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Distributed data and ontologies: An integrated semantic web architecture enabling more efficient data management
Author(s) -
Browne Oliver,
O'Reilly Philip,
Hutchinson Mark,
Krdzavac Nenad B.
Publication year - 2019
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.24144
Subject(s) - ontology , computer science , data integration , data quality , interface (matter) , semantic web , ontology based data integration , knowledge management , data model (gis) , data science , database , world wide web , business , marketing , metric (unit) , philosophy , epistemology , bubble , maximum bubble pressure method , artificial intelligence , parallel computing
Regulatory reporting across multiple jurisdictions is a significant cost for financial services organizations, due to a lack of systems integration (often with legacy systems) and no agreed industry data standards. This article describes the design and development of a novel ontology‐based framework to illustrate how ontologies can interface with distributed data sources. The framework is then tested using a survey instrument and an integrated research model of user satisfaction and technology acceptance. A description is provided of extensions to an industry standard ontology, specifically the Financial Industry Business Ontology (FIBO), towards enabling greater data interchange. Our results reveal a significant reduction in manual processes, increase in data quality, and improved data aggregation by employing the framework. The research model reveals the range of factors that drive acceptance of the framework. Additional interview evidence reveals that the ontological framework also allows organizations to react to regulatory changes with much‐improved timeframes and provides opportunities to test for data quality.