BOPI: A Programming Interface For Reuse Of Research Data Available On DSpace Repositories
This addresses the issue of reproducibility for researchers by providing a tool to access and reuse data more effectively, though it is incremental as it builds on existing DSpace systems.
The paper tackles the problem of low reproducibility in scientific experiments by developing a programming interface (BOPI) that enhances findability and accessibility of research data in DSpace repositories, with usability tests showing improvements in effectiveness, efficiency, and satisfaction during data reuse.
A recent study showed that more than 70% of researchers fail to reproduce their peers's experiments and more than half fail to reproduce their own experiments. Obviously, from a perspective of scientific quality this is a more than unsatisfying numbers. One approach to mitigate this flaw lies in the transparent provision of relevant research data to increase the base of available material to evaluate and possibly reconduct experiments. However, such data needs to be presented and accessed in a findable and purposefully usable way. In this work, we report the development of a programming interface to enhance findability and accessibility of research data (available in DSpace systems) and hence reproducibility of scientific experiments with data. This interface allows researchers to (i) find research data in multiples languages trough automatic translation of metadata; (ii) display a preview of data without download it beforehand; (iii) provide a detailed statistics of the data with interactive graphs for quality assessment; (iv) automatic download of data directly from Python-based experiments. Usability tests revealed that this interface improves the effectiveness, efficiency and satisfaction during the reuse of research data.