Netscher, Sebastian

Recker, Astrid

English

DSpace at Tartu University Library

Introduction to Research Data Management for Social ScientistsThis work is licensed under Creative Commons Namensnennung 4.0 International Lizenz.Astrid Recker & Sebastian NetscherCESSDA Training at the Data Archive for the Social SciencesGESIS - Leibniz Institute for the Social Sciences@CESSDA_DataIntroduction• Consortium of European Social Science Data Archivesa pan-European Research Infrastructure– providing large scale, integrated and sustainable data services – supporting research and co-operation in areas expected to be of great importance CESSDA, What‘s That?AustriaCzech RepublicDenmarkFinlandFranceGermanyGreeceLithuaniaNetherlandsNorwaySloveniaSwedenSwitzerlandUnited KingdomWhat is CESSDA Training?• Provides training and consulting in Research Data Management and Digital Preservation• Promotes strategies and procedures to ensure data quality and long-term availability • Get in touch:– visit our webpage: http://cessda.net/CESSDA-Training– follow us on Twitter: @CESSDA_Data– follow our blog: http://www.cessdatraining.wordpress.com– join our workshopsWe AreImage bySee-mingLee  (CC-by-sa)Astrid Recker (data sharing and digital preservation)Sebastian Netscher (research data management)Round of introductionsImage: CC-0A d…Outline of the WorkshopIntroduction to Research Data Management for Social Scientists09.15-10.30 Research Data Management, Data Discovery and Collection (Astrid & Sebastian)10.30-10.45 Coffee Break10.45-12.30 Data Handling: Documentation, Organizaton and Storage (Sebastian)12.30-13.30 Lunch break13.30-15.15 Research Ethics and Legal Compliance (Sebastian)15.15-15.30 Coffee Break15.30-16.30 Data Sharing and Long-term Preservation (Astrid)16.30-17.00 Wrap-Up (Astrid & Sebastian)Research Data ManagementResearchStudy planningData collectionData analysisArchiving & registeringWhat is Research Data Management (RDM)?• RDM is like “health care” for your data– keeps them safe from harm – makes them usable and discoverable • All strategies, processes and measures to maintain– data quality– interpretability of research results– (re-)usability of research data• Specifically addresses legal and ethical issues (e.g. informed consent, ownership, licensing)Image: CC-0RDM and the Data Lifecycle• RDM guides the research process along the data life cycle• Entails strategies to – process and validate– store and protect– document and describe– preserve and share data.ResearchStudy planningData collectionData analysisArchiving & registeringWhy Do We Need RDM?• It is an integral part of the research process– increases the quality of research– supports planning and guides research– creates transparency and replicability of findings– boosts reputation • It may be required by othersImage: CC-0RDM may be required by…• Your institute, e.g. by your working contract or project agreements• Funding agencies, e.g. to ensure reusability • Journals, claiming your data before publishing your article• Your supervisor…⇒ check for such conditionsImage by A. Herrema & H. Bouwteam (CC-by)Without RDM …… your data remain an undiscovered mystery– neither understandable for you in the future– nor for anyone else who tries to reuse them… your data is lost for yourself as well as for the research community, in disadvantage of researchImage: Iceberg by Uwe Kils (CC-by-sa)Data Management PlanningResearchStudy planningData collectionData analysisArchiving & registeringThe Data Management Plan (DMP)• A DMP is a systematic documentation of RDM• It desribes your strategies to– process and validate– store and protect – preserve and share your datathroughout the data lifecycleImage: CC-0How to Write a DMP?• A DMP uniquely relates to your research project– start right at the beginning of your research project– document what you did and why– frequently up-date and adapt it• A DMP is not just a plan, it is the implementation of a (research) planImage by P. Hochstenbach (CC-by)Where to Get a DMP?• Rely on the data life cycle• Various online templates and tools, e.g.– DCC. (2013): Checklist for a Data Management Plan. http://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf– DMPTool (2015): Data Management Planning Tool. https://dmptool.org//• Use the template provided in this workshopA First Look at the DMP• Have a look at the DMP template in your folder • Familiarize yourself with its sections and subsections• Consider …… parts you would be able to fill in off the top of your head… parts you would have to look for further information… obstacles or problems you encountered in the past  individual work -  time: about 15 minutesImage: CC-0The Structure of the DMP Template• Consists of seven parts– Cover page and general information on the project– Six sections (with subsections):1. data collection ⇒ session 12. documentation and metadata ⇒ session 23. storage, organization and security ⇒ session 24. ethics, legal compliance and Intellectual Property Rights ⇒ session 35. preservation and sharing ⇒ session 46. responsibilities and resourcesDiscovering and Collecting Data ResearchStudy planningData collectionData analysisArchiving & registeringResearchStudy planningData collectionData analysisArchiving & registerigResearch Idea and Research Data• Research idea⇒ strategy to test this idea⇒ definition of data needed– qualitative and/or quantitative data– individual and/or macro dataetc.• Decision on – whether to reuse existing data– or to collect new data?ResearchStudy planningData collectionData analysisArchiving & registerigDiscovering Research Data• Reuse of existing data– a lot of research data available– saves time and effort• Check for reuse of existing data– networks, papers and conferences– repositories, ⇒ e.g. www.re3data.org– CESSDA Data Catalogue⇒ http://cessda.net/CESSDA-Services/Resources/Data-CatalogueResearchStudy planningData collectionData analysisArchiving & registerigCollecting Research Data• No existing data available for reuse⇒ need to collect data• Data collection process– use of standards and methodologies– quality assurance– documentationFurther Readings• CESSDA (2015): Data Catalogue. http://cessda.net/CESSDA-Services/Resources/Data-Catalogue. • Corti, L., van den Eynden, V., Bishop, L. & Woollard, M. (2014): Managing and Sharing Research Data. A Guide to Good Practice. London: Sage Publication Ltd.• DANS (2010): Preparing Data For Sharing. Guide to Social Science Data Archiving. DANS Data Guide 8. The Hague: Royal Netherlands Academy of Art and Sciences & Netherlands Organization for Scientific Research.• Horton, L., van den Eynden, V., Corti, L. & Bishop, L. (2011): Data Management Recommendations for Research Centers and Programmes. Essex: UK Data Archive.• Jones, S. (2011): How to Develop a Data Management and Sharing Plan. Glasgow: Digital Curation Centre (DCC).

Introduction to Research Data Management for Social Scientists

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Introduction to Research Data Management for Social Scientists

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