This document summarizes a presentation about building a research data infrastructure for educational studies in Germany. It discusses the experiences of the FDB project, which aims to create a coordinated infrastructure through a network of organizations. Currently, the research data infrastructure has some limitations, including a lack of coordination, insufficient capacities, and underrepresentation of certain data types. Moving forward, the infrastructure needs to further coordinate its services, expand its capacities, and ensure long-term sustainability to fully support open educational data. The FDB project aims to address these challenges through its collaborative efforts.

1. Open Science Conference
Berlin 21.-22. März 2017
Building a research data infrastructure
for educational studies in Germany
- Experiences of the FDB-project
Alexia Meyermann, DIPF

2. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Open Educational Data
Why not accomplished yet?
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3. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Experiences of the German Network for
Educational Data („FDB-Project“)
Researchers of
the funding
programme
„EBF-
programme“
Part of the Data Infrastructure
- approx. 300 projects*
- approx. 200 data sets*
- 144 projects documented (09/2016)
- 46 data sets shared (09/2016)
* figures are estimated because of missing responses
sharing
2013-2016:
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4. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Experiences of the German Network for
Educational Data („FDB-Project“)
Researchers of
the funding
programme
„EBF-
programme“
Part of the Data Infrastructure
- approx. 300 projects*
- approx. 200 data sets*
- 144 projects documented (09/2016)
- 46 data sets shared (09/2016)
* figures are estimated because of missing responses
sharing
2013-2016:
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5. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Open Educational Data
Why not accomplished yet?
 an educational researchers‘ task: motivation, capabilities
 Motivation
• obligations to share (e.g. monitoring and evaluation systems, journal
requirements, funding requirements)
• incentives to share (e.g. data publications, citation rate)
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 Capabilities
• resources (time, money, personnel)
• skills (research data management)
 Some measures have already been taken by various stakeholders
 funding requirements and opportunities, citation and data journals
 FDB-project offers data management training, info material, counseling

6. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Open Educational Data
Why not accomplished yet?
 an educational researchers‘ task: motivation, capabilities
 a research data infrastucture‘s task
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7. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Open Educational Data
Why not accomplished yet?
 an educational researchers‘ task: motivation, capabilities
 a research data infrastucture‘s task
How should a research data infrastructure
for educational studies look like?
How to address
the specific needs of educational studies?
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8. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Educational Studies
Characteristics and Needs
Sociology,
economy,
psychology,
…
Data types,
methods,
terminology
High data
output
Sensitive data;
subject to approval
by local authorities
specialized services sufficient capacities
Educational research
Requirements on
data infrastructure
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multidisciplinary heterogeneous productive
complex legal and
regulatory environment

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 subject-specific,
institutional data
centers
 focus: Large-Scale-
Surveys; In-House-
Data
 small scale studies,
qualitative data
underrepresented
 diversified services,
complexity
Data Infrastructure for social, behavioural and
economic sciences in Germany*
Characteristics
* accredited by the German Data Form, www.ratswd.de, plus GESIS und Qualiservice

10. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Data Infrastructure
Needs addressed?
multidisciplinary heterogeneous productive
complex legal and
regulatory environment
+ subject-specific, high-level
services guaranteed
+ high and increasing number
of data centers
- complexity: no joint point of
access, no joint overview of
services and data
- capacities not sufficient, not
adequate: certain data types
are underrepresented
specialized services sufficient capacities
Educational research
Requirements
Infrastructure
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11. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Data Infrastructure
Needs addressed?
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multidisciplinary heterogeneous productive
complex legal and
regulatory environment
specialized services sufficient capacities
Educational research
Requirements
Infrastructure
+ subject-specific, high-level
services guaranteed
+ high and increasing number
of data centers
- complexity: no joint point of
access, no joint overview of
services and data
- capacities not sufficient, not
adequate: certain data types
are underrepresented

12. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Data Infrastructure
Need for action: coordination
 joint point of access and overview to reduce complexity and enhance
user-friendliness
 diversified services need to cooperate and need to be coordinated
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13. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Researchers
deposit find
Qualitative data
DIPF
Survey data
GESIS
Assessment data
IQB
reuse
www.forschungsdaten-bildung.de
FDB-project (German Network for Educational Data):
Building a joint service
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1st funding period 2013-2016

14. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Data Infrastucture
Need for action: coordination
 joint point of access and overview to reduce complexity and enhance
user-friendliness
 diversified services need to cooperate and to be coordinated
Coordinated infrastructure in the FDB-project:
 network architecture (technical, organizational, legal): roles and
responsibilities, shared software tool
 common metadata set (harmonization)
 common standards of data curation
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15. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Data Infrastucture
Need for action: expansion
 build Sufficient and adequate capacities
 adequate services for data types so far underrepresented (qualitative
data, small scale studies data, etc.)
 services for „local data“: institutional repositories at universities and
research organizations
 low-threshold services
 coordination
 selection and appraisal of data
 service level models
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added value service
?

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Open Educational Data
Why not accomplished yet?

17. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Open Educational Data
Why not accomplished yet?
 two pillars of open education data: Science and RDI
 educational researcher‘s tasks: motivation and capabilities
 data infrastructure‘s tasks: specialized services, joint and coordinated
services, sufficient capacities
 Future challenges:
- How to stimulate data reuse? Qualitative data ? -> Data quality
- How to deal with the growing number of data?-> Selection and appraisal
- How to build reliable services? -> Sustainability, long-term perspective,
professionalization of data curation activities
- and many more…
 Collaborative efforts needed!
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18. forschungsdaten-bildung.de // Open Science Conference // Berlin, 21.-22. März 2017
Forschungsdaten Bildung – German Network for Educational Data
• Team DIPF: Doris Bambey, Alexia Meyermann, Maike Porzelt, Thomas
Schwager
• Team IQB: Malte Jansen, Claudia Neuendorf, Lisa Pegelow
• Team GESIS: Reiner Mauer, Marcus Eisentraut, Karoline Harzenetter
web: www.forschungsdaten-bildung.de
E-Mail: verbund@forschungsdaten-bildung.de
Phone: + 49 (69) 24708 - 311
Thank you for your attention !
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