Curation as “Interoperability With the Future”: Preserving Scholarly Research Software in Academic Libraries

Abstract

This article considers the problem of preserving research software within the wider realm of digital curation, academic research libraries, and the scholarly record. We conducted a pilot study to understand the ecosystem in which research software participates, and to identify significant characteristics that have high potential to support future scholarly practices. A set of topical curation dimensions were derived from the extant literature and applied to select cases of institutionally significant research software. This approach yields our main contribution, a curation model and decision framework for preserving research software as a scholarly object. The results of our study highlight the unique characteristics and challenges at play in building curation services in academic research libraries.

The Open Innovation in Science research field: a collaborative conceptualisation approach

“…The free and open-source software movement provided inspiration to early calls for Open Science (Willinsky 2005), and today the transparency of open-source code allows the scientific community to cross boundaries around field-specific software packages and converge on common solutions like the software environment R. Another example is REANA, a research data analysis platform created by CERN to enable code and data reuse and reproduction, which has generated interest in disciplines well beyond physics (Pujol and Wareham 2019). However, as certain kinds of scientific research becomes inextricable from the software that supports them, software curation and preservation are becoming essential to secure the integrity of the scholarly record (Chassanoff and Altman 2020).…”

Reproducible Research Publication Workflow: A Canonical Workflow Framework and FAIR Digital Object Approach to Quality Research Output

“…These require a separate review process. We note that evaluating the reproducibility of a program code must account for the variability of some parameters, for example, the same source code of a machine learning program might lead to different sets of outputs and weights depending on the machine [21].…”

Emulation practices for software preservation in libraries, archives, and museums

“…Despite the increasing prevalence of software preservation in information institutions and concerns about these challenges amongst information professionals, scholarly attention to the software maintenance practices of librarians and archivists has been limited. Some notable recent examples include Chassanoff, Donaldson, and Kriesberg working on software curation in support of research data management practices in government, scientific repositories, and university research libraries (Chassanoff & Altman, 2020;Donaldson, 2019;Kriesberg et al, 2017). Even so, the coordination and social practices of software preservation projects often focus research on cyberinfrastructure initiatives, engineering teams, or space missions (Cohn et al, 2009;Mackenzie, 2006;Sim et al, 2009).…”