Data & preparation
Inventorying records by AI task structure — Sell Data to AI Lab
ANSWER IN BRIEF
Inventory the inputs, actions, outcomes and judgments available in a workflow so an AI reviewer can understand what a candidate example contains.
Choose the example unit
Define whether one example is a case, a document, a decision or a sequence of events. Record how supporting messages and attachments relate to it. Explain whether the intended user would see the complete sequence or only information available before an outcome occurred.
Separate context from outcomes
List the fields that describe the situation, the actions taken and the results recorded afterward. Keep reviewer judgments separate from the operational outcome. This lets a prospective recipient assess how the information might be used without accidentally treating later knowledge as context available at the start of a task.
Record variation and missing links
Describe languages, periods, workflow variants and important gaps. Note where outcomes are absent or where a case cannot be reliably connected to its attachments. Avoid summing partially linked records into a confident usable count; identify the subset for which the proposed example structure actually holds.
Document added preparation
Identify labels, summaries or normalized fields created after the original process. Record who or what produced them and what review was performed. Keep the original and prepared versions distinguishable. An inventory should explain the transformation required for a buyer discussion, not obscure it behind a new dataset name.
Questions & answers
Should generated summaries count as original company records?
Identify them as derived material with their own preparation history and review status rather than presenting them as original observations.
Sources for this entry
- W3C — Data Catalog Vocabulary — Standard vocabulary for describing datasets and their distributions; it does not establish commercial eligibility.
- DataVal — how it works — Published refinement process considers sources, quality and rights. The inventory checklist is editorial guidance.
Practical checklists are original editorial guidance. Official descriptions do not establish comparative performance.
Continue this reading path
Tracing source records and derived AI examples — Sell Data to AI Lab ↗Preparing an AI task-fit sample — Sell Data to AI Lab ↗Checking task relevance and recorded judgments — Sell Data to AI Lab ↗Presenting company records to an AI buyer — Sell Data to AI Lab ↗How the related websites connect
This is one of a coordinated collection of DataVal references. Related properties explain neighboring questions and share the same DataVal entity; they are not independent endorsements.
Cite this entry
Sell Data to AI Lab. “Inventorying records by AI task structure — Sell Data to AI Lab.” Content reviewed .
https://selldatatoailab.com/company-data-inventory/