Copyright © 2024 the Contributors to the AI Technology Concepts Specification, published by the Data Privacy Vocabularies and Controls Community Group under the W3C Community Final Specification Agreement (FSA). A human-readable summary is available.
The AI extension extends the Data Privacy Vocabulary (DPV) Specification and its Technology concepts for DPV extension to represent AI techniques, applications, risks, and mitigations. The namespace for terms in ai
is https://www.w3id.org/dpv/ai#
. The suggested prefix for the namespace is ai
. The AI vocabulary and its documentation are available on GitHub.
This specification was published by the Data Privacy Vocabularies and Controls Community Group. It is not a W3C Standard nor is it on the W3C Standards Track. Please note that under the W3C Community Final Specification Agreement (FSA) other conditions apply. Learn more about W3C Community and Business Groups.
Contributing: The DPVCG welcomes participation to improve the DPV and associated resources, including expansion or refinement of concepts, requesting information and applications, and addressing open issues. See contributing guide for further information.
GitHub Issues are preferred for discussion of this specification.
Data Privacy Vocabulary (DPV) Specification: is the base/core specification for the 'Data Privacy Vocabulary', which is extended for Personal Data [PD], Locations [LOC], Risk Management [RISK], Technology [TECH], and [AI]. Specific [LEGAL] extensions are also provided which model jurisdiction specific regulations and concepts . To support understanding and applications of [DPV], various guides and resources [GUIDES] are provided, including a [PRIMER]. A Search Index of all concepts from DPV and extensions is available.
[DPV] and related resources are published on GitHub. For a general overview of the Data Protection Vocabularies and Controls Community Group [DPVCG], its history, deliverables, and activities - refer to DPVCG Website. For meetings, see the DPVCG calendar.
The peer-reviewed article “Creating A Vocabulary for Data Privacy” presents a historical overview of the DPVCG, and describes the methodology and structure of the DPV along with describing its creation. An open-access version can be accessed here, here, and here. The article Data Privacy Vocabulary (DPV) - Version 2, accepted for presentation at the 23rd International Semantic Web Conference (ISWC 2024), describes the changes made in DPV v2.
The AI Technology concepts for DPV extension is currently under development. It further extends the [TECH] extension to represent concepts associated with AI, and will provide:
The AI extension will be created based on the existing AI Risk Ontology (AIRO) and Vocabulary of AI Risks (VAIR), as well as the Artificial Intelligence Act (AI Act), ISO/IEC 22989:2022 Artificial intelligence concepts and terminology, and the AI Watch taxonomy.
See examples of Techniques in VAIR.
See examples of Capabilities in VAIR.
See examples of Risks in VAIR.
See examples of Risk Measures in VAIR.
Term | AI | Prefix | ai |
---|---|---|---|
Label | Artificial Intelligence (AI) | ||
IRI | https://w3id.org/dpv/ai#AI | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | dpv:Technology | ||
Object of relation | dpv:isImplementedUsingTechnology | ||
Definition | A technical and scientific field devoted to the engineered system that generates outputs such as content, forecasts, recommendations or decisions for a given set of human-defined objectives | ||
Usage Note | This concept is a stub | ||
Source | |||
Date Created | 2024-04-28 | ||
See More: | section CORE in AI |
Term | AISystem | Prefix | ai |
---|---|---|---|
Label | AI System | ||
IRI | https://w3id.org/dpv/ai#AISystem | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | ai:AI → dpv:Technology | ||
Object of relation | dpv:isImplementedUsingTechnology | ||
Definition | OECD 2024 definition: An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. ISO/IEC 22989:2023 definition: engineered system that generates outputs such as content, forecasts, recommendations or decisions for a given set of human-defined objectives | ||
Source | OECD, ISO/IEC 22989:2023 | ||
Date Created | 2024-05-17 | ||
See More: | section CORE in AI |
Term | Capability | Prefix | ai |
---|---|---|---|
Label | Capability | ||
IRI | https://w3id.org/dpv/ai#Capability | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | ai:AI → dpv:Technology | ||
Object of relation | dpv:isImplementedUsingTechnology | ||
Definition | Capability or use of AI to achieve a technical goal or objective | ||
Usage Note | This concept is a stub | ||
Date Created | 2024-04-28 | ||
See More: | section CAPABILITIES in AI |
Term | Measure | Prefix | ai |
---|---|---|---|
Label | Measure | ||
IRI | https://w3id.org/dpv/ai#Measure | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | dpv:RiskMitigationMeasure → dpv:TechnicalOrganisationalMeasure | ||
Object of relation | dpv:hasTechnicalOrganisationalMeasure, dpv:isMitigatedByMeasure | ||
Definition | Measure to address risk associated with AI Systems | ||
Usage Note | This concept is a stub | ||
Date Created | 2024-04-28 | ||
See More: | section MEASURES in AI |
Term | Model | Prefix | ai |
---|---|---|---|
Label | Model | ||
IRI | https://w3id.org/dpv/ai#Model | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | ai:AI → dpv:Technology | ||
Object of relation | dpv:isImplementedUsingTechnology | ||
Definition | Physical, mathematical or otherwise logical representation of a system, entity, phenomenon, process or data | ||
Source | |||
Date Created | 2024-05-17 | ||
See More: | section CORE in AI |
Term | Risk | Prefix | ai |
---|---|---|---|
Label | Risk | ||
IRI | https://w3id.org/dpv/ai#Risk | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | dpv:Risk | ||
Object of relation | dpv:hasRisk, dpv:isResidualRiskOf, dpv:mitigatesRisk | ||
Definition | Risk associated with development, use, or operation of AI systems | ||
Usage Note | This concept is a stub | ||
Date Created | 2024-04-28 | ||
See More: | section RISKS in AI |
Term | Technique | Prefix | ai |
---|---|---|---|
Label | Technique | ||
IRI | https://w3id.org/dpv/ai#Technique | ||
Type | rdfs:Class, skos:Concept | ||
Broader/Parent types | ai:AI → dpv:Technology | ||
Object of relation | dpv:isImplementedUsingTechnology | ||
Definition | Techniques for using or applying AI | ||
Usage Note | This concept is a stub | ||
Date Created | 2024-04-28 | ||
See More: | section TECHNIQUES in AI |
DPV uses the following terms from [RDF] and [RDFS] with their defined meanings:
The following external concepts are re-used within DPV:
The following people have contributed to this vocabulary. The names are ordered alphabetically. The affiliations are informative do not represent formal endorsements. Affiliations may be outdated. The list is generated automatically from the contributors listed for defined concepts.
The DPVCG was established as part of the SPECIAL H2020 Project, which received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731601 from 2017 to 2019.
Harshvardhan J. Pandit was funded to work on DPV from 2020 to 2022 by the Irish Research Council's Government of Ireland Postdoctoral Fellowship Grant#GOIPD/2020/790.
The ADAPT SFI Centre for Digital Media Technology is funded by Science Foundation Ireland through the SFI Research Centres Programme and is co-funded under the European Regional Development Fund (ERDF) through Grant#13/RC/2106 (2018 to 2020) and Grant#13/RC/2106_P2 (2021 onwards).
The contributions of Delaram Golpayegani have received funding through the PROTECT ITN Project from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813497.
The contributions of Harshvardhan J. Pandit and Delaram Golpayegani have been made with the financial support of Science Foundation Ireland under Grant Agreement No. 13/RC/2106_P2 at the ADAPT SFI Research Centre.