NDLI: A Preliminary Approach on Ontology-based Visual Query Formulation for Big Data

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A Preliminary Approach on Ontology-based Visual Query Formulation for Big Data

Content Provider	CiteSeerX
Author	Soylu, Ahmet Skjævel, Martin G. Giese, Martin Horrocks, Ian Jimenez-Ruiz, Ernesto Kharlamov, Evgeny Zheleznyakov, Dmitriy
Abstract	Abstract. Data access in an enterprise setting is a determining factor for the potential of value creation processes such as sense-making, decision making, and intelligence analysis. As such, providing friendly data access tools that directly engage domain experts (i.e., end-users) with data, as opposed to the situations where database/IT experts are required to extract data from databases, could substantially increase competitiveness and profitability. However, the ever increasing volume, complexity, ve-locity, and variety of data, known as the Big Data phenomenon, renders the end-user data access problem even more challenging. Optique, an ongoing European project with a strong industrial perspective, aims to countervail the Big Data effect, and to enable scalable end-user data access to traditional relational databases by using an ontology-based approach. In this paper, we specifically present the preliminary design and development of our ontology-based visual query system and discuss directions for addressing the Big Data effect.
File Format	PDF
Access Restriction	Open
Subject Keyword	Ontology-based Visual Query Formulation Big Data Preliminary Approach Big Data Effect Ontology-based Approach Preliminary Design Value Creation Scalable End-user Data Access Enterprise Setting Intelligence Analysis End-user Data Access Problem Strong Industrial Perspective Database Expert Big Data Phenomenon Ontology-based Visual Query System Ongoing European Project Domain Expert Friendly Data Access Tool Traditional Relational Database Decision Making Data Access
Content Type	Text
Resource Type	Article

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