OPTIMISE · Open data: improving transparency, reproducibility and collaboration in science

Open data: improving transparency, reproducibility and collaboration in science

Open data involves making research data publicly available on an online database so they can be permanently stored, accessed, and (re)used by researchers and members of the public. Open data are a fundamental requirement of reproducible research and benefit society by speeding up scientific discoveries. Without access to data underlying published studies, the scientific community is hard pressed to validate and build on scientific discoveries. For this reason, many publishers and funding agencies have begun mandating that researchers publicly archive their datasets as a condition of publication or funding. However, open data policies remain a topic of debate within the scientific community and the adoption of good data sharing practices is slow in many disciplines. For example, some researchers feel strong ownership over their data and fear that potential individual benefits (e.g. increased citation rate, opportunities for co-authorship and new collaborations) will not compensate for any future publications lost by relinquishing priority of access to the data they collected – the fear of being ‘scooped’. At present, apprehensive authors can avoid publishing in journals with an open data policy or share their data in ways that make them difficult or impossible to re-use. There are also concerns about publicly sharing sensitive data that contain private information about human participants and/or the location of endangered species. Nevertheless, responsible open data practices hold the promise of greater transparency and reproducibility in science, with the potential to drastically accelerate research. However, further evidence is needed to verify the efficacy of open data at achieving these aims and assuage beliefs that open data can impede career advancement. The objectives of this action were to examine: (1) the effectiveness of open data at improving the effectiveness and impact of research in environmental science, and (2) the barriers and motivations affecting the decisions of researchers to adopt good open data practices. The findings suggest that improvements to the archiving quality of open data in ecology and evolution has been slow over the last decade, with a lack of researcher training and education identified as one of the main factors affecting poor data archiving practices. Editorial open data policies are largely successful at getting researchers to share their research data but have little to no impact on the completeness and reusability of open datasets. Finally, there is no evidence that good data sharing practices improve transparency in how researchers report their methods and results or that mandatory open data policies by journals increase error correction in ecology and evolution.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз