ArticlePeerJ. Computer science2018
Towards computational reproducibility: researcher perspectives on the use and sharing of software.
Article in PeerJ. Computer science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- cpm: A python library for theory-driven modelling in computational psychiatry.PLoS computational biology · 2026Article
- Exploratory Insights into Barriers and Open Practices for Computational Reproducibility in Scientific Research.F1000Research · 2025Article
- Assessing computational reproducibility in Behavior Research Methods.Behavior research methods · 2024Article
- Gene signatures for cancer research: A 25-year retrospective and future avenues.PLoS computational biology · 2024Article
- The Environmental Data Initiative: Connecting the past to the future through data reuse.Ecology and evolution · 2023Article
- A survey of the state of the practice for research software in the United States.PeerJ. Computer science · 2022Article
- Ten simple rules on writing clean and reliable open-source scientific software.PLoS computational biology · 2021Article
- Collaborating with our community to increase code sharing.PLoS computational biology · 2021Article
- Understanding experiments and research practices for reproducibility: an exploratory study.PeerJ · 2021Article
- A systematic metadata harvesting workflow for analysing scientific networks.PeerJ. Computer science · 2021Article
- Ad hoc efforts for advancing data science education.PLoS computational biology · 2020Article
- Modeling population heterogeneity from microbial communities to immune response in cells.Cellular and molecular life sciences : CMLS · 2020Review
- The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data.PloS one · 2019Review
- Towards computational reproducibility: researcher perspectives on the use and sharing of software.PeerJ. Computer science · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research software, which includes both source code and executables used as part of the research process, presents a significant challenge for efforts aimed at ensuring reproducibility. In order to inform such efforts, we conducted a survey to better understand the characteristics of research software as well as how it is created, used, and shared by researchers. Based on the responses of 215 participants, representing a range of research disciplines, we found that researchers create, use, and share software in a wide variety of forms for a wide variety of purposes, including data collection, data analysis, data visualization, data cleaning and organization, and automation. More participants indicated that they use open source software than commercial software. While a relatively small number of programming languages (e.g., Python, R, JavaScript, C++, MATLAB) are used by a large number, there is a long tail of languages used by relatively few. Between-group comparisons revealed that significantly more participants from computer science write source code and create executables than participants from other disciplines. Differences between researchers from computer science and other disciplines related to the knowledge of best practices of software creation and sharing were not statistically significant. While many participants indicated that they draw a distinction between the sharing and preservation of software, related practices and perceptions were often not aligned with those of the broader scholarly communications community.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.