Promoting Transparency and Trust in Biomedical Data: A FAIR Approach to Content Creation and Sharing - Asim Abbas; Sebastian Chalarca; Iram Wajahat; Fazel Keshtkar; Syed Ahmad Chan ukhari (Proceedings of the International Florida Artificial Intelligence Research Society Conference)
Efficient sharing of scientific knowledge is vital for research advancement and reproducibility. However, PDF dominance poses challenges in adhering to FAIR principles (Findability, Accessibility, Interoperability, Reusability). Some web-based frameworks enhance content interoperability using RDF and linked data but often target technical users. To address this, we introduce ``Semantically", a user-friendly platform for biomedical researchers that offers a semantic content authoring module, collaboration tools and improving annotation accuracy. We also propose a publishing infrastructure using schema.org to ensure machine-readable and well-organized datasets, enhancing data FAIRness. Combining Semantically's authoring module and schema.org provides a comprehensive solution for enhancing FAIRness and reproducibility of scientific content. ``Semantically" is an open-source tool accessible at~\href{https://github.com/bukharilab/Semantically}{Github}.