The document discusses challenges trainers may face when training researchers on data management planning and potential strategies to address these challenges. It identifies six common challenges: 1) researchers not understanding the need for data management planning, 2) researchers being unfamiliar with the concept of research data, 3) researchers not knowing how to describe their data, 4) researchers not thinking ethics and legal compliance applies to their work, 5) the complexity of data privacy and GDPR topics, and 6) researchers not understanding documentation and metadata. The document provides examples and explanations to help trainers overcome these challenges and motivate researchers on the importance of data management planning and its components.

1. 10/5/20
Data management
planning
Training for trainers
5.10.2020
Mari Elisa Kuusniemi
ORCID: 0000-0002-7675-287X
Tuuli Office

2. 310/5/20
Tuuli
Promotes data management planning
as an important part of good research
practice
Provides
• Tuuli Office: National coordination
for DMP requirements and
guidance
• DMPTuuli: Data management
planning tool
Funded by Ministry of Education and
Culture, Finland

3. 510/5/20
Research
Data
Management
(RDM) is a term that
describes the organisation,
storage, preservation, and
sharing of data collected and
used in a research project.

4. RESEARCH
PUBLICATION
RESEARCH
PLANNING
RESEARCH
PROPOSAL
RESEARCH
SETUP
RESEARCH
CONDUCT
RESEARCH
IMPACT
Research
Life Cycle
Modified version from graph created by UH Data Support
Original licence: CC BY
Good data management practice, oils the weels of research

5. 8810/5/20
Main requirements for a trainer
• You understand importance of research data management.
• You like to find ways to motivate researchers.
• You can search practical solutions with researchers (not
necessarily for them).

6. 910/5/20
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
I have not trained
research data
management
a couple of times many times
I have trained research data management... (N=34)

7. 121210/5/20
During the training
• We go through main challenges when training data
management planning
• We try to find examples how to overcome these challenges

8. 1410/5/20
Data
Management
Plan
(DMP) is a document that
outlines how data are to be
or is handled both during a
research project,
and after the project is
completed.

9. 1610/5/20
Challenge 1
Your course participants do not
understand the need of data
management planning

10. 181810/5/20
Why manage your research data and write
a data management plan (DMP)?
• It is good research practice!
• It helps you save time and money.
• You will reduce the risk of losing your data.
• You will be able to anticipate complex ownership and user
rights issues in advance.
• It helps you support open access to create productive future
collaborations.
• You will meet your funder’s requirements.
• Your DMP reflects your managerial skills as a project leader.

11. 202010/5/20
Topics of a Data Management Plan (DMP)
• General description of the data
• Ethical and legal compliance
• Documentation and metadata
• Storage and backup during the research project
• Opening, publishing and archiving the data after the
research project
• Data management responsibilities and resources
Reference: Tuuli-project. (2020, January 24). General Finnish DMP guidance (Version 2020).
Zenodo. http://doi.org/10.5281/zenodo.3630309

12. 2210/5/20
General
description of
the data
Identify the data of your
research project

13. 242410/5/20
General description of the data
• What kinds of data is your research based on?
• What data will be collected, produced or reused?
• What file formats will the data be in?
• Give a rough estimate of the size of the data
produced/collected.
• How will the consistency and quality of data be
controlled?

14. 2610/5/20
Challenge 2
Your course participants are not
used to describe the data they
use, collect or produce
They are not familiar with the
concept “research data”
Tekijä

15. 282810/5/20
What is research data?
“…any information that has been collected,
observed, generated or created to validate original
research findings.”
"...materials generated or collected during the course
of conducting research..."
“Although usually digital, research data also includes
non-digital formats such as, photos, diaries and
(laboratory) notebooks.”

16. 303010/5/20
In the DMP data is quite often understood
as a broad term including
• data collected by various methods (such as
surveys, interviews, measurements, imaging
techniques etc.),
• data produced during the research (such as
analysis results),
• research sources (such as archive material), and
• source code and software.

17. 3210/5/20
Challenge 3
Your course participants are not
used to describe the data they
use, collect or produce
They don’t know how to phrase
description of the data or how
write it down
Tekijä

19. 3510/5/20
Ethical and legal
compliance
Make sure you have
right to use data

20. 373710/5/20
Ethical and legal compliance
• What legal issues are related to your data
management? (For example, GDPR and other
legislation affecting data processing.)
• How will you manage the rights of the data you use,
produce and share?

21. 3910/5/20
Challenge 4
Your course participants do not
think ethics and legal compliance
concerns them because they do
not use sensitive data
They don’t see the need of
agreements about data rights

22. 414110/5/20
Legal issues can be…
• You collect information about persons => GDPR
• Your collect information about animals => GDPR
• You use material like literary, artistic, dramatic or
musical work, sound recording, film or broadcast =>
copyright law
• Your data will be part of commercial invention =>
copyright law, patent law
• Etc.

23. 424210/5/20
Agreement needs to done…
• When you use data collected/created by others
• You collect/produce data, which will be used by others
• You collect/produce data together with others
• You share data to other projects/organisations/…
• You preserve your data to a data archive or repository
• With funder and organisation (funders often require
transfer of right to organisation)
• Etc.

24. Worst-case scenarios
• You used material under copyright or produced in other project
without asking permission => your research results can’t be
published.
• You did not agree about using data collected and how to
publish based on data => your supervisor published paper
based on data you collected and you name is not in the
publication
• You did not agree about using data collected => you colleague
took all data with her, when she left to Canada.
• No-one signed a confidentiality agreement => one person from
the team told about bad data management to the press and
your reputation as researher is ruined.

25. 4410/5/20
Challenge 5
Data privacy, protection & GDPR
are huge topics! You can’t cover
all on a data management
planning training.
Ask help from a data protection
officer of your institution.

26. 4510/5/20
Documentation
and metadata
Your data needs to be
understandable
to yourself and reviewers

27. Documentation and metadata
• How will you document your data in order to make the data
findable, accessible, interoperable and re-usable for you and
others?
• What kind of metadata standards, README files or other
documentation will you use to help others to understand and
use your data?

28. 4710/5/20
Challenge 6
Your course participants do not
understand the concepts of data
documentation or metadata
Therefore they struggle to see the
importance of metadata and value
of data documentation for
themselves and others

29. 484810/5/20
Data documentation is an important skill
• Data documentation is part of good research
methodology
• Data documentation starts from the very beginning
of the projects and ends after the project.
• There are tools and techniques available
• discipline specific
• data type specific
• Good documentation procedures produce rich
metadata with minimum workload.

30. https://www.ukdataservice.ac.uk/manage-data/document.aspx

31. https://doi.org/10.5281/zenodo.1683181

32. FAIR is the ultimate goal of data documentation
FAIR is a set of guiding principles to make data
Findable
Accessible
Interoperable
Re-usable
Force11: https://www.force11.org/group/fairgroup/fairprinciples
Machine readable and
understandable

33. 10/5/20
Be Prepared
Scout motto

34. Challenge 1
Your course participants do not understand the
need of data management planning
Challenge 2
Your course participants are not familiar with
the concept “research data”
Challenge 3
Your course participants don’t know how to
phrase description of the data or how to write it
down
Challenge 5
Data privacy, protection & GDPR are huge
topics! You can’t cover all on a data
management planning training.
Challenge 4
Your course participants do not think ethics and
legal compliance concerns them.
They can’t see the need of agreements (about
data rights, etc.)
Challenge 6
Your course participants do not see the
importance of data documentation & metadata
for themselves and others

35. 575710/5/20
Poll
Which of the challenges is the most difficult for you to
overcome?
Tekijä

36. 585810/5/20
Group work
• Random small groups in breakout rooms (click to join the
group)
• Working time: 15 min
Tekijä

37. 595910/5/20
Task: How can you as a trainer be
prepared for this challenge?
• One challenge/group.
• Your group number tells the challenge number you work with
(you see the number when you join the group)
• Write the answer to the google doc:
http://bit.ly/DMPtrainercallenges
• Each group will present the findings to all, after the group
work
Tekijä

38. 10/5/20 60

39. 6110/5/20
Thanks!
Mari Elisa ”Mek” Kuusniemi
mari.elisa.kuusniemi@helsinki.fi