Name
Abstract | ||
|---|---|---|
For successful information systems development, conceptual data modelling is essential. Nowadays many conceptual data modelling techniques exist. In-depth comparisons of concepts of these techniques are very difficult as the mathematical formalizations of these techniques, if they exist at all, are very different. Consequently, there is a need for a unifying formal framework providing a sufficiently high level of abstraction. In this paper the use of category theory for this purpose is addressed. Well-known conceptual data modelling concepts, such as relationship types, generalization, specialization, collection types and constraint types, such as the total role constraint and the uniqueness constraint, are discussed from a categorical point of view. An important advantage of this framework is its 'configurable semantics'. Features such as null values, uncertainty and temporal behavior can be added by selecting appropriate instance categories. The addition of these features usually requires a complete redesign of the formalization in traditional set-based approaches to semantics. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1093/comjnl/39.3.215 | COMPUTER JOURNAL |
Keywords | Field | DocType |
conceptual data model,data modelling,category theory | Information system,Data modeling,Abstraction,Relational database,Computer science,Categorical variable,Theoretical computer science,Category theory,Semantics,Conceptual model (computer science) | Journal |
Volume | Issue | ISSN |
39 | 3 | 0010-4620 |
Citations | PageRank | References |
14 | 2.14 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arthur H. M. Ter Hofstede | 1 | 14 | 2.14 |
| E. Lippe | 2 | 49 | 7.70 |
| p j m frederiks | 3 | 61 | 5.42 |