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:
Read more about VET at https://www.scibite.com/platform/centree/vet/ or download the datasheet https://www.scibite.com/library-items/vet-datasheet/.
SciBite is an award-winning award-winning semantic software company offering an ontology-led approach to transforming unstructured content into machine-readable clean data. Supporting the top 20 pharma with use cases across life sciences, SciBite empowers customers with a suite of fast, flexible, deployable API technologies, making it a critical component in scientific data-led strategies. Headquartered in the UK, we support our global customer base through additional sites in the US and Japan.
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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