Biology subjects

Soundarajan, S.

Publications and source records attributed to Soundarajan, S..

3 recordsLinked to original sources

bioRxiv2023

SODA: Software to Support the Curation and Sharing of FAIR Autonomic Nervous System Data

Since 2014, the National Institutes of Health (NIH)s Stimulating Peripheral Activity to Relieve Conditions (SPARC) Program has been supporting research and development of therapeutic devices that modulate electrical activity in the autonomic nervous system (ANS) to improve organ function, also known as bioelectronic medicine. To optimize the reusability of data resulting from ANS-related research, the SPARC Program also supported the development of guidelines for curating and sharing data in line with the FAIR (Findable, Accessible, Interoperable, Reusable) Principles. These guidelines are exhaustive to maximize FAIRness of data but as a result, they are difficult and time-consuming for researchers to implement. To address these challenges, we developed SODA (Software to Organize Data Automatically), an open source and free cross-platform desktop software that guides researchers step-by-step in preparing and sharing their ANS-related data according to the SPARC guidelines. SODA combines intuitive user interfaces with automation to streamline the process and reduce researchers time, effort, and error in making their data FAIR. We provide in this paper an overview of SODA and results of testing its performance. We also provide an overview of the impact of SODA which is, to our knowledge, the first researcher-oriented tool for making data FAIR.

bioinformatics↗

bioRxiv2022

Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool

Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles tailored for research software have been proposed by the FAIR for Research Software (FAIR4RS) Working Group. They provide a foundation for optimizing the reuse of research software. The FAIR4RS principles are, however, aspirational and do not provide practical instructions to the researchers. To fill this gap, we propose in this work the first actionable step-by-step guidelines for biomedical researchers to make their research software compliant with the FAIR4RS principles. We designate them as the FAIR Biomedical Research Software (FAIR-BioRS) guidelines. Our process for developing these guidelines, presented here, is based on an in-depth study of the FAIR4RS principles and a thorough review of current practices in the field. To support researchers, we have also developed a workflow that streamlines the process of implementing these guidelines. This workflow is incorporated in FAIRshare, a free and open-source software application aimed at simplifying the curation and sharing of FAIR biomedical data and software through user-friendly interfaces and automation. Details about this tool are also presented.

scientific communication and education↗

bioRxiv2021

SPARClink: an interactive tool to visualize the impact of the SPARC program

The NIH SPARC program seeks to accelerate the development of therapeutic devices that modulate electrical activity in nerves to improve organ function. SPARC-funded researchers are generating rich datasets from neuromodulation research that are curated and shared according to FAIR (Findable, Accessible, Interoperable, and Reusable) guidelines and are accessible to the public on the SPARC data portal. Keeping track of the utilization of these datasets within the larger research community is a feature that will benefit data generating researchers in showcasing the impact of their SPARC outcomes. This will also allow the SPARC program to display the impact of the FAIR data curation and sharing practices that have been implemented. This manuscript provides the methods and outcomes of SPARClink, our web tool for visualizing the impact of SPARC, which won the 2nd prize at the 2021 SPARC FAIR Codeathon. With SPARClink, we built a system that automatically and continuously finds new published SPARC scientific outputs (datasets, publications, protocols) and the external resources referring to them. SPARC datasets and protocols are queried using publicly accessible REST APIs (provided by Pennsieve and Protocols.io) and stored in a publicly accessible database. Citation information for these resources is retrieved using the NIH reporter API and NCBI Entrez system. A novel knowledge-graph-based structure was created to visualize the results of these queries and showcase the impact that the FAIR data principles can have on the research landscape when they are adopted by a consortium.

bioinformatics↗