An Analytics Tool for Exploring Scientific Software and Related Publications

TL;DR

This paper introduces an analytics tool designed to explore and connect scientific software with related publications, enhancing reproducibility and joint artifact exploration.

Contribution

It presents a prototype and concept for automatic code discovery linking scientific software with publications, demonstrating feasibility and usefulness.

Findings

Prototype successfully links software and publications

Automatic code discovery is feasible

Use cases show practical benefits

Abstract

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.