DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering
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Abstract (arXiv)
DOLCE, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. DOLCE is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. DOLCE clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, DOLCE is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years DOLCE has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 0 of its 38 references that are in the map. First posted on arXiv 3 Aug 2023.
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Citing papers per year: 2024: 2; 2025: 5; 2026: 4.
11 papers.
- 2026Agentic Business Process Management: A Research Manifestocited by 7
- 2026Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agentscited by 3
- 2026The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labscited by 3
- 2025Procedural Knowledge Ontology (PKO)cited by 2
- 2025KROMA: Ontology Matching with Knowledge Retrieval and Large Language Modelscited by 2
- 2025Investigating Language Model Capabilities to Represent and Process Formal Knowledge: A Preliminary Study to Assist Ontology Engineeringcited by 2
- 2024EFO: the Emotion Frame Ontologycited by 1
- 2024Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotatecited by 0
- 2025Ontological foundations for contrastive explanatory narration of robot planscited by 0
- 2025AI- and Ontology-Based Enhancements to FMEA for Advanced Systems Engineering: Current Developments and Future Directionscited by 0
- 2026Knowledge Graph Re-engineering Along the Ontological Continuum (extended version)cited by 0
- 2026Knowledge Graph Re-engineering Along the Ontological Continuum (extended version)21 May 2026
- 2026The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labs2 Apr 2026
- 2026Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents1 Apr 2026
- 2026Agentic Business Process Management: A Research Manifesto19 Mar 2026
- 2025AI- and Ontology-Based Enhancements to FMEA for Advanced Systems Engineering: Current Developments and Future Directions21 Nov 2025
- 2025Ontological foundations for contrastive explanatory narration of robot plans26 Sep 2025
- 2025Investigating Language Model Capabilities to Represent and Process Formal Knowledge: A Preliminary Study to Assist Ontology Engineering12 Sep 2025
- 2025KROMA: Ontology Matching with Knowledge Retrieval and Large Language Models18 Jul 2025
- 2025Procedural Knowledge Ontology (PKO)26 Mar 2025
- 2024Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotate10 Jun 2024
- 2024EFO: the Emotion Frame Ontology19 Jan 2024