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As proponents of AI claim it will soon replace software engineers, what does this mean for qualitative researchers and research software development?
The Research Software Directory makes software tools used in research easily discoverable and usable. Thus, it also helps other researchers to reproduce and verify research results.
Research software infrastructure is critical for accelerating science, and yet, these digital public goods are often unsustainably funded. Solving this problem requires an appreciation of the intrinsic value of research software outputs, and greater investment of time and effort into effectively funding maintenance of software at scale.
From Fortran to arXiv.org, these advances in programming and platforms sent biology, climate science and physics into warp speed.
Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally it is recognised that data are meaningless unless their provenance is preserved, through appropriate meta-data. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation, control of experiment or data-collection and that which analyses, modifies and draws value from raw data.
Scientific code is not production software. Scientific code participates in the evaluation of a scientific hypothesis. This imposes specific constraints on the code that are often overlooked in practice.
We are proud to announce the release of enhancements which significantly facilitate scientific software citation and discovery.
Nature journals encourage researchers who submit papers that rely on custom software to provide the programs for peer review.
