BOPI: A Programming Interface For Reuse Of Research Data Available On DSpace Repositories

TL;DR

BOPI is a programming interface designed to improve the findability, accessibility, and usability of research data stored in DSpace repositories, thereby enhancing reproducibility of scientific experiments.

Contribution

This work introduces BOPI, a novel programming interface that enables multilingual search, preview, statistical analysis, and direct download of research data from DSpace systems.

Findings

Usability tests show improved effectiveness in data reuse.

Enhances data findability through multilingual metadata translation.

Facilitates reproducibility by simplifying data access and analysis.

Abstract

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.