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Exploratory Spatio-Temporal Analysis of Linked Statistical Data

17 Pages Posted: 3 Jul 2018 First Look: Accepted

See all articles by Vuk Mijovic

Vuk Mijovic

University of Belgrade - School of Electrical Engineering

Valentina Janev

University of Belgrade - Institute Mihajlo Pupin; University of Belgrade

Dejan Paunovic

University of Belgrade

Sanja Vranes

University of Belgrade

Abstract

Publishing and sharing open government data in Linked Data format provides many opportunities in terms of data aggregation/integration and creation of information mashups. Statistical data, that contains various performance indicators and their evolution through time, is an example of data that can be used as the foundation for policy prediction, planning and adjustments, and can be re-used in different applications. However, due to Linked Data being relatively a new field, currently there is a lack of tools that enable efficient exploration and analysis of linked geospatial statistical datasets. Therefore, ESTA-LD (Exploratory Spatio-Temporal Analysis) tool was developed to address some of the Linked statistical Data management issues, such as crossing the statistical and the geographical dimensions, producing statistical maps, visualizing different measures, comparing statistical indicators of different regions through time, etc. This paper discusses the modeling approach that was adopted so that the published data conform to the established standards for representing statistical, spatial and temporal data in Linked Data format. The main contribution is related to the delivery of state-of-the-art open-source tools for retrieving, quality assessment, exploration and analysis of statistical Linked Data that is made available through a SPARQL endpoint.

Keywords: Linked Data, RDF Data Cube Vocabulary, Statistical Data, Analysis, Visualization, Spatio-Temporal Data

Suggested Citation

Mijovic, Vuk and Janev, Valentina and Paunovic, Dejan and Vranes, Sanja, Exploratory Spatio-Temporal Analysis of Linked Statistical Data (2016). Journal of Web Semantics First Look 41_0_1. Available at SSRN: https://ssrn.com/abstract=3199268 or http://dx.doi.org/10.2139/ssrn.3199268

Vuk Mijovic

University of Belgrade - School of Electrical Engineering ( email )

73 Bulevar kralja Aleksandra
Belgrade
Serbia

Valentina Janev (Contact Author)

University of Belgrade - Institute Mihajlo Pupin ( email )

Belgrade
Serbia

University of Belgrade ( email )

Studentski trg 1
Belgrade, 11000
Serbia

Dejan Paunovic

University of Belgrade ( email )

Studentski trg 1
Belgrade, 11000
Serbia

Sanja Vranes

University of Belgrade ( email )

Studentski trg 1
Belgrade, 11000
Serbia

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