The Constellation Query Language

Heath, Clifford

doi:10.1007/978-3-642-05290-3_84

Cited by 12 publications

(3 citation statements)

References 6 publications

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“…An activity affects the Fact Base (i.e., the true statements of the current World), asserting, retracting or reallocating Facts. Moreover, the activity input can be identified as the Query Result of a conceptual Query Schema (e.g., in Constellation Query Language [11] or ConQuer [12]) applied on the Fact Base. In Set Theory, these operations as well as the Query Results can all be represented as the application of set operators to the sets representing the Fact Base and the specified Set of Facts.…”

Section: Problem Analysismentioning

confidence: 99%

“…Although current results represent important cornerstones in the ORM conceptual modeling, their immediate applicability to large international projects has not been fully demonstrated yet, and an internal European Space Agency explorative research investigation was started to probe the ORM methodology for conceptual process modeling [8]. This paper summarizes some of the investigation's results on 1 the link between the process specification and the data specification, as a possible area of improvement with respect to the current practices [3][5] [9] [11]. Analogously to conceptual data modeling languages, a conceptual process modeling language must satisfy the eight criteria listed in Halpin's book [5].…”

Section: Introductionmentioning

confidence: 99%

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Referencing Capabilities for Collaborative Engineering of Conceptual Process Modeling with Object-Role Modeling

Gianni

Bocciarelli

D’Ambrogio

2014

2014 IEEE 23rd International WETICE Conference

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Conceptual modeling has been proved to bring tangible advantages as a mean to formalize specifications in collaborative multi-partner projects. Particularly, the ObjectRole Modeling language-the most prominent conceptual data modeling language-offers verbalization capabilities that ensure a common semantic understanding of the data specification, specifically for complex data systems and for non-native English speakers. However, ORM is primarily aimed at data specifications and has been more marginally used for process specifications. The paper reports part of the results on an experimental activity undertaken to probe the use of ORM for conceptual process modeling. In particular, the paper introduces the definitions of referencing capabilities for linking data models to the activity-the fundamental element of a process-models in ORM. Specifically, two new concepts have been identified as potentially necessary for supporting conceptual process modeling using ORM: Extended Facts, for distinguishing current Facts from potentially true Facts; and Set of Facts for indicating the Extended Facts affected by the activity. An activity schema definition also shows how these concepts can support the definition of an ORM interlayer for conceptual process modeling.

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Section: Problem Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Referencing Capabilities for Collaborative Engineering of Conceptual Process Modeling with Object-Role Modeling

Gianni

Bocciarelli

D’Ambrogio

2014

2014 IEEE 23rd International WETICE Conference

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“…The Constellation Query Language (CQL) (Heath, 2009) is under development in the Active Facts tool to provide modeling and conceptual query functionality for ORM. The DogmaModeler tool has been extended to verbalize basic ORM constraints in ten languages (English, Dutch, German, Italian, Spanish, Catalan, French, Lithuanian, Russian and Arabic) (Jarrar, Kent, & Dogilli, 2006), but the verbalizations generated are not always grammatically correct (e.g.…”

Section: Related Researchmentioning

confidence: 99%

Automated Verbalization of ORM Models in Malay and Mandarin

Halpin

Lim

2016

International Journal of Information System Modeling and Design

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Fact-oriented modeling approaches such as Object-Role Modeling (ORM) include a rich graphical notation for capturing business constraints, allowing modelers to visualize fine details of their data models. These data models should be validated with domain experts who best understand the business requirements, even if unfamiliar with the graphical notation. Hence, the data models are best validated by verbalizing the models in a controlled natural language, and by populating the relevant fact types with examples. Comparatively little support exists for verbalizing fact-based models in non-English languages, especially Asian languages. This paper describes the authors' work on verbalizing ORM models in Bahasa Melayu (Malay) and Mandarin. The authors specify some typical transformation patterns, discuss features of these languages requiring special treatment (e.g. noun classifiers, repositioning of modal operators, and different uses for terms equivalent to “who” and “that” in English), and describe their current implementation efforts.

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