Affiliations: [a] Department of Engineering and Management, Instituto Superior Técnico, Lisbon University, Portugal; (E): [email protected] | [b] Department of Computer Science and Engineering, Instituto Superior Técnico, Lisbon University, Portugal; (E): [email protected] | [c] Information and Decision Support Laboratory, INESC-ID; Portugal; (E): [email protected] | [d] Information and Decision Support Laboratory, INESC-ID; Department of Computer Science and Engineering, Instituto Superior Técnico, Lisbon University; Portugal; (E): [email protected]
Abstract: The potential for long-term reuse of scientific data implies the need to manage the data for teh aforementioned purpose since day one. Data management must be applied throughout the scientific data lifecycle, comprising the creation, processing, analysis, preservation, access, and re-use of the data. As of today, a recommendation in the data management process should result in the constant update of a Data Management Plan. That document should contain answers to the key questions regarding identification of the nature of data, and the rules for its sharing, access, and archival. Since all these activities have associated uncertainties, it is necessary to apply a risk management process. In this research, a literature analysis, that produced a preliminary list of risk factors, was conducted; thereafter, these factors were consolidated after a Delphi study with a group of experts.
Keywords: Data management, Scientific data, Metadata, Delphi, Reference risk matrix
