Suchergebnisse

In 2011 the University of Edinburgh became the first UK Higher Education Institution (HEI) to adopt a research data policy. As of late 2015, 20 per cent of UK HEIs now have a policy. Whereas recommendations exist on what should go into a policy, there is no analysis on what is going in policies. This paper compared the content of policies to see if a standard form and language is emerging.The paper will show the adoption of two approaches. The first is a 'general principles' approach. This policy is short, strong on the normative values for data re-use and preservation and general goals, but weak on policy detail and enforcement mechanisms. The other approach is a formal 'legalistic' style; it is longer, specific in requirements, strong on definitions but not necessarily clear in direction or easy for researchers to work with. Policies are tested for type of university (research intensive vs non-research intensive) and age (university cohort). They are compared across date of publication and if mention of institutional support is made. The paper looks at a requirement to write a data management plan and to whom the policy applies. Comparisons are also made on statements on ownership, retention and research ethics, and requirements on accessibility, open data, and costing data management. The paper also looks to see if the policy is subject to review. The results of this research fed into London School of Economics and Political Science's own draft research data policy and a summary of policies for the Digital Curation Center's website. Data underpinning this paper is available under a CC-BY license through the UK Data Service. Laurence Horton is Data Librarian at the London School of Economics and Political Science, where he is responsible for providing the School's Research Data Management support. He previously worked at GESIS – Leibniz Institute for the Social Sciences setting up CESSDA Training in RDM and digital preservation. He also worked at the UK Data Archive on a Jisc funded Research Data Management ...

Election studies present a research data management challenge due to the size and diversity of the data they collect in a concentrated period. We consider how data infrastructure can support election studies to ensure the data they produce is good quality reusable comparative data. Election studies are critical large-scale data investments. When fully realised, election studies provide an unparalleled spatial and temporal resource for studying social attitudes and political behaviour. They have contemporary value for researchers but also as long-term data investments with prospective comparison across time and in comparative cross-national analyses. However, election studies operate under circumstances exceptional to other long-term longitudinal or repeated cross-sectional studies. Elections may occur at irregular intervals or as sudden 'snap' elections. Consequently, studies may have a concentrated period to design and collect data. Here the risk is that data management concerns are relegated to irrelevant or secondary consideration under the pressure to produce publications, with the result that data is not comparable across either time or spatial units. We seek to ensure election studies produce well-documented data, collected in compliance to recognised data harmonisation standards by ensuring data management planning and metadata are incorporated and implemented in the design and execution of the research.

This paper explores how data archives provide a service facilitating the gap between legal data protection requirements and research practices. Researchers encounter legal frameworks concerning data protection in all phases of the data-lifecycle, but research practice - without due care - can clash with these frameworks. Social science archives can intervene, helping researchers navigate an environment which simultaneously pushes data sharing, and consideration of the individual's right to privacy. These aims are not mutually exclusive, but pressure on researchers to 'get it right' when collecting, storing, analyzing, and anoymizing data has never been greater. We examine how archives can intervene in stages of the data-lifecycle, against the context of German and British regulatory requirements. We propose that whilst differences exist in the substance of laws (e.g. Bundesdatenschutzgesetz and Data Protection Act), research cultures, and funding environments, archives face similar challeges in the data reuse/privacy dynamic. With research innovations such as geo-referenced data, and increasingly, cross-national collaborative projects exisiting either across national laws or outside established legal frameworks - the regulatory grounding is not firm. Here facilitiation becomes an act of setting best-practice standards as guidance and, we suggest, data archives are best suited to be guides.

Purposing your survey: archives as a market regulator, or how can archives connect supply and demand?

Publishing in top-ranking journals in the social sciences and international relations requires writing with clarity. Accurately described and transparent methods sections ensure high-quality academic writing. The methodology section of empirical papers should explain the exact steps taken by the authors when operationalizing concepts and testing hypotheses to facilitate replication. This also allows for monitoring quality, challenging findings, and promoting good scientific practices. The quality of methodology sections is the result of the interaction between academic cultures of data sharing, effective application of rules, and good-quality research data management (RDM). This article evaluates the impact of standards on replicability. We present an empirical analysis of a set of sixty-six articles published during the period 1984-2013 that use data from all waves of the European Values Survey. We find differences demonstrating the impact of good RDM and data policies on good scientific practice.

The Council of European Social Science Data Archives (CESSDA) is an association of European nation archives working in cooperation to develop a European wide data infrastructure. Part of CESSDA's activities will be promoting Research Data Management training and support through and along with member archives. The aim of this panel is to provide a comparative forum, informing participants on funding environments and data sharing in different European countries thereby providing a cross-national perspective that can be sometimes ignored. This panel brings together representatives from CESSDA member archives to illustrate the social science data sharing requirements and reuse culture in their countries as well as display the work they are doing archiving data for reuse and providing Research Data Management support services. From this panel session we hope to identify commonalities, differences, obstacles, solutions, in the European experience and potential progress strategies for the CESSDA as it addresses the best way to coordinate European wide training and support on RDM, including support for European Union Horizon 2020 research projects. Although the session is focused on the European experience, it welcomes and strongly encourages international perspectives.

The quality of methodology sections is the result of interaction between academic cultures of data sharing, effective application of rules, academic excellence and good quality Research Data Management (RDM).This data set is based on the coding of 66 published empirical articles that used data from at least one wave of the European Values Survey (http://dx.doi.org/10.4232/1.11005) and was published at least in pre-print form between 1984 and 2013. It tests for an article describing the methodology of data collection.