SciBite’s Vocabulary Editing Toolkit (VET) is a desktop application designed to help curators build and manage lists of semantically related terms.
VET is an intuitive editor that makes it easy for scientists to adapt existing vocabularies or curate entirely new ones. The customisable, clutter-free interface provides users with real time sanity checking, and version control allowing edits to be easily tracked. The goal of this release is to further simplify how users create and manage vocabularies.
New features include:
SciBite's CTO James Malone explains how the semantic approach to using ontologies is essential in successfully training machine learning data sets. In this blog he discusses how Sherlock Holmes (amongst others) made an appearance when we looked to exploit the efforts of Wikipedia to identify articles relevant to the life science domain for a language model project.Read
SciBite CSO and Founder Lee Harland shares his views on why ontologies are relevant in a machine learning-centric world and are essential to help "clean up" scientific data in the Life Sciences industry.Read
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