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

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, velocity, 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.

Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users

“…The primary contributions presented in this article are a novel and easy-to-use concept and a flexible and extensible widget-based architecture for an ontology-based VQS, based on multiple coordinated representation and interaction paradigms for graph navigation and facet refinement, along with a prototype named OptiqueVQS [77,81]. The design of the OptiqueVQS is guided through industrial use cases provided by two large energy companies, namely Statoil 3 and Siemens 4 .…”

Exploratory analysis of large web datasets

“…In the recent years, solutions specifically conceived for big-data exploration are also being appearing in a number of different contexts, such as for example humanities [5], bioinformatics [6], business intelligence and analytics [7], and sensor-data management [8]. In [9], issues about big-data filtering are discussed and techniques based on the use of ontologies and visual tools for effective query formulation are presented. The problem of visually querying big-data collections is also discussed in [10], where the focus in on interactivity with the final user and the need to satisfy real-time questions.…”

Ontology Based Access to Exploration Data at Statoil

“…We also plan to compare performance and quality of our bootstrapper with existing analogous systems. Finally, in order to improve usability of our OBDA deployment and to facilitate construction of ontological query to end users with limited system experience we work on intuitive query interfaces [1][2][3][4][28][29][30][31].…”