Within the Clinical Sciences domain, there are standard terminology to uphold for metadata related to trial submissions. We will show an example of a [meta]data set required in clinical data workflow, which assembles metadata from multiple references to summarize a study design in a specific tabular format.

Implicit in this manual, repetitive process are semantic fundamentals of defining classes, relating synonyms to preferred terms, annotating or maintaining reference identifiers, and curating specific information against a standard term or format. Traditionally this manual work would take days to complete and would be repeated for each data set.

During this webinar we will discuss a tool and process built to semi-automate the ontology management, named entity recognition, and curation of this process using SciBite tools and associated APIs. By employing this method and defining the semantics with a suite of SciBite tools, we reduce manual efforts and reduce time needed to build this data set from days to hours.

The time savings from using tools translates to more time to devote to the studies themselves and less time tediously shifting through references. Finally, not to be dismissed, the knowledge preserved with semantic tools also scales to create future reproducible and connected (FAIR) data.