Authors
Cristóbal Barba-González, José García-Nieto, María del Mar Roldán-García, Ismael Navas-Delgado, Antonio J Nebro, José F Aldana-Montes
Publication date
2019/1/1
Journal
Expert Systems with Applications
Volume
115
Pages
543-556
Publisher
Pergamon
Description
Knowledge extraction and incorporation is currently considered to be beneficial for efficient Big Data analytics. Knowledge can take part in workflow design, constraint definition, parameter selection and configuration, human interactive and decision-making strategies. This paper proposes BIGOWL, an ontology to support knowledge management in Big Data analytics. BIGOWL is designed to cover a wide vocabulary of terms concerning Big Data analytics workflows, including their components and how they are connected, from data sources to the analytics visualization. It also takes into consideration aspects such as parameters, restrictions and formats. This ontology defines not only the taxonomic relationships between the different concepts, but also instances representing specific individuals to guide the users in the design of Big Data analytics workflows. For testing purposes, two case studies are developed …
Total citations
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Scholar articles
C Barba-González, J García-Nieto… - Expert Systems with Applications, 2019