Predavanje at an event "ESRA 2019 Conference, Highlighting the contribution of survey research in the changing data environmen, 15.-19.7.2019", European Survey Research Association (ESRA), Zagreb, Croatia (2019)
VIPAVC BRVAR, Irena
Good data management is essential in every research process. Even more when we are talking about international or comparative research. Large research teams and the legal regulations in collaborating countries make international research really challenging. In this presentation, we will present CESSDA's Data Management Expert Guide (www.cessda.eu/dmeg) with a special focus on the tasks needed to make international research and (re-)use of collected data possible. The guide is an online tutorial based on extensive experience of Social Science Data Archives joined in CESSDA consortium. It combines the data archives’ knowledge from engaging with researchers and answering their questions about Research Data Management (RDM). The guide is based on the research data life cycle and can be used either by individual researchers as a self-study material or as part of an online or face-to-face workshop on research data management. Many sources of information on RDM already exist and finding exactly the information you need can be a challenge. The CESSDA Data Management Expert Guide was designed to provide a comprehensive overview of all relevant aspects of data management within one online environment. The guide provides guidance for social scientists throughout all stages of their research while taking into account the diversity of the specific requirements that scientists may have to deal with. Based on responses from current users, this guide can be helpful outside the social sciences as well. Additionally to the guide we will present the work done by Science Europe (S.E.), which has recently published core RDM requirements. These are being implemented by a growing number of national and international research funders in Europe. On top of this, S.E. invites communities to formulate domain protocols for data management that would ease data management planning. A draft for such a protocol for social science research will be presented.
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