Drexel-CODATA FAIR-RRDM Workshop 2019
Sun 31 March and Mon 1 April 2019, Drexel University, Philadelphia, USA.
Responsible data management embodies the FAIR principles of making data findable, accessible, interoperable, and reusable. FAIR has helped focus minds and provided readily adopted terminology and guidelines, which in turn will help realise the benefits of accelerated analysis, with machines, at scale. In consequence, research communities and research institutions are faced with the task of rising to the challenge of FAIR and responsible data management.
Advancing the adoption of FAIR requires sharing protocols, practices, policies, methodologies, and approaches for responsible data management. The open science and open data movements have made significant progress in certain research communities and domains, but less so in others. While good practices have been developed within some research communities, it is in research institutions and universities that data management and some long term stewardship must take place. Sometimes reluctantly, research institutions have been obliged to take greater responsibility for research data management by the needs of researchers and their communities on the one hand and by the requirements of national funders on the other.
There are opportunities for knowledge sharing and coordination across a number of these axes: between research disciplines and communities; between research communities and institutions; and internationally among institutions. The biomedical and genomics fields, for example, have made considerable progress with data sharing and with issues of nomenclature and semantics. Much research activity of the last two decades could not have happened without community agreements on data sharing and mechanisms for managing concepts, semantic specifications and ontologies. Likewise, many biomedical research domains are addressing the challenges of controlled sharing of sensitive and restricted data, following the FAIR principles but with respect to ethical and legal criteria where these prevent certain data from being fully Open.
The aim of this workshop is to bring together researchers, data management experts, policy leaders and to facilitate knowledge sharing between research communities and between institutions. Perspectives from all domains and from research institutions are in scope. At least one session will examine progress in the biomedical community and lessons to be learnt, particularly in relation to good practice and mechanisms for controlled sharing of sensitive and restricted data.
Outputs and Impact
- highlight and scrutinise innovative approaches and key developments fulfilling FAIR principles;
- promote broad interest and participation in the pursuit of solutions across disciplines and institutions; and
- identify concrete mechanisms for knowledge sharing between research communities and between research institutions.
Call for Presentations and Posters/Lightning Talks
The deadline will be 18 February and accepted speakers will be notified no later than 1 March.
Recommended proposal lengths for the three categories of presentation are:
- Long, research presentation, addressing the workshop themes by reporting on an original research activity: 800-1200 words
- Short, practice presentation, addressing the workshop themes by reporting on a project or institutional activity: 400-800 words
- Poster and lightning talk addressing the workshop themes: 300-600 words
Workshop Themes / Sessions
- FAIR data: implications and responsibilities 1) for research communities and 2) for research institutions.
- FAIR data stewardship and knowledge sharing. What progress has been made in RDM and FAIR data stewardship? What can be learnt from biomedical research and from other domains?
- Limits of open data and how do deal responsibly with sensitive data. What can be learnt from biomedical fields and other fields for the controlled sharing of sensitive data?
- RDM, FAIR stewardship services and research infrastructures 1) for research communities and 2) for research institutions. How are research communities and/or research institutions implementing research infrastructures for RDM and FAIR stewardship? How are they tackling related and supporting issues such as: a) developing skills and capacity; b) addressing policy, legal and ethical issues; c) aligning strategies and priorities with FAIR and RDM responsibilities?
- Alignment of domain and institutional RDM and FAIR stewardship: What experiences exist and mechanisms are there for aligning domain and institutional RDM and FAIR stewardship? Examples of collaboration between research communities, domain research infrastructures and institutions will be particularly welcome.