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ORD_ResearchDataInEconomics

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Reserach Data in Economics

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ORD_ResearchDataInEconomics

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 12 Discussion „Fifty Shades of No“ [Screenshot from http://philarcher.org/diary/2015/50shadesofno/]
  13. 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 13

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