A typo in an instrument field can cost you a week tracing bad data back to its source. This video shows how Tetra OS ties controlled vocabularies directly to your data's metadata, so when a value comes in wrong you can pull up the record and see exactly why: a mislabeled pipeline, bad source data, or someone just typing it in wrong.
The walkthrough covers both TetraScience-curated vocabularies, like instrument type, and vocabularies you bring in yourself, whether that's a formal ontology system or a spreadsheet of solvents from your lab. You'll see a new ingestion path get set up for a cell culture analyzer, with the controlled value selected before any data has even arrived, and how that same value carries into pipeline configuration so context gets captured right at the point of ingestion.
For teams running their own ontologies, there's a look at the API side: defining custom vocabularies, adding synonyms so a user's shorthand still maps back to the right canonical term, and versioning value sets so app developers can target a specific one as it evolves. The platform stays open to whatever ontology tools your organization already runs, while keeping everything governed and mapped through one semantic layer underneath.