“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015, conference organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015

1. Die ZBW ist Mitglied der Leibniz-Gemeinschaft.
Research Data in Economics
Open Research Data: Implications for Science and Society
Warsaw, 28./29 May 2015
Ralf Toepfer
ZBW Leibniz Information Centre for Economics (Kiel / Hamburg)
Contact: r.toepfer@zbw.eu
Photo: Lukas Roth
Photo: Sönke Wurr, Münchow-Industrie-Fotos

2. 2
Agenda
 What is research data in economics?
 Data Sharing
 Incentives
 Discussion
Picture: “share-computer-key-260” by Emilio
Quintana on flickr.com. License: CC BY-NC-SA 2.0

3. 3
Sources for Reseach Data in Economics
Statistical Data Survey Data Data from
administrative
authorities
„Business“ data
National Statistical
Agencies
EU-LFS (European
Union Labour Force
Survey)
Public administration Stock price
International Statistical
Agencies (Eurostat,…)
SHARE (Survey of
Health, Ageing and
Retirement in Europe)
Labour bureau Financial statement
data
International
Organizations (OECD,
Worldbank, WTO,…)
Surveys run by
researchers
Tax authority Commercial
databases (Thomson
Reuters
Datastream,…)

4. 4
Macro- and micro-data
• Macrodata
 aggregated data (non-sensitive)
 often freely available at the internet
• Microdata
 Data about people, households, firms
 Not or only slightly/low anonymized
 Restricted/controlled access
 Specific workplaces for guest scientists (on-site)
 Controlled remote data processing/access

5. 5
Open Economics Principles
 Research Data in Economics should be open by default…
 …but we must accept that in some cases for reasons of privacy
and/or confidentiality the data cannot be made openly available…
 …in such cases researchers should share analysis under the least
restrictive terms consistent with legal requirements….
 …and this should include opening up non-sensitive data, summary
data, metadata and code
Open Economics Principles
[http://openeconomics.net/principles]

6. 6
Data Sharing in Economics
„The status quo in empirical research in economics and management is not to
share data.“ (Andreoli-Versbach, Mueller-Langer 2014, p.11)
(N=488) Do not share
data
Sporadically
share data
Share data
regulary
Responses 394 82 12
Percent 80.74% 16.8% 2.46%
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy
(2014), http://dx.doi.org/j.respol.2014.04.008

7. 7
Opinions on Data Sharing
On a scale from 1 to 5;
1=„Strongly disagree“ –
5=„Agree completely“
Strongly
Disagree
2 3 4 Agree
Completely
Researchers should
generally publish their data
(N=1491)
1,95% 5,9% 16,57% 31,32% 44,27%
Freely available research
data is a great contribution
to scientific progress
(N=1449)
1,73% 3,8% 11,32% 25,05% 58,11%
It is common in my
discipline / research
community to share data
(N=1436)
13,86% 23,33% 27,37% 24,44% 11%
Benedikt Fecher, Sascha Friesike, Marcel Hebing, Stephanie Linek, Armin Sauermann: A Reputation Economy: Results
from an Empirical Survey on Academic Data Sharing, Berlin and Kiel, February 2015, RatSWD Working Paper 246

8. 8
Modes of Sharing
• Private mangement: sharing data with colleagues within a research group
• Collaborative sharing: using data within a consortium
• Peer exchange: sharing data with trusted peers in informal networks
• Transparent governance: sharing data with external parties such as funders
and institutions for accountability, research assessment, scrutiny or inspection
• Community sharing: with members of a research community
• Public sharing: making data available to any member of the public
“…most researchers would make data available if they could decide on the
scope and modalities of the data reuse: who can access what kind of data how
and when.” (Fecher et al.)
Van den Eynden, V. and Bishop, L. (2014). Incentives and motivations for sharing research data, a researchers perspective.
[knowledge-exchange.info/Default.aspx?ID=733

9. 9
Sum up
 Researcher's widely agree that it is beneficial for scientific progress to share
data…
 …and most researcher‘s agree that other researcher should publish their data…
 …but only a minority share their data publicly
 Discrepancy between the expected benefit for scientific progress and the
individual researcher‘s behaviour
„…academia is a reputation economy, an exchange system that is driven
by individual reputation beyond money and status. In this regard, data
sharing will only see widespread adoption among research professionals
if it pays in the form of reputation.“ (Fecher et al. p.3)

10. 10
Incentives
• Appropriate reward structures for providing and documenting data and code
should be promoted (Fecher et al.)
• Provide easy and ready to use technical infrastructure (Fejen, Tenopir et al.)
 e.g., standardised data citation (DataCite DOIs)
 Support the establishment of data journals (Andreoli-Versbach, Mueller-
Langer)
 Repositories for research data (http://www.re3data.org)
• Intrinsic motivation (Osterloh, Frey)
„The core impediment to making data available is the lack of formal recognition of this task.“ (Fecher,
Friesike, Hebing, Linek, Sauermann 2015, p.13)

11. Seite 11
Trust & Credibility
 Dewald et al. (1986) attempted to replicate 54 papers published in the Journal of
Money, Credit and Banking and could replicate only two
 McCullogh et al. (2006) tried to replicate 69 articles published in the same journal
and could only replicate 14
 McCullogh et al. (2008) attempted to replicate 117 articles published in the
Federal Reserve Bank of St. Louis Review and could only replicate 9
“Despite claims that economics is a science, no applied economics journal
can demonstrate that the results published in its pages are replicable, i.e.,
that there exist data and code that can reproduce the published results.”
(Mc Cullough et al. p. 1093)
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy (2014), p.2
http://dx.doi.org/j.respol.2014.04.008

12. 12
Discussion
„Fifty Shades of No“ [Screenshot from http://philarcher.org/diary/2015/50shadesofno/]

13. Literature
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy (2014),
http://dx.doi.org/j.respol.2014.04.008
Benedikt Fecher, Sascha Friesike, Marcel Hebing, Stephanie Linek, Armin Sauermann: A Reputation Economy: Results from
an Empirical Survey on Academic Data Sharing, Berlin and Kiel, February 2015, RatSWD Working Paper 246.
http://www.ratswd.de/dl/RatSWD_WP_246.pdf
McCullough, B.D. / McGeary, Kerry Anne / Harrison, Teresa D.: Lessons from the JMCB Archive. Journal of Money, Credit,
and Banking, vol. 38, No.4(2006),pp. 1093-1107
Van den Eynden, V. and Bishop, L. (2014). Incentives and motivations for sharing research data, a researchers perspective.
[knowledge-exchange.info/Default.aspx?ID=733]
Michael A. Clemens: The Meaning of Failed Replications: A Review and Proposal. IZA DP No. 9000.
http://ftp.iza.org/dp9000.pdf
Fejen: What researchers want . A literature study of researchers‘ requirements with respect to storage and access to
research data. Stichting SURF. February 2011.
http://www.surf.nl/binaries/content/assets/surf/en/knowledgebase/2011/What_researchers_want.pdf
Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., Manoff, M. & Frame, M. (2011). Data Sharing by
Scientists: Practices and Perceptions. PLoS One, 6(6), e21101. http://doi.org/10.1371/journal.pone.0021101
Christine L. Borgman. 2010. "Research Data: Who will share what, with whom, when, and why?" China-North America
Library Conference, Beijing. Available at: http://works.bepress.com/borgman/238
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