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Ontology-Driven Automated Generation Of Data Entry Interfaces

Cannon, Alan, Kennedy, Jessie, Paterson, Trevor and Watson, Mark F (2004) Ontology-Driven Automated Generation Of Data Entry Interfaces. In: Key Technologies for Data Management: 21st British National Conference on Databases. Lecture Notes in Computer Science , 3112 . Springer, Berlin, pp. 150-164. ISBN 978-3-540-22382-5

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    Abstract/Description

    This paper discusses an ontology based approach for the automatic generation of data entry interfaces to databases. An existing domain ontology is mapped to a system domain model, which a domain expert can then specialise using their domain expertise, for their data entry needs as required for individual projects. Based on this specialised domain knowledge, the system automatically generates appropriate data entry interfaces with the aid of a presentation model. By constraining the data entered to a term definition ontology and utilising appropriate defined domain terminology the quality of the collected data can be improved. Compared with traditional modelbased user automatic interface development environments, this approach also has the potential to reduce the labour requirements for the expert developer, as the applied ontology provides initial domain knowledge to the system.

    Item Type: Book Section
    Print ISSN: 0302-9743
    ISBN: 978-3-540-22382-5
    Electronic ISBN: 978-3-540-27811-5
    Additional Information: Comprises: Proceedings of Key technologies for Data Management, the 21st British National Conference on Databases (BNCOD 21), Edinburgh 7-9 July 2004. Howard Williams & Lachlan MacKinnon (eds.) Edinburgh: Herriot-Watt University, 2004. ISBN: 190441012x.
    Uncontrolled Keywords: Domain ontology; Data entry interfaces; Automation; Database use; Computer programming;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
    Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
    Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Item ID: 3022
    Depositing User: Computing Research
    Date Deposited: 27 Oct 2009 17:06
    Last Modified: 22 Jan 2014 10:49
    URI: http://researchrepository.napier.ac.uk/id/eprint/3022

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