As organisations produce data and ingest externally generated data it is critical that they are able to harmonise to acceptable standards. The movement towards FAIR emphasises the need for human and machine readable metadata to enable data descriptions to be widely understood, both for the now and again in the future.
This need for FAIR is never more acutely felt than with the increasing investment in areas such as training deep learning models, as well as in search and big data integration. Finding, understanding and harmonising data for these applications is a long standing problem that requires good metadata; properly managed ontology standards are a key component of this strategy.
During this webinar you will hear from our Head of Ontologies Jane Lomax as she explains how we are working with our customers to embrace these standards, starting with robust ontology management, through to end user applications such as assay registration and natural language queries.
In the first of this two-part blog, I describe what ontologies are and how you can use them to make the best use of scientific data within your organisation.Read
This blog post focuses on mapping, building, and managing ontologies. In my previous blog, I described what ontologies are and how you can use them to make the best use of scientific data within your organization. Here I’ll expand upon this and focus on mapping, building, and managing ontologies.Read
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