An Analytics Tool for Exploring Scientific Software and Related Publications
This addresses the need for better reproducibility in research by providing a tool for scientists and researchers, though it is incremental as it builds on existing ideas for linking software and publications.
The paper tackles the problem of insufficient linking between scientific software and publications by developing an analytics tool for joint exploration, demonstrating feasibility and usefulness through a prototype, automatic code discovery concept, and two use cases.
Scientific software is one of the key elements for reproducible research. However, classic publications and related scientific software are typically not (sufficiently) linked, and it lacks tools to jointly explore these artefacts. In this paper, we report on our work on developing an analytics tool for jointly exploring software and publications. The presented prototype, a concept for automatic code discovery, and two use cases demonstrate the feasibility and usefulness of the proposal. Submitted to TPDL 2018 as Demonstration Paper.