How to write a Data Management 
Plan
A FOSTER-CESSDA Workshop 
November 5, 2015
GESIS Data Archive for the Social Sciences, 
Cologne, Germany
This work is licensed under  Creative Commons Namensnennung 4.0 International Lizenz.
Introduction
What is FOSTER?
• Facilitating Open Science Training for 
European Research
• 2 year project with the objective to 
– set in place sustainable mechanisms for EU researchers to 
foster open science in their daily workflow
– support researchers optimizing their research visibility and 
impact, 
– support the adoption of EU open access policies in line with 
the EU objectives on Responsible Research & Innovation 
• Information and resources: 
http://www.fosteropenscience.eu  
What is CESSDA?
• Consortium of European Social Science Data 
Archives
Austria
Czech Republic
Denmark
Finland
France
Germany
Greece
Lithuania
Netherlands
Norway
Slovenia
Sweden
Switzerland
United Kingdom
• a pan-European Research Infrastructure
– providing large scale, 
integrated and sustainable 
data services 
– supporting research and co-
operation in areas expected 
to be of great importance 
What is CESSDA Training?
• We provide resources, training and consulting in 
Research Data Management and Digital Preservation
• Hosted by the GESIS Data Archive for the Social 
Sciences 
• Get in touch:
– visit our webpage: http://cessda.net/CESSDA-Training 
– follow us on Twitter: @CESSDA_Data 
– visit our blog: http://www.cessdatraining.wordpress.com 
– join our workshops
Who are we?
• …Astrid Recker 
expert in data sharing and 
digital preservation
• …Sebastian Netscher
investigating research 
data management
• …and today‘s special guest
Libby Bishop (UK Data Archive)
Image by See-ming Lee  (CC-by-sa)
Outline of the Workshop
How to Write a Data Management Plan
09.00-10.30 Introduction (Astrid)
10.45-12.30 Data Handling: Data Documentation, Management and Storage (Sebastian)
12.30-13.30 Lunch break
13.30-15.15 Research Ethics and Legal Compliance (Libby & Sebastian)
15.30-16.30 Data Sharing: Long-term Preservation and Archiving (Astrid)
16.30-17.00 Wrap-Up (Libby, Astrid & Sebastian)
Round of introductions
Image: pixabay (CC-0)
… who a
re you???
… why are you here???
… what’s your research about???
’
???
And…
Research Data 
Management
Research
Study 
planning
Data 
collectionData analysis
Archiving & 
registering
What is Research Data Management?
Im
ag
e: 
CC
-0
RDM is like data health care – for happier, 
healthier data 
What is Research Data Management?
• All strategies, processes, and measures to 
maintain
– Data quality
– Interpetability of research results
– (Re-)Usability of research data
– Specifically addresses legal and ethical issues 
(e.g. informed consent, ownership, licensing)
RDM and the Data Lifecycle
• Encompasses the entire research data life 
cycle
• Entails strategies to 
– process and validate
– store and protect
– document and describe
– preserve and share data
Research
Study 
planning
Data 
collectionData analysis
Archiving & 
registering
S t r a t e g i e s  a n d  Meas u r e st r t i   r
Data collection 
(which data, how?)
Ethical aspects 
(informed consent)
Documentation and 
metadata
Data security and 
backup
Selecting data for 
long-term 
preservation 
Legal aspects (data 
protection, intellectual 
property rights)
Respon s i b i l i t i e s  a n d  Re s o u r c e si i l i t i   r
Areas of Research Data Management
1. Quality assurance
Create readable, 
authentic data; prevent 
data loss
2. Replicability
Guarantee that results 
can be understood and 
reproduced; 
demonstrate validity of 
results
3. Re-usability
Enable re-use of data in 
new contexts and to 
answer new research 
questions
Image: cc0
Objectives of Research Data Management
RDM may be required by
• Your institute, e.g. by your working contract 
or project agreements
• Funding agencies, e.g. to ensure 
reusability 
• Journals, claiming your data 
before publishing your article
• Your supervisor…
=> check for such conditions Image by A. Herrema (CC-by)
Data Management 
Planning
Research
Study 
planning
Data 
collectionData analysis
Archiving & 
registering
The Data Management Plan (DMP)
• A DMP is a systematic documentation of 
RDM
• defines strategies, measures and 
responsibilities for
– processing and validating
– storing and protecting 
– preserving and sharing your data
• throughout the data lifecycle Image: pixabay (CC-0)
How to write a DMP
• A DMP uniquely relates to your 
research project
– start right at the beginning 
of your research project
– document what you did and why
– frequently up-date and adapt it
– A DMP is not just a plan, it is 
the implementation of a 
(research) plan Image by P. Hochstenbach  (CC-by)
How do I get started?
– Rely on the data lifecycle
– Various online templates and tools, e.g.
– DCC. (2013): Checklist for a Data Management 
Plan. 
http://www.dcc.ac.uk/sites/default/files/doc
uments/resource/DMP/DMP_Checklist_2013.pdf
– Tools: DMPTool (https://dmptool.org/) or DMP 
Online (https://dmponline.dcc.ac.uk) 
– Use the template provided in this workshop
A first look at the DMP
• Have a look at the DMP template in your folder 
• Familiarize yourself with its sections and 
subsections
• Consider …
…parts you would be able to fill 
in off the top of your head
…parts you would have to look for 
further information
…obstacles or problems you 
encountered in the past 
 individual work   -  time: about 15 minutes
Im
ag
e: 
pix
ab
ay
 (C
C-
0)
The Structure of the DMP Template
• Consists of seven parts
– Cover page and general information on the project
– Six sections (with subsections):
• data collection 
• documentation and metadata   session 2
• storage, organization and security  session 2
• ethics, legal compliance 
and Intellectual Property Rights  session 3
• preservation and sharing   session 4
• responsibilities and resources  
Further Reading
• CESSDA (2015): CESSDA User Guide RDM. 
http://cessda.net/CESSDA-Training/Research-Data-Management. 
• Corti, L., van den Eynden, V., Bishop, L. & Woollard, M. (2014): 
Managing and Sharing Research Data. A Guide to Good Practice. 
London: Sage Publication Ltd.
• DANS (2010): Preparing Data For Sharing. Guide to Social Science Data 
Archiving. DANS Data Guide 8. The Hague: Royal Netherlands Academy 
of Art and Sciences & Netherlands Organization for Scientific Research.
• Horton, L., van den Eynden, V., Corti, L. & Bishop, L. (2011): Data 
Management Recommendations for Research Centers and 
Programmes. Essex: UK Data Archive.
• Jones, S. (2011): How to Develop a Data Management and Sharing 
Plan. Glasgow: Digital Curation Centre (DCC).