The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
An ontological analysis of the relationship construct in conceptual modeling
Open accessAbstract
Conceptual models or semantic data models were developed to capture the meaning of an application domain as perceived by someone. Moreover, concepts employed in semantic data models have recently been adopted in object-oriented approaches to systems analysis and design. To employ conceptual modeling constructs effectively, their meanings have to be defined rigorously. Often, however, rigorous definitions of these constructs are missing. This situation occurs especially in the case of the relationship construct. Empirical evidence shows that use of relationships is often problematical as a way of communicating the meaning of an application domain. For example, users of conceptual modeling methodologies are frequently confused about whether to show an association between things via a relationship, an entity, or an attribute. Because conceptual models are intended to capture knowledge about a real-world domain, we take the view that the meaning of modeling constructs should be sought in models of reality. Accordingly, we use ontology, which is the branch of philosophy dealing with models of reality, to analyze the meaning of common conceptual modeling constructs. Our analysis provides a precise definition of several conceptual modeling constructs. Based on our analysis, we derive rules for the use of relationships in entity-relationship conceptual modeling. Moreover, we show how the rules resolve ambiguities that exist in current practice and how they can enrich the capacity of an entity-relationship conceptual model to capture knowledge about an application domain.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Entity Relationship Model — Toward a Unified View of Data
Chen, P. P.-S. (2002) · Software Pioneers · doi:10.1007/978-3-642-59412-0_18 · Cited by 5,751
The entity-relationship model—toward a unified view of data
Chen, P. P.-S. (1976) · ACM Transactions on Database Systems · doi:10.1145/320434.320440 · Cited by 4,708
Object-oriented modeling and design
Rumbaugh, J. E., Blaha, M. R., Premerlani, W. J., Eddy, F., & Lorensen, W. E. (1991) · CERN Document Server (European Organization for Nuclear Research) · Cited by 4,435
Introduction to Database Systems
(2006) · Foundations of Database Design · doi:10.1201/9781420003345.ch1 · Cited by 3,521
Fundamentals of Database Systems
Elmasri, R. A., & Navathe, S. B. (1989) · Cited by 3,141
(2007) · Software Solutions for Engineers and Scientists · doi:10.1201/9781420043037.ch29 · Cited by 1,631
Anchoring Data Quality Dimensions in Ontological Foundations
Wand, Y., & Wang, R. Y. (1996) · Communications of the ACM · doi:10.1145/240455.240479 · Cited by 1,479
Self-citationFundamentals of Data Base Systems
Deen, S. M. (1977) · doi:10.1007/978-1-349-15843-0 · Cited by 1,279
Formal ontology, conceptual analysis and knowledge representation
Guarino, N. (1995) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1995.1066 · Cited by 1,197
Simons, P. (2000) · DIAL (Catholic University of Leuven) · doi:10.1093/acprof:oso/9780199241460.001.0001 · Cited by 973
Cited by
Nevo, S., & Wade, M. R. (2010) · MIS Quarterly · doi:10.2307/20721419 · Cited by 517
Theory-oriented software engineering
Stol, K.-J., & Fitzgerald, B. (2015) · Science of Computer Programming · doi:10.1016/j.scico.2014.11.010 · Cited by 63
Metadata
- Authors
- Wand, Y., Storey, V. C., & Weber, R.
- Venue
- ACM Transactions on Database Systems
- Published
- 1999-12
- Volume
- 24
- Issue
- 4
- Pages
- 494-528
- ISSN
- 0362-5915 (ISSN-L)
- 1557-4644
- OpenAlex
- W2093823648
- Cited by
- 411
- References
- 33
- FWCI
- 17.55
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An ontological analysis of the relationship construct in conceptual modeling. https://app.cochat.ai/papers/10.1145/331983.331989
- The paper
- Wand, Y., Storey, V. C., & Weber, R. (1999). An ontological analysis of the relationship construct in conceptual modeling. ACM Transactions on Database Systems. https://doi.org/10.1145/331983.331989
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.