Cognition and Modeling: Foundations for Research and Practice (original) (raw)
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2005
In this paper we present a framework for the evaluation and (re)design of modeling languages. We focus here on the evaluation of the suitability of a language to model a set or real-world phenomena in a given domain. In our approach, this property can be systematically evaluated by comparing the level of homomorphism between a concrete representation of the worldview underlying the language (captured in a metamodel of the language), with an explicit and formal representation of a conceptualization of that domain (a reference ontology). The framework proposed comprises a number of properties that must be reinforced for an isomorphism to take place between these two entities. In order to illustrate the approach proposed, we evaluate and extend a fragment of the UML static metamodel for the purpose of conceptual modeling, by comparing it with an excerpt of a philosophically and cognitive well-founded reference ontology.
Using a Common-Sense Realistic Ontology: Making Data Models
2005
This chapter examines the following question: "How well do data models map the world?" Data modelling languages are used in today's information systems engineering environments to model reality. Many have a degree of hype surrounding their quality and applicability with narrow and specific justification often given in support of one over another. We want to more deeply understand the fundamental nature of data modelling languages. We thus propose a theory, based on ontology, that should allow us to understand, compare, evaluate, and strengthen data modelling languages. We then introduce Chisholm's ontology and apply methods to analyse some data modelling languages using it. We find a good degree of overlap between all of the data modelling languages analysed and the core concepts of Chisholm's ontology, and conclude that the data modelling
On ontology, ontologies, conceptualizations, modeling languages, and (meta) models
In philosophy, the term ontology has been used since the 17 century to refer both to a philosophical discipline (Ontology with a capital “O”), and as a domain-independent system of categories that can be used in the conceptualization of domain-specific scientific theories. In the past decades there has been a growing interest in the subject of ontology in computer and information sciences. In the last few years, this interest has expanded considerably in the context of the Semantic Web and MDA (Model-Driven Architecture) research efforts, and due to the role ontologies are perceived to play in these initiatives. In this paper, we explore the relations between Ontology and ontologies in the philosophical sense with domain ontologies in computer science. Moreover, we elaborate on formal characterizations for the notions of ontology, conceptualization and metamodel, as well as on the relations between these notions. Additionally, we discuss a set of criteria that a modeling language should meet in order to be considered a suitable language to model phenomena in a given domain, and present a systematic framework for language evaluation and design. Furthermore, we argue for the importance of ontology in both philosophical senses aforementioned for designing and evaluating a suitable general ontology representation language, and we address the question whether the so-called Ontology Web languages can be considered as suitable general ontology representation languages. Finally, we motivate the need for two complementary classes of modeling languages in Ontology Engineering addressing two separate sets of concerns.
A proposed Ontology to support Modeling Diagrams
2010
This paper investigates ontology. Ontology exhibits enormous potential in making software more efficient, adaptive, and intelligent. It is recognized as one of the areas which will bring the next breakthrough in software development. Ontology specifies a rich description of the terminology, concepts and properties explicitly defining concepts. Since understanding concepts and terms is one of the difficulties in modeling diagrams, this paper suggests an ontology aiming to identify some heavily used modelling diagrams concepts to make them
Syntax, Semantics and Pragmatics of Conceptual Modelling
Lecture Notes in Computer Science, 2012
Models, modelling languages, modelling frameworks and their background have dominated conceptual modelling research and information systems engineering for last four decades. Conceptual models are mediators between the application world and the implementation or system world. Currently conceptual modelling is rather a craft and at the best an art. We target on a science and culture of conceptual modelling.
Using Ontology Languages for Conceptual Modeling
Journal of Database Management, 2010
Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper pres...
What practitioners really want: requirements for visual notations in conceptual modeling
Software & Systems Modeling, 2018
This research was aimed at eliciting the requirements of practitioners who use conceptual modeling in their professional work for the visual notations of modeling languages. While the use of conceptual modeling in practice has been addressed, what practitioners in fact require of the visual notation of the modeling languages they use has received little attention. This work was thus motivated by the need to understand to what extent practitioners' requirements are acknowledged and accommodated by visual notation research efforts. [Method:] A mixedmethod study was conducted, with a survey being offered over the course of several months to LinkedIn professional groups. The requirements included in the survey were based on a leading design theory for visual notations, the Physics of Notations (PoN). After preprocessing, 104 participant responses were analyzed. Data analysis included descriptive coding and qualitative analysis of purposes for modeling and additional requirements beyond the scope of visual design. Statistical and factorial analysis was used to explore potential correlations between the importance of different requirements as perceived by practitioners and the demographic factors (e.g., domain, purpose, topics). [Results:] The results indicate several correlations between demographic factors and the perceived importance of visual notation requirements, as well as differences in the perceived relative importance of different requirements for models used to communicate with model