The format for the data management plans for PhD students at Wagenigen UR explained. This format was developed by the library in cooperation with the Wageningen Graduate Schools.

1. Data management plan format
Wouter Gerritsma, Wageningen UR Library

2. Data management plan
 A data management plan is a formal document you
develop at the start of your research project which
outlines all aspects of your data (i.e., what you will do
with your data during and after your research project).
 Data management plan is not a static document, but
needs adjustment at regular intervals

3. Data management policies
 Currently there are not many funder requirements for
data management in the Netherlands.
 Data management policies are discussed by NWO and EC
● NWO is on the brink to implement DM policies
 Data management policies become mandatory for PhD's
of Wageningen Graduate Schools per 04/2014

4. WGS format for a Data Management Plan
 Format consists of 9 questions
(http://www.wageningenur.nl/library/dmp)
 The template assists you to go trough all these questions
with explanation
 Questions are illustrated with example from Lucy
Vermeulen (PhD cadidate, ESA)

5. 1. Organizational Context
 A data management belongs to a researcher, part of a
group, and should have a file name to identify it on you
computer.

6. 1. Organizational Context
 A data management belongs to a researcher, part of a
group, and should have a file name to identify it on you
computer.

7. 2. Give a short description of your work
 There is no need to repeat what is in you research plan,
but a short description to give some context to the
reader is sufficient.
 Give two or three lines to explain what is not obvious
from the title

8. Short description of your research
 Give two or three lines to explain what is not obvious
from the title

9. 3. Define data management roles
 Who has control over the data, what is the role of your
supervisor? Who owns the data? Is there a person in the
research group with a specific responsibility for data
analysis and management?

10. 3. Define data management roles
 Who has control over the data, what is the role of your
supervisor? Who owns the data? Is there a person in the
research group with a specific responsibility for data
analysis and management?

11. 4. Give an overview of expected type of
research data, software choices, data size
& growth
 Identifying your possible research data before you
actually start collecting those data, makes sure no
research output is overlooked.

14. 5. Short term storage solutions

15. 5. Short term storage solutions

16. 5. Short term storage solutions

17. 6. Structuring your data and information

18. 7. Documentation and metadata
 Describe how you are going to document your data
collection process, what the resulting data files comprise
and how they will be processed further. Think about
documenting the:
1. content (what does your dataset contain?)
2. context (who, what, why, where and how will the
data be collected and analysed)
3. process (are there specific processes and does it
make sense to organise notes by process?)

19. 7. Documentation and metadata
 Describe how you are going to document your data
collection process, what the resulting data files comprise
and how they will be processed further. Think about
documenting the:
1. content (what does your dataset contain?)
2. context (who, what, why, where and how will the
data be collected and analysed)
3. process (are there specific processes and does it
make sense to organise notes by process?)

20. 8. Sharing and ownership
 Do you expect that others may be interested to re-use
you data, and do you have plans to share it with them?
 How are you going to make sure your data files will be
accessible once you leave the department?
 Are there specific funder’s requirements to share you
data, or to impose an embargo?
 If other parties (outside your group or outside
Wageningen UR) are involved in this research, are there
agreements how the data will be used and shared?
 Are there privacy or security issues, and if there are,
how are you dealing with them?

21. 8. Sharing and ownership
 Do you expect that others may be interested to re-use
you data, and do you have plans to share it with them?
 How are you going to make sure your data files will be
accessible once you leave the department?
 Are there specific funder’s requirements to share you
data, or to impose an embargo?
 If other parties (outside your group or outside
Wageningen UR) are involved in this research, are there
agreements how the data will be used and shared?
 Are there privacy or security issues, and if there are,
how are you dealing with them?

22. 9. Long term storage
 Which part of your research data has value for long term
storage?
 Do you intend to preserve these data for the long term?
 If not, argue why.
 Is there a common practice in your field or do you intend
to use the services provided by Wageningen UR?

23. 9. Long term storage
 Which part of your research data has value for long term
storage?
 Do you intend to preserve these data for the long term?
 If not, argue why.
 Is there a common practice in your field or do you intend
to use the services provided by Wageningen UR?

24. Examples of long term storage
 http://library.wur.nl/WebQuery/wurpubs?A170=dat

29. Thank you!
Courtesy to Lucy Vermeulen who
allowed us to share parts of her
DMP
The input of Marina Noordegraaf
@insearch4data and Hugo
Besemer is acknowledged
On the Web:
@wowter
wowter.net
http://www.slideshare.net/wowter