S4: Data Standards, Ontologies, and Software Tools
Data Standards, Ontologies, and Software Tools for FAIR Open Data
University of Miami, Miami, Florida
As part of the Library of Integrated Network-based Cellular Signatures (LINCS) program and other national research consortia, we have developed data standards and ontologies to harmonize, annotate, and formally describe diverse biological data types to support the research community’s goals of making these digital resources Findable, Accessible, Interoperable, and Reusable (FAIR). These data include multi-omics datasets from the LINCS consortium, chemical biology data from PubChem, biochemical target data from various resources, and most recently we leveraged data from Tox21 and other reporter gene assays from the Molecular Libraries Program. To standardize and integrate these datasets we leverage we ontologies including BioAssay Ontology, Drug Target Ontology, Cell Line Ontology, which we developed or contributed to developing. To enable FAIR data in practice, in the LINCS consortium, we have developed and implemented infrastructure and processes to handle the entire data pipeline from receiving data and metadata, registration, annotation, mapping to external reference resources, and publication via the LINCS Data Portal (LDP). We are also developing better data curation tools and technologies to facilitate the needs of domain experts to request ontology updates and new terms from ontology developers. I will provide an overview of the data standards, ontologies, processes, and software tools we have been developing to support such FAIR open data.