Risk Management for Research Data about people. A general matrix to be used by data stewards and research supporters for the assessment of privacy risks with research data and determination of appropriate methods for risk management

This matrix is generic. It is a tool for data stewards or other research supporters to assist researchers in taking appropriate measures for the safe use and protection of data about people in scientific research. It is a template that you can adjust to the context of your own institution, faculty and / or department by taking into consideration your setting’s own policies, guidelines, infrastructure and technical solutions. In this way you can more effectively determine the appropriate technical and organizational measures to protect the data based on the context of the research and the risks... Mehr ...

Verfasser: Hrudey, Jessica
Ploeg, Jan Lucas van der
Schrijvers, Joan
Verhoeven, Arnold
Hoogen, Henk van den
Sijbers-Klaver, Marjolein
Ilamparuthi, Santosh
Kuiper, Toine
Tjong Kim Sang, Erik
van Ulzen, Niek
Drost, Yvonne
Verheul, Ingeborg
Dokumenttyp: other
Erscheinungsdatum: 2019
Verlag/Hrsg.: Zenodo
Schlagwörter: Anonymization / Pseudonymization / RDM / Research Data Management / LCRDM / Netherlands / Personal Data / Basic Steps / Risk Management / Data Stewardship / Data Support / Privacy Risk
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26807883
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://research.hva.nl/en/publications/bc5c948a-6c75-40c7-835d-e28746925b0d

This matrix is generic. It is a tool for data stewards or other research supporters to assist researchers in taking appropriate measures for the safe use and protection of data about people in scientific research. It is a template that you can adjust to the context of your own institution, faculty and / or department by taking into consideration your setting’s own policies, guidelines, infrastructure and technical solutions. In this way you can more effectively determine the appropriate technical and organizational measures to protect the data based on the context of the research and the risks associated with the data.