# What is data provenance? Findem publishes a public search API over its indexed pages; the guide is at https://www.findem.ai/lazyweb/agent-access. Source: https://www.findem.ai/glossary/data-provenance Source observed: 2026-11-11T21:16:26.582Z Last checked: 2026-11-13T04:08:13.925+00:00 Indexed: 2026-11-11T21:23:55.245+00:00 --- --- title: "What is data provenance? Meaning and why it matters | Findem" description: "Data provenance is the record of where data came from and how it changed. See how it works, how it relates to lineage, and why it matters for hiring AI." url: "https://www.findem.ai/glossary/data-provenance" --- # What is data provenance? ← Back to glossary AI and people intelligence Data provenance is the record of where a piece of data came from and what happened to it along the way, including its original source, who or what created or changed it, and when. It lets people judge whether data can be trusted, trace an AI output back to its inputs, and correct errors at the source. ## How data provenance works The W3C, which sets web standards, defines provenance as "information about entities, activities, and people involved in producing a piece of data or thing, which can be used to form assessments about its quality, reliability or trustworthiness" ( [PROV-Overview](https://www.w3.org/TR/prov-overview/) ). NIST's glossary gives a shorter version from the NIST Privacy Framework: "metadata pertaining to the origination or source of specified data" ( [NIST CSRC](https://csrc.nist.gov/glossary/term/Provenance) ). The W3C's [PROV data model](https://www.w3.org/TR/prov-dm/) breaks provenance into a few core pieces: - **Entities:** The data itself, such as a job title on a profile. - **Activities:** The processes that created, used, or changed it, such as collecting, merging, or labeling, and when they happened. - **Agents:** The people, organizations, or software responsible for those activities. - **Derivations:** Which pieces of data were produced from which others. A provenance record lets someone follow a fact back through those steps. For a candidate profile, that might mean seeing which source a current title came from, when it was collected, and which records were merged to produce it. Usage varies around related terms. Some teams use data lineage for the path data takes through systems and transformations, and provenance for the broader record that includes origin and responsibility. Others use the two interchangeably. NIST's Generative AI Profile also separates data provenance, such as source, signatures, and versioning for the data behind an AI system, from content provenance, which tracks the origin of generated content ( [NIST AI 600-1](https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf) ). ## Why data provenance matters for talent teams People data is assembled from many sources, and a recommendation is only as trustworthy as the facts behind it. [Explainable AI](https://www.findem.ai/glossary/explainable-ai) shows a reviewer why a candidate was surfaced; provenance is what lets that reviewer check where the underlying evidence came from. It also matters when records from different sources are combined through [entity resolution](https://www.findem.ai/glossary/entity-resolution) or connected in a [knowledge graph](https://www.findem.ai/glossary/knowledge-graph): if a merge is wrong, provenance shows where to fix it. Regulators ask about origin too. For high-risk AI systems, which include AI used to recruit or select people ( [Annex III, point 4](https://ai-act-service-desk.ec.europa.eu/en/ai-act/annex-3) ), the EU AI Act requires data governance practices that cover "data collection processes and the origin of data, and in the case of personal data, the original purpose of the data collection" ( [Article 10](https://ai-act-service-desk.ec.europa.eu/en/ai-act/article-10) ). Under the [GDPR](https://eur-lex.europa.eu/eli/reg/2016/679/oj), Article 14 requires organizations that obtain personal data from someone other than the person it describes to tell that person which source it came from. This page is a general overview, not legal advice. When evaluating AI that works with people data, teams can ask: - **Source:** Which kinds of sources stand behind a profile or signal. - **Recency:** When each detail was last collected or verified. - **Changes:** Whether merges, corrections, and labels are recorded. - **Traceability:** Whether a reviewer can get from a recommendation to the evidence behind it. ## How Findem approaches data provenance Findem's [3D People Graph](https://www.findem.ai/why-findem/3d-data) resolves information from more than 100,000 sources, including GitHub, Stack Overflow, Crunchbase, and a customer's own ATS and CRM, into a single career view. Profiles are verified across sources and refreshed over time, and explainability sits behind every insight. Before expert labeling, Findem's [Labeling Engine](https://www.findem.ai/platform/data-labeling-engine) removes duplicates, noise, and outdated information to create a reliable foundation. The platform shows the logic and evidence behind its signals so people can examine and defend their choices. In [Findem Studio](https://www.findem.ai/studio), evidence is checked, conclusions are validated, and reasoning is shown before anyone acts. Findem's AI does not reject candidates or make hiring decisions, and people review results before they influence hiring decisions. Read more in [Responsible AI at Findem](https://www.findem.ai/why-findem/responsible-ai). ## Further reading - [Security & AI: Here's what HR leaders need to know](https://www.findem.ai/blog/ai-security-in-hr) - [AI governance in HR: A practical guide](https://www.findem.ai/blog/ai-governance-in-hr-guide) - [Purpose-built HR AI vs. general enterprise AI](https://www.findem.ai/blog/purpose-built-hr-ai-vs-general-enterprise-ai) ## Related terms - [Explainable AI](https://www.findem.ai/glossary/explainable-ai) - [Knowledge graph](https://www.findem.ai/glossary/knowledge-graph) - [Entity resolution](https://www.findem.ai/glossary/entity-resolution) - [Data enrichment](https://www.findem.ai/glossary/data-enrichment) - [EU AI Act](https://www.findem.ai/glossary/eu-ai-act) ## Sources - [PROV-Overview: An Overview of the PROV Family of Documents](https://www.w3.org/TR/prov-overview/) W3C Working Group Note, April 30, 2013 - [PROV-DM: The PROV Data Model](https://www.w3.org/TR/prov-dm/) W3C Recommendation, 2013 - [Provenance (glossary)](https://csrc.nist.gov/glossary/term/Provenance) NIST Computer Security Resource Center - [Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)](https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf) National Institute of Standards and Technology, July 2024 - [EU AI Act, Article 10: Data and data governance](https://ai-act-service-desk.ec.europa.eu/en/ai-act/article-10) European Commission AI Act Service Desk - [General Data Protection Regulation (EU) 2016/679, Article 14](https://eur-lex.europa.eu/eli/reg/2016/679/oj) EUR-Lex, Official Journal of the European Union - [3D People Graph](https://www.findem.ai/why-findem/3d-data) - [The People Intelligence Platform](https://www.findem.ai/platform) The People Intelligence Platform for people-centric work. Unify people and network data with Findem's AI people intelligence infrastructure to improve hiring, mobility, workforce planning, and talent decisions. [See the platform](https://www.findem.ai/platform) [Request a demo](https://www.findem.ai/request-demo) ## Frequently asked questions. **What is the difference between data provenance and data lineage?** Usage varies. Many teams use data lineage for the path data takes through systems and transformations, and data provenance for the broader record of where data originated, who changed it, and when. Some treat the two terms as the same thing. **What is an example of data provenance?** A candidate profile that shows where its current job title came from, when that detail was collected, and which records were merged to build the profile. If the title turns out to be wrong, a reviewer can see which source supplied it and correct it there. **Why does data provenance matter for AI?** An AI system's outputs depend on its data. Provenance lets people judge data quality and trustworthiness, trace an output back to its inputs, and fix errors at the source. The EU AI Act requires high-risk AI data governance to cover data collection processes and the origin of data. **What is the W3C PROV standard?** PROV is a family of W3C documents, published in 2013, for describing and exchanging provenance information. Its data model, PROV-DM, describes provenance in terms of entities, the activities that created or changed them, and the agents responsible, so different systems can share provenance in a common format. **How does Findem handle data provenance?** Findem's 3D People Graph resolves information from more than 100,000 sources into a single career view, with profiles verified across sources and refreshed over time. The platform shows the logic and evidence behind its signals, and people review results before they influence hiring decisions. --- [Read this page’s summary](https://www.findem.ai/lazyweb/api/public/v1/page-tldr?url=https%3A%2F%2Fwww.findem.ai%2Fglossary%2Fdata-provenance&trace=t_9544b0955d7a) ## Ask a follow-up about this page Need a more specific answer? Ask the exact question you have. It returns a fresh, cited answer from Findem’s knowledge base. No account or API key required. Open this URL with your own question, URL-encoded. Include your question in q. All research inputs are optional; no account or setup. `GET https://www.findem.ai/lazyweb/agent/faq?q={question}&trace=t_9544b0955d7a` [Tool guide and examples](https://www.findem.ai/lazyweb/agent-access) · [OpenAPI](https://www.findem.ai/lazyweb/api/public/v1/openapi.json) · [Page TLDR form](https://www.findem.ai/lazyweb/agent-tools/page-tldr?url=https%3A%2F%2Fwww.findem.ai%2Fglossary%2Fdata-provenance). 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