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Part-whole relations in object-centered systems: An overview

Open access
Artale, Alessandro, Franconi, Enrico, Guarino, Nicola, Pazzi, Luca·1996·Data & Knowledge Engineering

Abstract

Abstract Knowledge bases, data bases and object-oriented systems (referred to in the paper as Object-Centered systems) all rely on attributes as the main construct used to associate properties to objects; among these, a fundamental role is played by the so-called part-whole relation. The representation of such structural information usually requires particular semantics together with specialized inference and update mechanisms, but rarely do current modelling formalisms and methodologies give it a specific, ‘first-class’ dignity. The main thesis of this paper is that the part-whole relation cannot simply be considered as an ordinary attribute: its specific ontological nature requires to be understood and integrated within data-modelling formalisms and methodologies. On the basis of such an ontological perspective, we survey the conceptual modelling issues involving part-whole relations, and the various modelling frameworks provided by knowledge representation and object-oriented formalisms.

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Metadata

Authors
Artale, A., Franconi, E., Guarino, N., & Pazzi, L.
Venue
Data & Knowledge Engineering
Publisher
Elsevier BV
Published
1996-11
Volume
20
Issue
3
Pages
347-383
ISSN
0169-023X (ISSN-L)
OpenAlex
W2030658843
Cited by
228
References
2
FWCI
15.38
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Part-whole relations in object-centered systems: An overview. https://app.cochat.ai/papers/10.1016/s0169-023x(96)00013-4
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Artale, A., Franconi, E., Guarino, N., & Pazzi, L. (1996). Part-whole relations in object-centered systems: An overview. Data & Knowledge Engineering. https://doi.org/10.1016/s0169-023x(96)00013-4

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.