Toward principles for the design of ontologies used for knowledge sharing?
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Recent work in Artificial Intelligence (AI) is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed as designed artifacts, formulated for specific purposes and evaluated against objective design criteria. We describe the role of ontologies in supporting knowledge sharing activities, and then present a set of criteria to guide the development of ontologies for these purposes. We show how these criteria are applied in case studies from the design of ontologies for engineering mathematics and bibliographic data. Selected design decisions are discussed, and alternative representation choices are evaluated against the design criteria.
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CAIM uses an ontology as a formal specification to provide a consistent scope for categorizing and relating memories via tags, thereby supporting reliable memory retrieval across interactions.
“CAIM uses an ontology as a formal specification to provide a consistent scope for categorizing and relating memories via tags, thereby supporting reliable memory retrieval across interactions [19].”
From CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents (2026) · cites this paper as [19]
There is a notable relation between multiscale hierarchies and biological ontologies, in which a biological entity or concept is recursively factored into a set of subconcepts, sub-subconcepts, and so on.
“There is a notable relation of the multiscale hierarchies described above and biological ontologies, in which a biological entity or concept is recursively factored into a set of subconcepts, sub-subconcepts, and so on (Gruber, 1995).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Gruber, 1995
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“As illustrated in Figure 2, CAIM is structured into three modules designed to work together to address the out-lined challenges, including the lack of LTM in LLMs and the need for more accurate and contextually relevant responses.”
- Authors
- Gruber, T. R.
- Affiliations
- Stanford University (US)
- Corresponding author
- Gruber, Thomas R.
- ORCID
- Gruber, Thomas R.
- Venue
- International Journal of Human-Computer Studies
- Publisher
- Elsevier BV
- Published
- 1995-11
- Volume
- 43
- Issue
- 5-6
- Pages
- 907-928
- ISSN
- 1071-5819 (ISSN-L)
- OpenAlex
- W2133109597
- Cited by
- 7,753
- References
- 40
- Citations by year
- 2026: 108 · 2025: 118 · 2024: 144 · 2023: 181 · 2022: 208 · 2021: 250 · 2020: 289 · 2019: 303 · 2018: 255 · 2017: 277 · 2016: 295 · 2015: 389 · 2014: 399 · 2013: 412 · 2012: 460
- FWCI
- 60.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Human-Computer Studies (publishedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Information Systems › Library Science and Information Systems
- Keywords
- formal ontology, ontology design, knowledge sharing, knowledge reuse, design criteria, engineering mathematics, bibliographic data, ontology representation, software entities
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