An ontology-centric architecture for extensible scientific data management systems

Yuan Fang Li*, Gavin Kennedy, Faith Ngoran, Philip Wu, Jane Hunter

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    35 Citations (Scopus)

    Abstract

    Data management has become a critical challenge faced by a wide array of scientific disciplines in which the provision of sound data management is pivotal to the achievements and impact of research projects. Massive and rapidly expanding amounts of data combined with data models that evolve over time contribute to making data management an increasingly challenging task that warrants a new approach. In this paper we present an ontology-centric architecture for data management systems that is extensible and domain independent. In this architecture, the behaviors of domain concepts and objects are captured entirely by ontological entities, around which all data management tasks are carried out. The open and semantic nature of ontology languages also makes this architecture amenable to greater data reuse and interoperability. To evaluate the proposed architecture, we have applied it to the challenge of managing phenomics data.

    Original languageEnglish
    Pages (from-to)641-653
    Number of pages13
    JournalFuture Generation Computer Systems
    Volume29
    Issue number2
    DOIs
    Publication statusPublished - Feb 2013

    Fingerprint

    Dive into the research topics of 'An ontology-centric architecture for extensible scientific data management systems'. Together they form a unique fingerprint.

    Cite this