From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research

With the digitalisation of scientific practice and processes, including data-driven research and an increasing number of machine/deep learning models, the development of research software has become a fundamental component of scientific work. Proper management and documentation of the research software development process are thus essential for good scientific practice, reproducibility, and knowledge transfer. Similar to data management plans (DMPs), software management plans (SMPs) are an essential tool to document and organise research software development in all phases of its lifecycle: planning, design, coding, testing, sharing, and preserving [1-6]. While there are clear structural parallels between DMPs and SMPs, a key difference stands out: while DMPs have now established themselves as a kind of quasi-standard in many disciplines, SMPs have yet to achieve a comparable adoption. One factor pushing the spread of DMPs was the obligation set by funding bodies. While topics that are addressed by SMPs are already touched upon in many funding applications, SMPs as a tool have not yet found broad adoption: they are currently a common discussion topic in scientific councils but are rarely implemented. Why this discrepancy? To answer this question, we are taking a twofold approach. First, we are conducting qualitative interviews with decision-makers within funding organisations in Germany, the United Kingdom, and Australia. The focus lies on the current and future use of SMPs, as well as their effectiveness for documentation, reporting, and communication. The results will be documented and made accessible as soon as possible. In parallel, a second group is conducting a quantitative survey among scientists, infrastructure providers, and other potential user groups. The focus lies on usage practices, the acceptance, and the user-friendliness of SMPs. The anonymised results will be published as open research data. Our conference contribution brings together the findings from both approaches, involving different stakeholders in the current debate on the use of SMPs in Germany and other countries. At the same time, it highlights current problems and key challenges reported by both funding organisations and the scientific community, while also offering recommendations for future solutions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-04
DOI
https://doi.org/10.5281/zenodo.16735301
Primary Topic
Scientific Computing and Data Management
Type
article
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article

From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research

Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research

article en

Abstract

With the digitalisation of scientific practice and processes, including data-driven research and an increasing number of machine/deep learning models, the development of research software has become a fundamental component of scientific work. Proper management and documentation of the research software development process are thus essential for good scientific practice, reproducibility, and knowledge transfer. Similar to data management plans (DMPs), software management plans (SMPs) are an essential tool to document and organise research software development in all phases of its lifecycle: planning, design, coding, testing, sharing, and preserving [1-6]. While there are clear structural parallels between DMPs and SMPs, a key difference stands out: while DMPs have now established themselves as a kind of quasi-standard in many disciplines, SMPs have yet to achieve a comparable adoption. One factor pushing the spread of DMPs was the obligation set by funding bodies. While topics that are addressed by SMPs are already touched upon in many funding applications, SMPs as a tool have not yet found broad adoption: they are currently a common discussion topic in scientific councils but are rarely implemented. Why this discrepancy? To answer this question, we are taking a twofold approach. First, we are conducting qualitative interviews with decision-makers within funding organisations in Germany, the United Kingdom, and Australia. The focus lies on the current and future use of SMPs, as well as their effectiveness for documentation, reporting, and communication. The results will be documented and made accessible as soon as possible. In parallel, a second group is conducting a quantitative survey among scientists, infrastructure providers, and other potential user groups. The focus lies on usage practices, the acceptance, and the user-friendliness of SMPs. The anonymised results will be published as open research data. Our conference contribution brings together the findings from both approaches, involving different stakeholders in the current debate on the use of SMPs in Germany and other countries. At the same time, it highlights current problems and key challenges reported by both funding organisations and the scientific community, while also offering recommendations for future solutions.

Zenodo (CERN European Organization for Nuclear Research)
Goethe University Frankfurt (DE), Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Physikalisch-Technische Bundesanstalt (DE), Zuse Institute Berlin (DE), Heidelberg University (DE), Humboldt-Universität zu Berlin (DE), Max Planck Digital Library (DE), ZB MED - Information Centre for Life Sciences (DE), Scientific Computing & Modelling (Netherlands) (NL), Technische Universität Berlin (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 49%
Scientific Computing and Data Management
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