Learning The Differences Between Ontologies and Conceptual Schemas Through Ontology-Driven Information Systems.

In the traditional systems modeling approach, the modeler is required to capture a user\u27s view of some domain in a formal conceptual schema. The designer\u27s conceptualization may or may not match with the user\u27s conceptualization. One of the reasons for these conflicts is the lack of an initial agreement among users and modelers concerning the concepts belonging to the domain. Such an agreement could be facilitated by means of an ontology. If the ontology is previously constructed and formalized so that it can be shared by the modeler and the user in the development process, such conflicts would be less likely to happen. Following up on that, a number of investigators have suggested that those working on information systems should make use of commonly held, formally defined ontologies that would constrain and direct the design, development, and use of information systems - thus avoiding the above mentioned difficulties. Whether ontologies represent a significant advance from the more traditional conceptual schemas has been challenged by some researchers. We review and summarize some major themes of this complex discussion. While recognizing the commonalities and historical continuities between conceptual schemas and ontologies, we think that there is an important emerging distinction that should not be obscured and should guide future developments. In particular, we propose that the notions of conceptual schemas and ontologies be distinguished so as to play essentially different roles for the developers and users of information systems. We first suggest that ontologies and conceptual schemas belong to two different epistemic levels. They have different objects and are created with different objectives. Our proposal is that ontologies should deal with general assumptions concerning the explanatory invariants of a domain - those that provide a framework enabling understanding and explanation of data across all domains inviting explanation and understanding. Conceptual schemas, on the other hand, should address the relation between such general explanatory categories and the facts that exemplify them in a particular domain (e.g., the contents of the database). In contrast to ontologies, conceptual schemas would involve specification of the meaning of the explanatory categories for a particular domain as well as the consequent dimensions of possible variation among the relevant data of a given domain. Accordingly, the conceptual schema makes possible both the intelligibility and the measurement of those facts of a particular domain. The proposed distinction between ontologies and conceptual schemas makes possible a natural decomposition of information systems in terms of two necessary but complementary epistemic functions: identification of an invariant background and measurement of the object along dimensions of possible variation. Recognition of the suggested distinction represents, we think, a natural evolution in the field of modeling, and significant principled guidance for developers and users of information systems

Design and Implementation of a Conceptual Modeling Assistant (CMA)

This Master's Thesis de nes an architecture for a Conceptual Modeling Assistant (CMA) along with an implementation of a running prototype. Our CMA is a piece of software that runs on top of current modeling tools whose purpose is to collaborate with the conceptual modelers while developing a conceptual schema. The main functions of our CMA are to actively criticize the state of a conceptual schema, to suggest actions to do in order to improve the conceptual schema, and to o er new operations to automatize building a schema. On the one hand, the presented architecture assumes that the CMA has to be adapted to a modeling tool. Thus, the CMA permits the inclusion of new features, such as the detection of new defects to be criticized and new operations a modeler can execute, in a modeling tool. As a result, all modeling tools to which the CMA is adapted bene t of all these features without further work. On the other hand, the construction of our prototype involves three steps: the de nition of a simple, custom modeling tool; the implementation of the CMA; and the adaptation of the CMA to the custom modeling tool. Furthermore, we also present and implement some examples of new features that can be added to the CMA

Design and Implementation of a Conceptual Modeling Assistant (CMA)

This Master's Thesis de nes an architecture for a Conceptual Modeling Assistant (CMA) along with an implementation of a running prototype. Our CMA is a piece of software that runs on top of current modeling tools whose purpose is to collaborate with the conceptual modelers while developing a conceptual schema. The main functions of our CMA are to actively criticize the state of a conceptual schema, to suggest actions to do in order to improve the conceptual schema, and to o er new operations to automatize building a schema. On the one hand, the presented architecture assumes that the CMA has to be adapted to a modeling tool. Thus, the CMA permits the inclusion of new features, such as the detection of new defects to be criticized and new operations a modeler can execute, in a modeling tool. As a result, all modeling tools to which the CMA is adapted bene t of all these features without further work. On the other hand, the construction of our prototype involves three steps: the de nition of a simple, custom modeling tool; the implementation of the CMA; and the adaptation of the CMA to the custom modeling tool. Furthermore, we also present and implement some examples of new features that can be added to the CMA

A Case study on building conceptual schemas by refining general ontologies

This document presents a case study to validate a new approach to develop conceptual schemas (or databases) for information systems, consisting in the refinement of a general ontology [CdPO03]. We use a well-known case study [BCN92] to execute the three activities required to develop a conceptual schema from a general ontology: the refinement, pruning and refactoring activities. We first present the requirements of the case study and then refine the general ontology OG to obtain the extended ontology OX. We have developed a software prototype to automate the pruning and the refactoring activities. Therefore, a pruned ontology OP and a first version of conceptual schema CS1 has been obtained using this prototype. Finally, the quality of CS1 has been improved by means of manual refactorings to obtain a final conceptual schema CS. In this case study, we have used the public version of the Cyc ontology [LGP+90]. However, for a practical application we find it convenient to use as conceptual modelling language the UML, so that we believe our results apply to any similar language.Postprint (published version

A Case study on building conceptual schemas by refining general ontologies

This document presents a case study to validate a new approach to develop conceptual schemas (or databases) for information systems, consisting in the refinement of a general ontology [CdPO03]. We use a well-known case study [BCN92] to execute the three activities required to develop a conceptual schema from a general ontology: the refinement, pruning and refactoring activities. We first present the requirements of the case study and then refine the general ontology OG to obtain the extended ontology OX. We have developed a software prototype to automate the pruning and the refactoring activities. Therefore, a pruned ontology OP and a first version of conceptual schema CS1 has been obtained using this prototype. Finally, the quality of CS1 has been improved by means of manual refactorings to obtain a final conceptual schema CS. In this case study, we have used the public version of the Cyc ontology [LGP+90]. However, for a practical application we find it convenient to use as conceptual modelling language the UML, so that we believe our results apply to any similar language