This webinar explores how the Mondo ontology bridges clinical and translational research, featuring insights from Chris Mungall and hosted by the Pistoia Alliance’s FAIR Implementation Community of Interest.

By Amos Bairoch, University of Geneva and Swiss Institute of Bioinformatics

This webinar presents the Cellosaurus, a manually curated knowledge resource which aims to describe all cell lines used in biomedical research. It provides information on immortalized, naturally immortal and finite life cell lines. Its taxonomy scope encompasses both vertebrates and invertebrates. Currently it describes over 122,000 cell lines from 684 species. For each cell line it provides a wealth of information, cross‐references and literature citations.

The Cellosaurus is available on the ExPASy server (https://web.expasy.org/cellosaurus/) and can be downloaded in different formats under the CC BY 4.0 license. The Cellosaurus is a key resource to help researchers identify potentially contaminated/misidentified cell lines, thus contributing to improving the quality and reproducibility of research in the life sciences. It is part of the Resource Identification Initiative (RII) which aims to enable resource transparency within the biomedical literature through the use of Research Resource Identifiers (RRIDs). Some of the information in the Cellosaurus is uploaded into Wikidata thus allowing semantic connection of cell lines to other biological objects. We would like to expand its use in the context of the FAIRification of biological data by providing an RDF version of the resource and a SPARQL endpoint query service.

This webinar will explore how the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles can serve as a key enabler to automate and accelerate R&D process workflows. Through the lens of a real-world use case, the session will illustrate the practical implementation of FAIR, highlighting its role in driving faster and more impactful science. By making data more reusable and enhancing its value, FAIR also facilitates greater collaboration and partnership through improved data sharing. Ultimately, the webinar aims to show how FAIR interoperability makes data truly actionable, unlocking its full potential across research ecosystems.

This webinar presents the Statistics Ontology, STATO which is a semantic framework to support the creation of standardized analysis reports to help with review of results in the form of data matrices. STATO includes a hierarchy of classes and a vocabulary for annotating statistical methods used in life, natural and biomedical sciences investigations, text mining and statistical analyses.

This presentation reviewed the challenges in identifying, acquiring and utilizing research data in relation to an evolving data market. Strategic solutions were examined in which the FAIR principles play a key role in the future of data management.

With the explosion of interest in both enhanced knowledge management and open science, the past few years have seen considerable discussion about making scientific data “FAIR” — findable, accessible, interoperable, and reusable. The problem is that most scientific datasets are not FAIR. When left to their own devices, scientists do an absolutely terrible job creating the metadata that describe the experimental datasets that make their way in online repositories. The lack of standardization makes it extremely difficult for other investigators to locate relevant datasets, to re-analyse them, and to integrate those datasets with other data.

The Center for Expanded Data Annotation and Retrieval (CEDAR) has the goal of enhancing the authoring of experimental metadata to make online datasets more useful to the scientific community. The CEDAR work bench for metadata management will be presented in this webinar. CEDAR illustrates the importance of semantic technology to driving open science. It also demonstrates a means for simplifying access to scientific data sets and enhancing the reuse of the data to drive new discoveries.