Towards Interactive Analytics over RDF Graphs

Maria-Evangelia Papadaki,Yannis Tzitzikas,Nicolas Spyratos

doi:10.3390/a14020034

Abstract

The continuous accumulation of multi-dimensional data and the development of Semantic Web and Linked Data published in the Resource Description Framework (RDF) bring new requirements for data analytics tools. Such tools should take into account the special features of RDF graphs, exploit the semantics of RDF and support flexible aggregate queries. In this paper, we present an approach for applying analytics to RDF data based on a high-level functional query language, called HIFUN. According to that language, each analytical query is considered to be a well-formed expression of a functional algebra and its definition is independent of the nature and structure of the data. In this paper, we investigate how HIFUN can be used for easing the formulation of analytic queries over RDF data. We detail the applicability of HIFUN over RDF, as well as the transformations of data that may be required, we introduce the translation rules of HIFUN queries to SPARQL and we describe a first implementation of the proposed model.

Highlights

The amount of data available on the Web today is increasing rapidly due to successful initiatives, such as the Linked Open Data movement
We study how that language can be applied to Resource Description Framework (RDF) data by clarifying how the concept of analysis context can be defined, what kind of transformations are required and how HIFUN queries are translated to SPARQL
We focus on the support of analytics over any RDF Data, and we focus on a query translation approach, i.e., an approach that does not require transforming or transferring the existing data; instead it can be directly applied over a SPARQL endpoint

Summary

Introduction

The amount of data available on the Web today is increasing rapidly due to successful initiatives, such as the Linked Open Data movement (http://lod-cloud.net/). Resource Description Framework (RDF) The Resource Description Framework (RDF) [37,38] is a graph-based data model for linked data interchanging on the web. It uses triples i.e., statements of the form subjectpredicateobject, where the subject corresponds to an entity (e.g., a branch, a product, etc.), the predicate to a characteristic of the entity (e.g., name of branch) and the object to the value of the predicate for the specific subject (e.g., “branch1 ”). Any finite subset of T constitute an RDF graph (or RDF data set)

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