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5.3 SowiDataNet – A User-Driven Repository for Data Sharing and Centralising Research Data from the Social and Economic Sciences in Germany

Authors: Linne, Monika;

5.3 SowiDataNet – A User-Driven Repository for Data Sharing and Centralising Research Data from the Social and Economic Sciences in Germany

Abstract

Using digital repositories to manage and publish scientific research is well established and increasingly accepted within scholarly communities. This is not the case for research data from the social and economic sciences in Germany, since scholars from these scientific areas most of the time restrict their research data from being published and reused. German researchers and organisations produce big amounts of data, but all too often do not document, archive or publish it. This issue is opposed to the fact that flexible data distribution and the reuse of research data are becoming increasingly relevant in the social sciences. For this reason, the Leibniz Institute for the Social Sciences in collaboration with the Social Science Centre Berlin, the German Institute for Economic Research, and the German National Library of Economics, started the development of a new data repository: SowiDataNet. SowiDataNet intends to reduce the reluctance in data sharing and to help establish a data sharing mentality in Germany. The disclosure of researchers’ concerns about data sharing is of great help in this matter, and so SowiDataNet is community driven. This requires close co-operation with all stakeholders. For this reason, a comprehensive requirements analysis has been conducted, which included expert interviews, literature reviews and a workshop addressing all stakeholders. At present, a well advanced prototype is being adjusted on the basis of user tests carried out by a heterogeneous group of scholars from different research institutions. The main focus of SowiDataNet is based upon quantitative data from the social and economic sciences and, as such, on two specifically empirically oriented scientific disciplines. The core of this network will be a web-based, independent infrastructure that allows for low-threshold archiving, standardised documentation and distribution of research data. To ensure high data quality as well as data protection, all submitted data will be reviewed by a data curator on the basis of a criteria catalogue. Centralising research data from different scientific organisations and individual researchers is another aim of SowiDataNet. Currently, holding of research data in Germany is heavily fragmented, which precludes a user-friendly, centralised and, therefore, quick data retrieval. Research data is either held by individual scholars, research data centres or by institutions – in a more or less standardised form, all too often neither visible nor available for the academic community. Consequently, a broad overview of previously conducted research cannot be obtained. Due to this major hurdle, data reuse by other scholars underlies extremely high levels of complexity and effort, or in the worst – but not very uncommon – case is simply impossible. Resolving this unsatisfactory situation is an aim of SowiDataNet, which will integrate decentralised research data together within one repository network. Monika Linne is a member of the ‘Archive Instruments and Metadata Standards’ team at GESIS, Data Archive for Social Sciences, Leibniz Institute for the Social Sciences. After her studies in sociology, she worked for the Federal Centre for Health Education of Germany in the field of health databases. Following this, she was employed as a Scientific Project Manager for media analysis at Unicepta in Cologne. Since 2010 she has been employed as a scientific associate at GESIS. She is also conducting social network analyses on team work for her dissertation.

Keywords

research, digital, data, Germany

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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