About Reproducible Research Data and Software
Reproducible Research Data and Software
About this Collection
Open research practices, where academic work is made as transparent and accessible as possible, are important when using digital technology in research projects. Enabling reproducibility means that the findings of a study should be reliably achieved again when it is repeated.
The creation of reproducible software and data has major benefits for stakeholders such as the scientific community, funding bodies, the general public. Software and data can be used and reused across the research community and beyond to improve our knowledge and drive innovation.
Software and data are important outputs of academic work and are significant digital research objects, which require appropriate management. Having a solid foundation of reproducible research software enables transparency and strengthens the authority of research work by enabling others to independently replicate and verify their results.
Access to high-quality data sets is the lifeblood of many areas of contemporary academia. Research software and data play an important role throughout the entire research lifecycle, from prototypes and exploratory data analysis, through to archived outputs that can be repurposed by others to explore new questions in the future, enabling ground-breaking new discoveries.
This collection brings together articles that explain how to improve your ability to write research software and manage data that is easier for others to find, access, and use. This increases the impact of your research through the creation of high-quality, non-traditional outputs and data analyses.
These materials encompass a range of interdisciplinary perspectives, making it an invaluable resource for researchers, scientists, software engineers, and practitioners seeking to enhance the reliability and rigour of their computational research.
With a focus on best practices, practical techniques, and cutting-edge tools, this collection serves as a valuable resource for anyone seeking to enhance the reliability and trustworthiness of their software-based research work.
The scope of this collection includes, but is not limited to:
Deadline: 31st December 2023
Any questions about this collection? Please get in contact with research@f1000.com.
This Collection is associated with the Research on Research, Policy & Culture Gateway.
The creation of reproducible software and data has major benefits for stakeholders such as the scientific community, funding bodies, the general public. Software and data can be used and reused across the research community and beyond to improve our knowledge and drive innovation.
Software and data are important outputs of academic work and are significant digital research objects, which require appropriate management. Having a solid foundation of reproducible research software enables transparency and strengthens the authority of research work by enabling others to independently replicate and verify their results.
Access to high-quality data sets is the lifeblood of many areas of contemporary academia. Research software and data play an important role throughout the entire research lifecycle, from prototypes and exploratory data analysis, through to archived outputs that can be repurposed by others to explore new questions in the future, enabling ground-breaking new discoveries.
This collection brings together articles that explain how to improve your ability to write research software and manage data that is easier for others to find, access, and use. This increases the impact of your research through the creation of high-quality, non-traditional outputs and data analyses.
These materials encompass a range of interdisciplinary perspectives, making it an invaluable resource for researchers, scientists, software engineers, and practitioners seeking to enhance the reliability and rigour of their computational research.
With a focus on best practices, practical techniques, and cutting-edge tools, this collection serves as a valuable resource for anyone seeking to enhance the reliability and trustworthiness of their software-based research work.
The scope of this collection includes, but is not limited to:
- How the benefits and challenges of reproducibility are communicated and taught to the next generation of researchers
- Reproducibility in software development
- How data processing workflows are made reproducible and documented for reuse (metadata, provenance)
- Talks and posters about how researchers have made their work FAIR/open
- Software publication best practices: dependency management, version control
- Writing documentation for code and data
- Software development skills and techniques to ensure code clarity, readability, and maintainability.
- Using containerization and virtualization to create reproducible computing environments for research software and data processing.
- Project design; data management planning
- Software testing; data validation
- The ethical and legal considerations surrounding data privacy, open-source software, and intellectual property rights within the context of reproducible digital research outputs
- The challenges of making machine learning and artificial intelligence systems replicable and transparent
- How the concepts of open research and reproducible software apply in the context of cloud computing
Deadline: 31st December 2023
Any questions about this collection? Please get in contact with research@f1000.com.
This Collection is associated with the Research on Research, Policy & Culture Gateway.
Collection Advisor
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Joe Heffer