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RDA COVID-19 Working Group. Recommendations and Guidelines on data sharing

  • The Research Data Alliance (RDA) COVID-19 Working Group members bring various, global expertise to develop a body of work that comprises how data from multiple disciplines inform response to a pandemic combined with guidelines and recommendations on data sharing under the present COVID-19 cicumstances. This extends to research software sharing, in recognition of the key role in software in analysing data. The work has been divided into four research areas (namely, clinical, omics, epidemiology, social sciences) with four cross cutting themes (namely, community participation, indigenous data, legal and ethical considerations, research software), as a way to focus the conversations, and provide an initial set of guidelines in a tight timeframe. The detailed guidelines are aimed to help stakeholders follow best practices to maximise the efficiency of their work, and to act as a blueprint for future emergencies. The recommendations in the document are aimed at helping policymakers and funders to maximise timely, quality data sharing and appropriate responses in such health emergencies. This work was executed in an intense period over just over 6 weeks, with five iterations, all of which were opened for public community comment. Draft releases and comments are avaialable here (https://doi.org/10.15497/rda00046). This activity has been conducted under the RDA guiding principles of Openness, Consensus, Balance, Harmonization, Community-driven, and Non-profit and technology-neutral.

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Metadaten
Author:Stefan SauermannORCiD
Parent Title (English):Research Data Alliance, 2020.
Document Type:Article
Language:English
Completed Date:2020/06/30
Date of first Publication:2020/11/27
Responsibility for metadata:Fachhochschule Technikum Wien
Release Date:2020/11/27
GND Keyword:COVID19 Data Sharing
Publish on Website:1
Open Access:1
Reviewed:1
Link to Publication:https://doi.org/10.15497/rda00052.
Department:Department Life Science Engineering
Research Focus:Data-Driven, Smart & Secure Systems
Projects:Eigenmittel
Studienjahr:2019/2020
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International