Connecting Knowledge to Data Through Transformations in KnowID: System Description

Fillottrani, Pablo Rubén; Jamieson, Stephan; Keet, C. Maria

doi:10.1007/s13218-020-00675-6

Cited by 1 publication

(1 citation statement)

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“…The aim of the evaluation with a proof-of-concept tool was to ascertain experimentally whether the transformation rules were indeed correct, using test models in EER and ARM to cover all cases. A preliminary flexible tool was designed and implemented, which takes EER and ARM diagrams serialized in JSON, transforms them at the back-end into an array, applies the relevant transformation rules, and returns an ARM or EER diagram and a log file with the record of the transformation (see Figure 5) [42]; the code, some examples, and a few screenshots are available at http://www.meteck.org/KnowID.html. In total, 83 tests were run with the latest version.…”

Section: Discussionmentioning

confidence: 99%

KnowID: An Architecture for Efficient Knowledge-Driven Information and Data Access

Fillottrani

Keet

2020

Data Intelligence

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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 Enhanced Entity-Relationship (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.

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Section: Discussionmentioning

confidence: 99%