Published Versions 1 Vol 2 (4) : 487–512 2020
KnowID: An Architecture for Efficient Knowledge-DrivenInformation and Data Access
: 2019 - 10 - 08
: 2020 - 04 - 24
: 2020 - 04 - 26
307 7 0
Abstract & Keywords
Abstract: Modern information systems require the orchestration of ontologies, conceptual data modeling techniques, and efficient data management so as to provide a means for better informed decision-making and to keep up with new requirements in organizational needs. A major question in delivering such systems, is which components to design and put together to make up the required “knowledge to data” pipeline, as each component and process has trade-offs. In this paper, we introduce a new knowledge-to-data architecture, KnowID. It pulls together both recently proposed components and we add novel transformation rules between EER and the Abstract Relational Model to complete the pipeline. KnowID’s main distinctive architectural features, compared to other ontology-based data access approaches, are that runtime use can avail of the closed world assumption commonly used in information systems and of full SQL augmented with path queries.
Keywords: Extended entity-relationship diagrams; Abstract relational model; Ontology-based data access
We thank David Toman for feedback on an earlier draft. We also thank the 20 students of the 7 capstone projects for exploring the solution space in implementing the transformation rules.
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Article and author information
Cite As
P.R. Fillottrani & C.M. Keet. KnowID: An architecture for efficient knowledge-driven information and data access. Data Intelligence 2(2020), 487–512. doi: 10.1162/dint_a_00060
Pablo Rubén Fillottrani
P.R. Fillottrani ( and C.M. Keet ( jointly developed the theory. Both authors have mademeaningful and valuable contributions in revising and proofreading the resulting manuscript.
Pablo Rubén Fillottrani is a Professor with the Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina, and independent researcher at Comisión de Investigaciones Cientficas de la Provincia de Buenos Aires. He is head of LISSI, Software Engineering and Information Systems R&D Lab. His research interests are in ontology engineering, semantic Web, knowledge representation and information integration with applications in digital government and softwareengineering. Pablo obtained his PhD at Universidad Nacional del Sur in 2001.
C. Maria Keet
P.R. Fillottrani ( and C.M. Keet ( jointly developed the theory. C.M. Keet coordinated the writing of the manuscript and devised the examples. Both authors have made meaningful and valuable contributions in revising and proofreading the resulting manuscript.
C. Maria Keet is an Associate Professor with the Department of Computer Science, University of Cape Town, South Africa. Her research interests are in knowledge engineering, including ontology engineering, natural language generation, and ontology-driven conceptual modeling, which have resulted in over 100 publications. She wrote a textbook on ontology engineering.Maria obtained her PhD at the KRDB Research Centre, Free University of Bozen-Bolzano, Italy, in 2008. She also has worked as systems engineer in the IT industry for three and half years.
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Published: Dec. 17, 2020 (Versions1
Data Intelligence