Year: 2017
Type: article
Abstract: Achieving research reproducibility is challenging in many ways: there are social and cultural obstacles as well as a constantly changing technical landscape that makes replicating and reproducing research difficult. Users face challenges in reproducing research across different operating systems, in using different versions of software across long projects and among collaborations, and in using publicly available work. The dependencies required to reproduce the computational environments in which research happens can be exceptionally hard to track – in many cases, these dependencies are hidden or nested too deeply to discover, and thus impossible to install on a new machine, which means adoption remains low. In this paper, we present ReproZip , an open source tool to help overcome the technical difficulties involved in preserving and replicating research, applications, databases, software, and more. We will examine the current use cases of ReproZip , ranging from digital humanities to machine learning. We also explore potential library use cases for ReproZip, particularly in digital libraries and archives, liaison librarianship, and other library services. We believe that libraries and archives can leverage ReproZip to deliver more robust reproducibility services, repository services, as well as enhanced discoverability and preservation of research materials, applications, software, and computational environments.
Source: IASSIST Quarterly
DOI: 10.29173/iq18
Authors: Vicky Steeves, Rémi Rampin, Fernando Chirigati
Institution: New York University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W2776350112