OPTIMISE SIGNED

Project "OPTIMISE" data sheet

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 Project objective

Science is facing a reproducibility crisis, whereby many research results, including landmark studies, cannot be independently reproduced. As a consequence, scientific progress is slowed and entire research fields can be misguided. Finding a meaningful solution to this crisis requires increasing transparency and collaboration among researchers to ‘OPTIMISE’ how we conduct science. I will study the role and importance of open data as a means of achieving this goal. Making research data openly accessible to other scientists and the public has many societal benefits, including validating research results and accelerating discoveries. However, open data is controversial among researchers, mainly because of perceived individual costs. Furthermore, we lack empirical research on the efficacy of open data practices at resolving the reproducibility crisis. By combining approaches in social and natural sciences, this action will address this knowledge gap in an interdisciplinary fashion via two overarching objectives: A) Assess whether open data policies result in high-quality data sharing and reduce poor scientific practices; B) Investigate the barriers and motivations behind decisions to adopt open data practices. I will focus on the field of ecology and evolution (my background) and examine: 1) the efficacy of editorial policies mandating open data, 2) the influence of open data practices on the quality of research results, 3) challenges and solutions to sharing sensitive data, 4) barriers to good open data practices, and 5) individual motivations for sharing data. The data to answer these questions are readily collectable and reciprocal knowledge transfer will directly benefit both the hosts and the candidate. Deliverables will help elucidate the barriers and benefits of open science practices to improve research transparency, reproducibility and discovery. These goals support H2020’s objective to facilitate innovation and growth while maintaining scientific integrity.