Large-Scale Data Sharing in the Life Sciences: Data Standards, Incentives, Barriers and Funding Models (The 'Joint Data Standards Study')

Abstract

Recent studies have demonstrated the value of sharing and re-using data in the life sciences. This study builds on that premise, exploring the practice of sharing data and identifying incentives, facilitators and obstacles to data sharing. In the light of its findings the study presents characteristics of models which support effective, ethical data sharing, to enable first-class, innovative and productive science, within and across disciplines. The study spanned the full spectrum of the life sciences, and all data types and methods. It examined ten case studies, including two comparators from outside the life sciences. These case studies were supplemented by interviews with key informants and by desk research. Key recommendations arising from the study include: insistence on a data management plan, clearly defined remit and goals, sustained work on the development of vocabularies and ontologies, awareness of the needs of archiving and long-term preservation, gathering user input into tools development programmes, and a code of practice for managing and sharing confidential data