An ontological and semantical approach to source-receiver interoperability

"October 1994."Includes bibliographical references (p. 10).Jacob Lee, Michael D. Siegel

Understanding the Impact of Business Functional Areas on the Theory of Multiple Grammar Selection

Theory of Multiple Grammar Selection (TMGS) is used to select the optimum combination of grammars when more than one grammar is needed to create conceptual models. However, as unnecessary grammars may also be selected into the optimum combination, overlap of the grammatical constructs can increase. Thus, the resulting conceptual model decreases its clarity and usefulness. One way of solving this issue is reducing the number of constructs in the reference ontology. Since ontological constructs have different importance levels in different domains the level of importance can be used as the basis for reducing number of constructs. This paper presents the result of a study we carried out to find how the importance levels of Bunge-Wand-Weber (BWW) ontology can be measured within a selected domain. As the information system domain of this study, we selected a specific business functional area namely, Sales & Distribution. Thus.the findings can be applied to any domain with similar characteristics to Sales & Distribution functional area

A MODEL OF SYSTEMS DECOMPOSITION

The way in which systems should be decomposed so they can be better understood and better designed remains a fundamental problem in the information systems discipline. A number of different decomposition methodologies have been proposed. However, no methodology has emerged as dominant, presumably because the relative strengths and limitations of each methodology are still unclear. Case study research that has compared the methodologies, for example, has produced only equivocal results. In the absence of a theory of decomposition, it is difficult to make insightful predictions about the merits and failings of a particular methodology. Consequently, it is difficult to undertake empirical research that produces compelling results. Accordingly, in this paper we develop a rudimentary model of decomposition that we hope might form the basis of a subsequent, more complete theory of decomposition

TOWARD A THEORY OF THE DEEP STRUCTURE OF INFORMATION SYSTEMS

The deep structure of an information system comprises those properties that manifest the meaning of the real-world system that the information system is intended to model. In this paper we describe three models that we have developed of information systems decl}.structure properties. The first, the representational model, proposes a set of constructs that enable the ontological completeness of an information systems grammar to be evaluated. The second, the state-tracking model, proposes four requirements that information systems must satisfy if they are to faithfully track the real-world system they are intended to model. The third, the good-decomposition model, proposes a set of necessary conditions that an information system must meet if it is to be well decomposed. The three models facilitate the evaluation of grammars used to analyze, design, and implement information systems and specific scripts that represent implemented information systems

AN ONTOLOGICAL ANALYSIS OF SOME FUNDAMENTAL INFORMATION SYSTEMS CONCEPTS

This paper describes how ontological concepts can be used to model information systems. We view an information system as an object that is independent of its use or its technology of implementation. The main premise of the model is that an information system is a representation of a real-world system, and as such it should possess certain characteristics, We show how the model can be used to define various concepts such as real-time, batch, data processing, management reporting, decision support, controls, and decomposition. Furthermore, we show how the model may serve as the foundation of a theory of systems analysis and design. In particular, it provides a formal definition of information systems specifications and a normative model of decomposition

A software maintenance method based on the software configuration management discipline

Software maintenance has until recently been the neglected phase in the software engineering process, despite the fact that maintenance of existing software systems may account for over half of all efforts expended by a software organization. Research into software maintenance, compared to other phases of the software engineering process is rare. Moreover, it is widely accepted that current software maintenance methods and techniques are unable to cope with the complexity inherent in maintaining software systems. This thesis is concerned with the development of a method, named Configuration Management Formalization for Maintenance (COMFORM), designed for the maintenance of existing software systems. COMFORM provides guidelines and procedures for carrying out a variety of activities performed during software maintenance. It accommodates a change control framework, around which the Software Configuration Management discipline is applied. Redocumentation is another problem tackled by COMFORM, which gathers together the documentation necessary to improve the maintainability and quality of existing software systems. This is achieved by the use of forms representing the output of each phase of a proposed software maintenance model. The information obtained by filling in forms is formalized according to a data model, which provides a common basis for the representation of the method's functionality. Finally, a prototype of COMFORM has been implemented, so that the procedures and guidelines set up by the method can be enforced and followed by its users

Finding hidden semantics of text tables

Combining data from different sources for further automatic processing is often hindered by differences in the underlying semantics and representation. Therefore when linking information presented in documents in tabular form with data held in databases, it is important to determine as much information about the table and its content. Important information about the table data is often given in the text surrounding the table in that document. The table's creators cannot clarify all the semantics in the table itself therefore they use the table context or the text around it to give further information. These semantics are very useful when integrating and using this data, but are often difficult to detect automatically. We propose a solution to part of this problem based on a domain ontology. The input to our system is a document that contains tabular data and the system aims to find semantics in the document that are related to the tabular data. The output of our system is a set of detected semantics linked to the corresponding table. The system uses elements of semantic detection, semantic representation, and data integration. Semantic detection uses a domain ontology, in which we store concepts of that domain. This allows us to analyse the content of the document (text) and detect context information about the tables present in a document containing tabular data. Our approach consists of two components: (1) extract, from the domain ontology, concepts, synonyms, and relations that correspond to the table data. (2) Build a tree for the paragraphs and use this tree to detect the hidden semantics by searching for words matching the extracted concepts. Semantic representation techniques then allow representation of the detected semantics of the table data. Our system represents the detected semantics, as either 'semantic units' or 'enhanced metadata'. Semantic units are a flexible set of meta-attributes that describe the meaning of the data item along with the detected semantics. In addition, each semantic unit has a concept label associated with it that specifies the relationship between the unit and the real world aspects it describes. In the enhanced metadata, table metadata is enhanced with the semantics and representation context found in the text. Integrating data in our proposed system takes place in two steps. First, the semantic units are converted to a common context, reflecting the application. This is achieved by using appropriate conversion functions. Secondly, the semantically identical semantic units, will be identified and integrated into a common representation. This latter is the subject of future work. Thus the research has shown that semantics about a table are in the text and how it is possible to locate and use these semantics by transforming them into an appropriate form to enhance the basic table metadata