discussions with research staff and senior university managers at meetings and conferences.1 By Joseph Ssebulime, CC BY 4.0.
1 Poster submitted to the 2018 IFLA Library and Information Congress: Joseph Balikuddembe Ssebulime, Martie Van Deventer and Heila Piennar, ‘The role Academic Libraries could play in sensitizing researchers about research data management: a case of Makerere University Library’, Session 153 — Poster Session, IFLA WLIC 2018 — ‘Transform Libraries, Transform Societies’, Kuala Lumpur, Malaysia, 27 August 2018, http://library.ifla.org/id/eprint/2297
How Fast Do Things Change?
Joseph believes that the impact of his activity on driving cultural change is ‘a little bit slow but very steady’. It’s useful to have an ‘elevator pitch’ ready for when an opportunity arises, and he advises anyone interested in driving data management awareness to ‘start by having conversations with as many stakeholders as possible across the university; this can begin with a brief discussion whenever there is a chance to talk to a senior official;’ if they are convinced, these conversations pave the way for more formal approaches and proposals. It’s clear that having a confident personality is beneficial for success, but with the right people in place Joseph believes that ‘every academic institution across the country’ can implement this activity. Are you the person who can do it?
Additional Resources
Ssebuline, Joseph, Van Deventer, Martie, and Pienaar, Heila, ‘The Role Academic Libraries Could Play in Developing Research Data Management Services: A Case of Makerere University Library’, [Preprint], 5 July 2018, https://www.researchgate.net/publication/326208493
1.2. Does a Policy Solve Everything? Policy as a Driver for Engagement at Leiden University
Author: Joanne Yeomans
Contributors: Fieke Schoots, Laurents Sesink
© Yeomans, Schoots and Sesink, CC BY 4.0 https://doi.org/10.11647/OBP.0185.02
The Centre for Digital Scholarship at Leiden University reaches out directly to research institutes to understand the support they need to implement RDM policy.
Table 1.2, CC BY 4.0.
A Crown Is Merely a Hat that Lets the Rain In
A Research Data Management (RDM) policy can outline expectations but by itself will rarely engender a change of behaviour. Worse, although it may be the culmination of many months or years of work, it may prove to be ‘merely a hat that lets the rain in’ if not properly implemented, exposing gaps in service provision and support, and magnifying the resistance that academics feel towards administrative tasks that take them away from their research.
Engaging researchers to help produce a practical plan for implementing an RDM policy can, however, prove to be an ideal way of learning first-hand what they need to support their data management. The policy can therefore become the ‘crown’ that demonstrates the effectiveness and success of the resulting RDM services.
Leiden’s Use of its RDM Policy to Prompt Discussion
Leiden University Libraries’ Centre for Digital Scholarship is taking the RDM discussion directly to researchers, by engaging with individual researchers on a one-to-one basis and by reaching out to research institutes and finding out what they need in order to be able to implement the Leiden University RDM Regulations1 approved in 2016.
‘We can use our RDM policy as the reason to arrange a meeting and discuss what is expected by the university in terms of data management,’ says Fieke Schoots, a Data Management Expert at the Centre for Digital Scholarship who initiated and coordinates the data management activities at Leiden University Libraries. Once a meeting is underway, ‘we can use the policy as a focus for finding out what is needed, by an individual or a research group, to improve their data management and so we can plan to work on solutions to make their data management easier.’ These solutions help to provide incentives that result in compliance with the policy.
The result is an environment where researchers know where to go to ask for support with their data management and the central support services have a better understanding of the practical needs of the research staff regarding their research data.
‘One Size’ Does Not Fit All
The Leiden policy regulations recognise that disciplinary differences exist for many practical data management decisions and, therefore, avoid imposing a ‘one-size-fits-all’ solution. The regulations indicate explicitly where departments and institutes should devise their own procedures, and include a whole section on ‘elaboration’ that lists the specific decisions that need to be taken at a faculty or institutional level to supplement the generic policy.
Implementation of the regulations was expected to be completed by 2019 and was to be carried out jointly by the faculties and various central services: the ICT (Information, Communication and Technology) Shared Services, Academic Affairs, Information Management, and the Centre for Digital Scholarship. Some progress was made with some faculties, but by 2018 it became clear that the levels of engagement required to bring about change across the entire University were beyond the current staffing capacity. The implementation period was, therefore, extended to the end of 2020 and new support staff appointments began.
Why Does this Kind of Engagement Take Time?
In early 2019, two members of the university library visited every faculty board to discuss the needs for support regarding open access, data management (including the procedures and services needed to elaborate and implement the policy), and the use of digital tools and methodologies. Regarding data management there were still too many diverse needs at the faculty level and so a new round of talks has begun with the 29 institutional scientific committees.2
To begin the conversation, a report on the current data management support for researchers in each institute has been produced, using enquiry and training statistics and a qualitative description of the current relevant services. This kind of engagement is staff- and time-intensive to organize and carry out.
Although the absence of dedicated staff was slowing the pace of change, it was not the only problem. ‘Research staff were sometimes reluctant to start discussing new services whilst still waiting for solutions to long-standing problems,’ says Fieke. It was clear that solutions would need to be delivered to persuade research staff to engage in new discussions. As a result, several pilot projects have begun in parallel to develop solutions for the storage of legacy data sets and encryption tools.
Continuing the Engagement with a Matrix of Support Services
In order to improve the connections between staff, maintain the ongoing engagement, and deliver solutions, the steering board has agreed to a new approach to organising and strengthening support that employs both decentralised and centralised expertise (see Fig. 1.2.1).
Fig. 1.2.1 Leiden University’s proposed thematic and disciplinary networks, 2019. By Marcel Villerius, Leiden University, CC BY 4.0.
Fieke explained this new approach:
The matrix identifies key support themes, such as ethics and legal advice, where there are existing staff both in central support units and embedded within the faculties or institutes. Upon this matrix you can build multidisciplinary and thematic networks to bring these staff members together at a faculty level and a theme level, respectively.
The first thematic ‘Data Management Network’ event was organised by the Centre for Digital Scholarship in June 2019. It brought together embedded data stewards, central RDM support staff, and researchers who are particularly active in data management from across the whole university, to talk about their priorities for developments to improve data management practice.
Through this meeting, central support staff have already learnt more about the research processes and needs of researchers, and researchers have learnt more about the expertise and possibilities offered by further engagement with central support staff.
The ongoing efforts to engage researchers have been very rewarding for both sides, but have also been necessary to ensure that the regulations are a welcome tool for change.
Fig. 1.2.2 Leiden University’s Data Management Network convening event, 27 June 2019. Leiden University Libraries, CC BY 4.0.
1 Research Data Management Regulations, Leiden University, April 2016, https://www.library.universiteitleiden.nl/binaries/content/assets/ul2ub/research--publish/research-data-management-regulations-leiden-university_def.pdf
2 Leiden University Scientific Institutes, https://www.universiteitleiden.nl/en/about-us/management-and-organisation/faculties/institutes
2. Finding Triggers for Engagement
Despite the benefits of data management planning for the researcher, many still regard it as an administrative burden. Interestingly, some institutions were able to turn data management planning into an opportunity to engage researchers in discussions about data.
This chapter looks at several case studies where workflows have been designed to bring about interaction and engagement at key moments in the research process.
Being able to work in collaboration with other support or management units within the university was a key factor in each of these.
2.1. Taking Advantage of Existing Administrative Systems: MRC/CSO Social and Public Health Sciences Unit, University of Glasgow
Authors: Joanne Yeomans, Iza Witkowska
Contributor: Mary-Kate Hannah
© Yeomans, Witkowsk and Hannah, CC BY 4.0 https://doi.org/10.11647/OBP.0185.03
Piggybacking onto an existing system for approving research proposals, the Health Sciences Unit at the University of Glasgow automatically contacts researchers that might need RDM support at the beginning of their projects, and then follows up throughout the project’s lifespan.
Table 2.1, CC BY 4.0.
Engagement as Early as Possible — The WHY
In the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow,1 the department representatives decided to use an existing administrative reporting system to help engage with researchers about data management issues and to manage requests coming to the IT (Information Technology) and other support staff offices.
Part of the reason we set up this system is that people would apply for grants, and then when the research started they’d go to the support staff and ask: can you help me with transcribing, can you help me with fieldwork or whatever else was needed, and the support staff representative would say: we don’t have this in our diary, we have two other surveys happening at the moment, so we can’t do this, we need warning that these things are going to happen. So now, because it’s reported in advance in the system, they can plan, they can take on new staff, anything that is needed. — Mary-Kate Hannah, Data Scientist in the Unit.
How Early Is Early? The HOW
Whenever a project is initiated, a researcher has to fill in and submit an online form. The research proposal is considered by the ‘Portfolio Group’ which checks that the topic is in line with the unit’s focus and identifies what resources might be needed within the department, whether space for staff members, IT facilities, and so on.
The Portfolio Group consists of senior and experienced research staff, and senior representatives of all the different research programmes. Representatives from various support offices also sit in on the meetings. The group considers the proposal and, among other things, identifies whether there is data collection or data creation planned and whether data will be stored at Glasgow University. If so, they tick a box in the form that indicates a data management plan (DMP) is required and this triggers an automatic email to Mary-Kate and to the submitter so that they can follow this up. Without Mary-Kate signing off on the completion of a satisfactory DMP, the researcher cannot move forward with their grant application or their research.
The automated email starts the process of putting Mary-Kate in touch with the researcher to assist with the writing of the plan. This happens regardless of whether a funder requires a DMP or not: if the research is going to generate data that will be stored at Glasgow University, then the department itself still requires a DMP to get things right from the start.
Fig. 2.1.1 Mary-Kate Hannah helping a researcher to complete a DMP at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. Photograph by Enni Pulkkinen, 2019, CC BY 4.0.
Benefits for the Researcher — The WHAT
So, what happens after the sending of the automated email saying that a DMP is needed? The next step involves Mary-Kate sending a customized email and flagging up resources such as the pre-filled DMP template and the DMPonline tool, as well as offering support on any other Research Data Management (RDM) relevant aspect (for example, handling personal data). She also refers researchers to a recorded presentation about RDM consisting of PowerPoint slides with recorded voiceover. This personal touch is definitely the key factor in making the implementation of this process successful.
The RDM support doesn’t end there. Once a project begins, a study or trial master file2 is set up on the network drive and customized for the project team. It has standard folders for storing common administrative documentation, such as grant application and legal documents, and includes a folder for data management. This generic folder structure was developed after looking at and reviewing many studies at the department. ‘Researchers and support staff are very happy with this; it saves time as they don’t have to think about this themselves,’ says Mary-Kate.
Fig. 2.1.2 Mary-Kate Hannah delivering a training session on data management planning at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. Photograph by Enni Pulkkinen, 2019, CC BY 4.0.
Looking Back, Does It Work?
Yes, it does! People are getting used to the idea of planning their data management: because they did it for their last project, they are expecting it for their next project. They have often reported that the process of writing the DMP has been helpful and that they have found conversations with the research data management advisor to be useful.
Having said that, there is still room for improvement in the system to save researchers’ time. For example, researchers need to write similar details in different forms for their grant application, their ethical review request, and their DMP. These forms are delivered at different times and the procedural timing could be better optimized.
Sometimes the detailed information requested in the DMP comes too late, for example, ‘the researcher might have had ethical approval for their data collection consent form which did not contain data-sharing information, then they start to write their data management plan and realize that they will have to make an amendment to their consent form and ask for an amendment to their ethics application,’ says Mary-Kate.
What is clear though, is that embedding a requirement for data management planning directly in the unit’s authorization process is crucial in getting researchers to think about their data management at an early stage, and in putting RDM support staff in contact with researchers right from the start.
2.2. Engaging with Researchers through Data Management Planning at the University of Manchester
Author: Joanne Yeomans
Contributors: Rosie Higman, Christopher Gibson
© Yeomans, Higman and Gibson, CC BY 4.0 https://doi.org/10.11647/OBP.0185.04
The University of Manchester illustrates how careful design of DMP templates and DMP policies allows staff to effectively engage with researchers through DMP review.
Table 2.2, CC BY 4.0.
Requiring an approved Data Management Plan (DMP) before allowing a research project to begin might work for smaller units within a university, but it might not scale up across a large research-intensive university. The University of Manchester has found a way to design their DMP template and DMP requirement process so that the library support team can potentially engage with all researchers at an early stage of their research. Focusing the engagement around the writing of the DMP means that they can offer advice when a researcher is beginning their project, but they can also learn first-hand whether the university’s data management policies are practical.
At the University of Manchester, a DMP is required when applying for funding, ethics approval and/or IT storage. ‘Between these you encompass most research at the university,’ thinks Rosie Higman, Research Services Librarian. ‘I’m not saying we’ve got it perfect but at least in theory, we’re going to cover most projects through these routes.’
The University has DMP templates in the DMPonline3 system that ask university-specific questions in the first section (see Fig. 2.2.1). These include questions about storage needs and whether the research is handling personal data using a tick-box format so that the questions are easier to answer. The University’s Information Governance Office uses this part of the form as the asset register in accordance with the European General Data Protection Regulation (GDPR).
Fig. 2.2.1 Overview of the University of Manchester DMPonline template showing the Manchester-specific questions. University of Manchester Library, CC BY 4.0.
The Research Data Management team (Fig. 2.2.2) in Research Services at the university library check this first section of every DMP and give feedback to the submitter.
Fig 2.2.2 University of Manchester Research Data Management team. From left to right: Jess Napthine-Hodgkinson (Research Services Officer); Clare Liggins (Research Services Librarian); Chris Gibson (Research Services Librarian). Rosie Higman has since started a new position at the University of Sheffield. University of Manchester Library, CC BY 4.0.
What Do You Learn from Checking So Many DMPs?
‘You can certainly tell which DMPs are from people who have been to our training,’ Rosie is pleased to point out. ‘It’s helped us work out where we have lots of gaps, where the policy is unrealistic or the procedures are unsupportable.’ She gives an example: ‘There’s a university procedure for when a researcher makes a recording of a participant; it’s clear and well written and has been around for some time, but it suggests that every researcher should have access to an encrypted recording device and the university is only just working out what the cost of that would be.’
When talking to researchers about a DMP, you are therefore sometimes challenged, ‘how do you do that in practice?’ In the case of encrypted recordings, the Research Data Management (RDM) team, with the help of information governance and IT (Information Technology), has been able to draw up a list of practical steps a researcher can take, but this has raised difficult questions about whether the policy should stand. ‘It’s making our services more responsive to what researchers want,’ concludes Rosie.
Avoiding Being a Victim of Your Own Success
Almost 20% of the submitters request a more detailed review of their DMP and most of these requests are from researchers dealing with personal data or ethical permissions.
Rosie and her team have some standardised answers, which an officer tailors to each case before drafting a response. One of three librarians will then review the officer’s comments and enhance them with more discipline-specific suggestions. They aim to treat each plan in under an hour. ‘We already spend significant time on this and every week meet to discuss the DMP review requests that have come in and how we can balance them with our other work priorities. If the demand increases, we’re not yet sure how to address this,’ admits Rosie.
One technique that they believe will save review time is to remove the option to allow free text and instead offer tick-boxes in answer to fixed questions. The use of pre-drafted comments for responses has also helped, but the time it takes to review a single DMP is still a challenge.
The use of DMPonline started in Manchester in 2018, when the European GDPR also came into effect. Although all researchers are required by university policy4 to write a DMP, it’s not clear what proportion of researchers are doing so. The university also has a system for tracking student progress in general, which requires students to have a conversation with their supervisor, during which there is a prompt to check that the student has a DMP. ‘This is a good start, but obviously carries the risk that if a supervisor does not care about data management then students will not create a DMP,’ says Rosie.
With just over a year of experience in using DMPonline in this way, the library team thinks it is a good time to review the level of compliance. They will do this by checking the institutional records to identify the proportion of research projects that have a DMP and expressing this as a percentage for the university, faculties and schools. The results, expected in late 2019, will be interesting to compare differences in behaviour and should give the team some idea of how demand for reviews might increase.
2.3. Timing Is Everything When It Comes to Engaging with Researchers at the University of Technology Sydney
Author: Iza Witkowska
Contributors: Wendy Liu, Duncan Loxton, Elizabeth Stokes, Sharyn Wise
© Witkowska, Liu, Loxton, Stokes and Wise, CC BY 4.0 https://doi.org/10.11647/OBP.0185.05
At the University of Sydney, support staff provide grant recipients with ‘stub’ DMPs and interviews at the right time to maximize researcher engagement.
Table 2.3, CC BY 4.0.
At the University of Technology Sydney, the eResearch Unit5 in the Central IT (Information Technology) Division and the Library’s Research Data Team6 collaboratively approach recipients of major research grants and offer them a 45-minute interview to provide data management support and create a data management plan (DMP). The aim of this activity is to help grant recipients to comply with the data management plan policy from Australia’s major research funders and to simultaneously engage them with discussions about research data.
Many Research Data Management (RDM) support services within universities and research institutions do this, so what makes the work by the team from the University of Technology Sydney so successful and noteworthy? Well, it’s all in the details.
First, they come to researchers with a ‘stub’ DMP: a pre-filled DMP based on the abstract of the funded grant application. This advance work helps to make things run more smoothly and means they can structure the interview around whether the draft plan accurately characterises the researchers’ data management activities and requirements. And why does this approach work? Well, as the saying goes ‘you catch more flies with honey than with vinegar’. The stub DMP is the ‘honey’ because it takes researchers one step closer to meeting funders’ requirements. The expected outcome of the interview is not to have a completed DMP, but to have started a conversation about data management.
Second, persistence. It’s not always easy to get the lead investigator to respond to the first contact, but our colleagues from Sydney don’t give up. They repeatedly attempt to schedule an interview, and will approach more junior researchers on the project, especially those responsible for data curation/custodianship, if the lead investigator remains unavailable.
Third, their timing is right. These interviews target research teams at the right point in the project cycle to make data management decisions. They also provide an immediate connection to eResearch support if complex software or computational infrastructure is required.
There are benefits on both sides. Researchers engage with research data, and gain awareness of RDM infrastructure and the support available at the university before they need it. The provision of appropriate data storage solutions, software or other infrastructure for their research projects is guaranteed. Policy compliance becomes less of a hurdle, and the increase in collaboration between service units within the university helps to break down institutional silos. Librarians can demystify research data management practices for researchers in a friendly way, while gaining a deeper understanding of specific data management requirements.
The good news is that any organisation able to provide a DMP tool (in this case, Stash,7 a home-grown service integrated into the research management system) and build communication between IT infrastructure and Library/RDM services, can implement a similar initiative. Good communication channels and the ability to provide a swift follow-up are also essential. In order to achieve this, it’s helpful to have a coordinator in place, especially someone familiar with the available IT infrastructure.
To take this service to the next level, this activity can be linked to broader institutional campaigns surrounding academic integrity, raising its profile within the university. Other options are to strengthen collaboration with other research support offices and collect evidence that DMPs improve data management practices, for example, by conducting user satisfaction surveys. To secure the project in the longer term, it is also important to document and communicate its success to senior administration.
1 MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow receives joint core funding from the Medical Research Council (MRC) and the Scottish Government Chief Scientist Office (CSO).
2 Trial master file, https://en.wikipedia.org/wiki/Trial_master_file
3 DMPonline tool, https://dmponline.dcc.ac.uk
4 University of Manchester Research Data Management Policy, http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=33802
5 eResearch Unit, https://eresearch.uts.edu.au/
6 Library’s Research Data Team, https://www.lib.uts.edu.au/research/research-data-management
7 Stash, research data management tool, https://www.lib.uts.edu.au/research/research-data-management/research-data-management-plan-rdmp
3. Engagement through Training
Direct training requires substantial time and effort, but is one of the most effective ways to make people aware of the importance of Research Data Management (RDM) best practices. The following case studies are each aimed to engage researchers with research data through different training methods:
Bring Your Own Data (B.Y.O.D.) workshop at the University of Cambridge;Methods Class Outreach at the University of Minnesota;PhD course at UiT The Arctic University of Norway; Open courses at UiT The Arctic University of Norway.These cases were initiated either by individuals or a small group of RDM support staff, illustrating the potential for a few people to make a difference. The size of the relevant institutions ranges from small to large, showing how such approaches can be implemented across a diverse range of institutional settings.
Where There’s a Will, There’s a Way
Don’t worry if you’re short of resources: our contributors had the same concerns. These activities don’t cost much in terms of training materials and infrastructure, and you can select the most suitable training approaches according to the number of staff at your disposal. If you already have an RDM team in place, you can gain inspiration from UiT in Norway and focus on organising a course tailored to a particular target group. If you have concerns about the capacity of your team, you might find the cases from Cambridge and Minnesota particularly appealing. We hope that you will be inspired by these stories and that you can find suitable training methods for your own institution.
3.1. Bring Your Own Data (B.Y.O.D.) Workshop at the University of Cambridge
Author: Connie Clare
Contributor: Annemarie Hildegard Eckes-Shephard
© Clare and Hildegard Eckes-Shephard, CC BY 4.0 https://doi.org/10.11647/OBP.0185.06
A University of Cambridge Data Champion shows how one volunteer can engage with peers and provide valuable support through leading an interactive workshop on RDM best practices.
Table 3.1, CC BY 4.0.1
1 Note that the figures above are for the Department of Geography, University of Cambridge, and not for the University of Cambridge overall.
Scientific papers tend to be written and presented with clarity and structure, but most would agree that clarity and structure are not always features of the underlying raw data. Although most researchers embark on their academic journey with the intention of adhering to good data management practices, as soon as they are faced with balancing data management against the other pressing demands of a deadline-driven research schedule, it drops in priority. It rarely takes long before finding and organising files becomes a dreaded digital chore.
A Helping Hand
University of Cambridge Data Champion, Annemarie Hildegard Eckes-Shephard, is currently undertaking a PhD in Biogeography. Her doctoral research focuses on developing a mechanistic growth model to determine how trees respond to climate change, and this research experience — together with her previous role as a crop database curator — has made Annemarie familiar with large datasets and well-equipped with tips and tricks to help others.
Annemarie understands the many challenges of managing research data and identifies time as a major constraint: ‘Researchers are often too busy to allocate time for organising their digital files, yet if they could only prioritise this task, it promises to save time and frustration in the long-term.’ Annemarie highlights other barriers to proper data management as ‘a general lack of motivation to structure data or insufficient training on the topic’: researchers simply don’t know how or where to start organising their data.
A ‘B.Y.O.D.’ Invitation
As an empathetic PhD student, Annemarie wanted to share her knowledge about best practice with her colleagues within the Department of Geography. She therefore started ‘Bring Your Own Data’ (B.Y.O.D.), a project part-funded by Jisc,1 which brought researchers together for monthly workshops on how to organise their data to improve the quality of their research. Each two-hour workshop began with a short introductory talk delivered by Annemarie to teach important aspects of data management, including:
file-naming conventions; writing ‘README’ files (messages to future self);structuring files and folders; using a data audit framework2 to help researchers think about their data management.As the name implies, B.Y.O.D. encouraged participants to bring their own laptops and start organising their data in an interactive and inclusive environment. Annemarie hoped that working in a group would facilitate collaboration and networking whilst inspiring individuals to work towards open science using good data management practices. She also believed that ‘making an official event in their calendar and therefore setting time aside would help researchers overcome the perception of not having enough time for data management.’
Fig. 3.1 The ‘Bring Your Own Data’ workshop is underway at the University of Cambridge. © Annemarie Eckes-Shephard, CC BY 4.0.
Feedback for Future Learning
Participants were asked to complete a short survey before and after each workshop to provide information about their aims and objectives for the session and how they were planning to achieve them, and to provide feedback with suggestions for how future workshops could be improved.
While B.Y.O.D. was well-received by all the participants, Annemarie admits that over time it became difficult to encourage people to attend the event, and that more support would have been required to publicise future workshops. Perhaps the use of promotional materials (for example, posters and flyers) would have increased visibility to a wider audience. Nevertheless, B.Y.O.D. is a shining example of how an individual effort can generate a demonstrable impact and drive cultural change within a research community.
3.2. Introducing Data Management into Existing Courses at the University of Minnesota
Author: Yan Wang
Contributor: Alicia Hofelich Mohr, Jenny McBurney
© Wang, Hofelich Mohr and McBurney, CC BY 4.0 https://doi.org/10.11647/OBP.0185.07
To provide more discipline-relevant support, the University of Minnesota RDM team contacts staff who are teaching graduate research methods, and works with them to embed suitable RDM training in their courses.
Table 3.2, CC BY 4.0.
From Grassroots to Widespread Influence
Back in 2015, two recent PhD graduates working at the University of Minnesota (UMN) contacted every instructor of graduate research methods in social science, and proposed integrating disciplinary Research Data Management (RDM) education into their courses. It was a bold proposal, but since then this disciplinary RDM training has grown from its small-scale, grassroots beginnings, becoming integrated into 60 courses across 7 colleges.
Alicia Hofelich Mohr, one of these two PhD graduates, is currently a library collaborator at the College of Liberal Arts. These collaborators are disciplinary experts based at their domain-specific college, and their job is to work closely with the RDM colleagues from the library to jointly provide general and domain-specific research support, including training, to all faculty members.
The University of Minnesota has a strong culture of good RDM. This is partly thanks to its early adoption of RDM support; since 2010, the RDM team has grown from around 10 staff members to more than 25, and includes librarians and collaborators from different colleges.
Being embedded in regular research methods courses, the RDM training usually lasts between 60 to 90 minutes with a class size of five to 20 students. All courses start with the same basic RDM principles: file-naming and file organisation; data sharing; archiving; and security issues. Additional subjects are introduced depending on the discipline.
A Lightweight Approach Makes for an Excellent Return on Investment
If you want to introduce elements of RDM training to existing courses within your institution, Alicia suggests you can ‘find a few motivated people and that is really all you need to start. When you are a small team, you can do things quickly’. Their lightweight approach does not cost much but makes an excellent return on investment, and the disciplinary elements of the training clearly demonstrate the relevance of RDM to the attendees.
