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The challenges of theory-software translation.

Caroline JayRobert HainesDaniel S KatzJeffrey C CarverSandra GesingSteven R BrandtJames HowisonAnshu DubeyJames C PhillipsHui WanMatthew J Turk
Published in: F1000Research (2020)
Background: Software is now ubiquitous within research. In addition to the general challenges common to all software development projects, research software must also represent, manipulate, and provide data for complex theoretical constructs. Ensuring this process of theory-software translation is robust is essential to maintaining the integrity of the science resulting from it, and yet there has been little formal recognition or exploration of the challenges associated with it. Methods: We thematically analyse the outputs of the discussion sessions at the Theory-Software Translation Workshop 2019, where academic researchers and research software engineers from a variety of domains, and with particular expertise in high performance computing, explored the process of translating between scientific theory and software. Results: We identify a wide range of challenges to implementing scientific theory in research software and using the resulting data and models for the advancement of knowledge. We categorise these within the emergent themes of design, infrastructure, and culture, and map them to associated research questions. Conclusions: Systematically investigating how software is constructed and its outputs used within science has the potential to improve the robustness of research software and accelerate progress in its development. We propose that this issue be examined within a new research area of theory-software translation, which would aim to significantly advance both knowledge and scientific practice.
Keyphrases
  • data analysis
  • healthcare
  • primary care
  • public health
  • machine learning
  • electronic health record
  • quality improvement
  • risk assessment