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| Auteurs principaux: | , , , |
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| Format: | Preprint |
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2025
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| Accès en ligne: | https://arxiv.org/abs/2509.01617 |
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| _version_ | 1866914017024409600 |
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| author | Partridge, Chris Mitchell, Andrew de Cesare, Sergio Soto, Oscar Xiberta |
| author_facet | Partridge, Chris Mitchell, Andrew de Cesare, Sergio Soto, Oscar Xiberta |
| contents | If one looks at contemporary mainstream development practices for conceptual modelling in computer science, these so clearly focus on a conceptual schema completely separated from its information base that the conceptual schema is often just called the conceptual model. These schema-centric practices are crystallized in almost every database textbook. We call this strong, almost universal, bias towards conceptual schemas the schema turn. The focus of this paper is on disentangling this turn within (computer science) conceptual modeling. It aims to shed some light on how it emerged and so show that it is not fundamental. To show that modern technology enables the adoption of an inclusive schema-and-base conceptual modelling approach, which in turn enables more automated, and empirically motivated practices. And to show, more generally, the space of possible conceptual modelling practices is wider than currently assumed. It also uses the example of bCLEARer to show that the implementations in this wider space will probably need to rely on new pipeline-based conceptual modelling techniques. So, it is possible that the schema turn's complete exclusion of the information base could be merely a temporary evolutionary detour. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01617 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Disentangling the schema turn: Restoring the information base to conceptual modelling Partridge, Chris Mitchell, Andrew de Cesare, Sergio Soto, Oscar Xiberta Databases Artificial Intelligence Software Engineering D.2.10 If one looks at contemporary mainstream development practices for conceptual modelling in computer science, these so clearly focus on a conceptual schema completely separated from its information base that the conceptual schema is often just called the conceptual model. These schema-centric practices are crystallized in almost every database textbook. We call this strong, almost universal, bias towards conceptual schemas the schema turn. The focus of this paper is on disentangling this turn within (computer science) conceptual modeling. It aims to shed some light on how it emerged and so show that it is not fundamental. To show that modern technology enables the adoption of an inclusive schema-and-base conceptual modelling approach, which in turn enables more automated, and empirically motivated practices. And to show, more generally, the space of possible conceptual modelling practices is wider than currently assumed. It also uses the example of bCLEARer to show that the implementations in this wider space will probably need to rely on new pipeline-based conceptual modelling techniques. So, it is possible that the schema turn's complete exclusion of the information base could be merely a temporary evolutionary detour. |
| title | Disentangling the schema turn: Restoring the information base to conceptual modelling |
| topic | Databases Artificial Intelligence Software Engineering D.2.10 |
| url | https://arxiv.org/abs/2509.01617 |