Glossary

The words used in AI data deals.

Data manifests, trajectories, PII transformation, data broker registration. Each term gets a short definition.

What are expertise traces? An unsettled term, defined

Expertise traces is a marketing label for records of how professionals work: the steps taken, judgment calls made and checks run.

A data asset has two meanings.

A data broker collects personal information from multiple sources and sells it.

A data corpus for AI is data treated as one set.

A data lab is micro1's term for a company that supplies training data to AI models, sitting between data holders and AI labs.

A forward deployed engineer (FDE) works directly with a customer to understand problems and build solutions using that customer's data.

A rights holder in AI licensing is the party with authority to license content or data to an AI company.

A trajectory in AI is the record of steps an agent took while working on a task.

AI data governance is the rules and records for which data goes into an AI system and how to prove its origin.

An RL environment is a simulated workplace where an AI agent practices a task and gets scored on the result.

Data exhaust is data left as a by-product of online activity, behavior and transactions.

Data monetization is using data to produce measurable economic value.

Data provenance is the record of where data came from, how it was made and who handled it.

Human data is data people produce on request to train and test AI models, like expert answers, grading and rankings.

Operational data in AI deals is the records a company produces while working, like chat, email, tickets, documents and CRM entries.

Referential integrity is the rule that every link between records points at a real record.

Synthetic data is made by an algorithm that copies patterns from real data.

Workflow data is the record of how work moved across tools, from request to deliverable.