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Connecting Knowledge to Data Through Transformations in KnowID: System Description

Kurzanzeige
dc.contributor.authorFillottrani, Pablo R.
dc.contributor.authorJamieson, Stephan
dc.contributor.authorKeet, C. Maria
dc.date.accessioned2021-04-23T09:35:31Z
dc.date.available2021-04-23T09:35:31Z
dc.date.issued2020
dc.description.abstractIntelligent information systems deploy applied ontologies or logic-based conceptual data models for effective and efficient data management and to assist with decision-making. A core deliberation in the design of such systems, is how to link the knowledge to the data. We recently designed a novel knowledge-to-data architecture (KnowID) which aims to solve this critical step through a set of transformation rules rather than a mapping layer, which operate between models represented in EER notation and an enhanced relational model called the ARM. This system description zooms in on the novel tool for the core component of the transformation from the Artificial Intelligence-oriented modelling to the relational database-oriented data management. It provides an overview of the requirements, design, and implementation of the modular transformations module that straightforwardly permits extension with other components of the modular KnowID architecture.de
dc.identifier.doi10.1007/s13218-020-00675-6
dc.identifier.pissn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-020-00675-6
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/36303
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 34, No. 3
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectConceptual modeling
dc.subjectData management
dc.subjectOntology-mediated data access
dc.titleConnecting Knowledge to Data Through Transformations in KnowID: System Descriptionde
dc.typeText/Journal Article
gi.citation.endPage379
gi.citation.startPage373

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Künstliche Intelligenz 34(3) - September 2020