Semantic ModelingIn contrast to other types of data models, a semantic model specifies the meaning of domain-specific concepts such as genes, proteins, and assays. With a well-integrated semantic model, both humans and machines can easily find which data is right for their use case and unambiguously understand the data and its context. A semantic model simplifies research data integration and management and forms a key step towards making data more FAIR.
Building a Semantic Model (using RDFS or OWL) for R&D research covering areas like Project, Study, Assay, Dataset, Clinical Trial, etc. We can also provide integration of a range of biomedical data - PK/PD, Omics, ELNs, sample inventories, public datasets, CMC data, etc.
Aligning metadata with enterprise data governance, i.e. the common vocabularies/ontologies/metadata guidelines used within the organization.
Data curation to increase interoperability and usability of data using open-source industry-standard ontologies and vocabularies and building knowledge graphs.
Data lives in specific vendor applications, which hampers data integration, use of the data in new scenarios, and prevents a unified view of the data within the company.
Having the data in an application-specific structure is useful as long as it is used within the application. It might prevent use outside the application, though, which is especially problematic when the application is no longer supported or replaced.
Legacy data becomes unusable when the meaning or context can no longer be retrieved.
Data across subsequent stages of R&D is unlinked and therefore impossible to interpret.
Are you, as a data steward, data scientist or researcher, constantly wasting time cleaning and structuring siloed data from different data sources and datasets? And does the way the data is stored and annotated hinder you in making biomedical discoveries?
Maybe you have just started looking into semantic models and knowledge graphs as a solution for these time and resource consuming efforts? This infographic shows the benefits of semantic models and knowledge graphs and how The Hyve, in collaboration with a top pharma company, solved their data integration challenge.
