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Biomedical research software come in various formats such as Python scripts, desktop software, or web applications, and are developed for various purposes such as data visualization, computational modeling, or artificial intelligence (AI) development. They have become an essential part of biomedical research, especially with the advent of cloud computing and AI. Making biomedical research software reusable is therefore critical to enable the reproducibility of research results, prevent duplicate efforts, and ultimately increase the pace of discoveries.
In this talk, we discuss the importance of biomedical research software, why they should be made reusable, and how this can be achieved by developers and managers of biomedical research software. We particularly cover the FAIR Principles for Research Software (FAIR4RS Principles), which are adaptations of the FAIR Principles tailored specially for making research software reusable.
We also present the FAIR Biomedical Research Software (FAIR-BioRS) guidelines, which are a set of minimal, actionable, step-by-step instructions we have established for developers to easily make their biomedical research software reusable in compliance with the FAIR4RS Principles.
This session will be taught by Bhavesh Patel. Bhavesh is an Associate Research Professor at the California Medical Innovations Institute (CalMI2), a nonprofit biomedical research institute located in San Diego, CA. He completed his Ph.D. in Mechanical Engineering at the University of California Berkeley where he specialized in computational modeling. He joined CalMI2 right after graduating in 2015 where he has been developing computational models for various organs and medical devices. He has been involved in the field of Findable, Accessible, Interoperable, and Reusable (FAIR) data practices since 2019. He leads the FAIR Data Innovations Hub, a division at CalMI2 where he and his team are developing various guidelines and computer tools that make it easier for biomedical researchers to make their data and software FAIR. These include tools such as SODA (Software to Organize Data Automatically) for the NIH SPARC program and FAIRhub for the NIH Bridge2AI program.
This presentation meets the NLM/NIH strategic plan goals of (a) accelerating discovery & advancing health by providing the tools for data driven research and (b) building a workforce for data-driven research and health. The presentation addresses health information resources and data and increasing health information access and use by including information about the NIH SPARC and Bridge2AI programs.
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