RDA COVID-19 Guidelines and Recommendations
Research Data Alliance releases recommendations and guidelines for data sharing in the context of the COVID-19 pandemic

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The Research Data Alliance (RDA) COVID-19 Working Group has released the final version of its guidelines and recommendations on how data from multiple disciplines inform responses to a pandemic and can be shared under the present COVID-19 circumstances.

The COVID-19 pandemic has demonstrated challenges and roadblocks in the rapid collection, sharing and dissemination of data and research findings to inform urgent public health responses. The RDA COVID-19 Working Group was formed to help address these challenges by developing guidelines and recommendations for the deposit of data sources in common data hubs or platforms, and sharing of data, including a framework, common tools and processes, and principles that can be embedded in research practice. 

The Working Group addressed four research areas (Clinical, Omics, Epidemiology, Social Sciences) with four cross-cutting themes (Community Participation, Indigenous Data, Legal and Ethical Considerations, Research Software). EIFL Open Access Programme Manager Iryna Kuchma co-moderated the Social sciences sub-group with Amy Pienta from the University of Michigan. 

The guidelines aim to help stakeholders follow best practices to maximize the efficiency of their work, and to act as a blueprint for future emergencies. The recommendations are aimed at helping policymakers and funders to maximize timely, quality data sharing and appropriate responses in health emergencies.

The RDA Guidelines and Recommendations - a snapshot

  • Governments, research funders, and research or research-supporting institutions from across the globe should coordinate their efforts, support and promote open science through policy and investment to streamline the flow of data between local entities, and across international jurisdictions. The recommendations note the need for incentivizing the early publication/release of data outputs and the software used to produce them during a public health emergency. 
  • Research outputs should align with the FAIR principles, meaning that data, software, models and other outputs should be Findable, Accessible, Interoperable and Reusable. A balance between achieving ‘perfectly’ FAIR outputs and timely sharing is necessary, with the key goal of immediate and open sharing as a driver. Data management plans should be created early in the research process and updated regularly to prepare for data deposit and reuse.
  • Research outputs need to be documented, including documentation of the methodologies used to collect, define and construct data, data cleaning, data imputation, data provenance and so on. 
  • To facilitate data quality control, timely sharing and sustained access, data should be deposited in data repositories. Whenever possible, these should be trustworthy data repositories that have been certified, subject to rigorous governance, and committed to longer-term preservation of their data holdings. 
  • With respect to ethical and privacy considerations around participant and patient data, the guidelines note the need to find a balance that takes into account individual, community and societal interests and benefits while also addressing public health concerns and objectives. Access to individual participant data and trial documents should be as open as possible and as closed as necessary, to protect participant privacy and reduce the risk of data misuse. 
  • Emergency data related laws and regulations activated during a pandemic need to clearly outline data custodianship/ownership, publication rights and arrangements, consent models, and permissions around sharing data and exemptions.