European Conference on Information Systems ( ECIS ) 2002 Using Psychology to Understand Conceptual Modelling (original) (raw)

Using Psychology to Understand Conceptual Modeling

… on Information Systems (ECIS 2002), Poland, 2002

There have been a growing number of publications suggesting that philosophical ontologies will define a rigorous basis for conceptual modelling, particularly for data modelling methods and notations. An examination of an underlying psychological assumption of the conceptual modelling process is used to show that philosophical ontologies are being used as a 'telescope' to view the products of yet another 'telescope' and this undermines their reliability by being too far removed from the actual modelling process. An ontology of conceptual structure, derived through linguistic analysis provides a psychologically realistic alternative to the philosophical ontologies that is as close to its mental interpretation as possible and is a more promising approach to understanding the modelling process.

On the Role of Conceptual Models in Information Systems Research - From Engineering to Research

Conceptual modelling deals with the process of building or interpreting a conceptual model. Stakeholders use the resulting model to reason and communicate about a domain in order to improve their common understanding of it. From this perspective, conceptual modelling and conceptual models are subjects for information systems research. In this paper, we argue that this engineering-driven view on conceptual models is only one possible perspective for information systems research. Based on language critique, we show how conceptual models can be used not as a subject of but as an important and useful instrument for information systems research. Conceptual models help to structure and formalize the interpretation of a subjective understanding in a domain of focus. We propose a research approach which is based on three roles that the researcher adopts and show how conceptual models are a useful source of knowledge and an instrument for interpretation respectively. We combine our view with an existing framework for information systems research and reinterpret existing research as matching to our approach.

Terminological concept modelling and conceptual data modelling

International Journal of Metadata, Semantics and Ontologies, 2009

Ontologies are useful for many purposes. The use of an ontology is, for example, crucial for writing consistent definitions of concepts within a specific domain. In this paper, we will argue that the principles of rigorous terminology work are useful for building consistent ontologies. In many cases, developers of IT systems encounter severe problems, because they neglect the necessity of developing a proper ontology (concept model) before they develop a conceptual data model as a basis for an IT system. In this paper, we will argue that the development of an ontology is crucial for setting up a conceptual data model, and therefore it should always be added as an initial stage to data modelling. Also we will give some examples of the mapping between ontologies and conceptual data models. Future research will reveal to what extent it will be possible to set up rules for automatic mapping of concepts of an ontology into classes and attributes of a conceptual data model. the development of ontologies as a basis for large IT systems and metadata taxonomies. She is chairman of SC 3, Systems to manage terminology, knowledge and content in ISO TC 37 Terminology and other language resources.

Ontological foundations for conceptual modelling

The objective of this issue entitled “Ontological Foundations for Conceptual Modeling” is to collect innovative and high-quality research contributions regarding the role played by the aforementioned the- oretical disciplines to the foundations of conceptual modeling. The issue should be of interest to several academic communities, including primarily the communities of applied ontology and conceptual mod- eling, but also the ones of database and information systems design, knowledge engineering, semantic interoperability and information integration, enterprise modeling, agent and object orientation, software engineering (in particular domain and requirements engineering), natural-language processing, business rules and model-driven engineering.

In the Defense of Ontological Foundations for Conceptual Modeling

In his article entitled “On Ontological Foundations of Conceptual Modeling” (henceforth OFCM), Boris Wyssusek reviews several approaches that have the common objective of investigating how results from areas such as formal ontology in philosophy, cognitive science, semiotics and linguistics can be employed in the construction of a well-founded theoretical basis for the discipline of conceptual modeling in computer science. Despite the title of his essay, which may let the reader think of an analysis of what the ontological foundations of conceptual modeling are, Wyssusek wonders whether the very idea makes sense, concluding very negatively that “the project of ontology-based conceptual modeling appears to be impossible in principle”. We shall bring here arguments against such conclusion, hoping to convince the readers that the ontology-driven approach to conceptual modeling is well and alive, and that it dramatically improves the quality of information systems.

Applying ontology-based rules to conceptual modeling: a reflection on modeling decision making

2007

Abstract Conceptual modeling represents a domain independently of implementation considerations for purposes of understanding the problem at hand and communicating about it. However, different people may construct different models given the same domain. Variations among correct models, while known and familiar in practice, have hardly been investigated in the literature. Their roots are in the decisions made during the modeling process, where modelers face the need to map reality into modeling constructs.

An ontological analysis of the relationship construct in conceptual modeling

ACM Transactions on Database Systems, 1999

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.