Linked Data Visualization : Techniques, Tools, and Big Data (9781681738345) by unknow

Author:unknow
Language: eng
Format: epub
ISBN: 9781681738345
Publisher: LightningSource
Published: 2020-09-15T05:00:00+00:00

Vocabulary-Specific Tools

A variety of tools target to multidimensional LD that is modeled with the DCV (RDF Data Cube Vocabulary).6 CubeViz [Ermilov et al., 2013, Salas et al., 2012] (Figure 3.17) is a faceted browser for exploring statistical data. The tool provides data visualizations using different types of charts (i.e., line, bar, column, area, and pie). The Payola DCV (Payola Data Cube Vocabulary) [Helmich et al., 2014] adopts the LDVM stages [Brunetti et al., 2013, Klímek et al., 2015] in order to visualize RDF data described by the DCV. The same types of charts as in CubeViz are provided in this tool. The OLAP4LD framework provides access to multidimensional LD and model it as data cubes based on DCV [Kämpgen and Harth, 2014]. Using the OLAP4LD infrastructure, the LDCE (Linked Data Cubes Explorer) has been developed, allowing the users to explore and analyze datasets that include governmental statistical.

ESTA-LD (Exploratory Spatio-Temporal Analysis) [Mijovic et al., 2016] (Figure 3.18) is a Web tool for visualizing spatio-temporal data from data cubes which are modeled with the DCV. ESTA-LD provides several visualization types for presenting spatio-temporal data, e.g., choropleth map, timeline, chart. The OpenCube Toolkit [Kalampokis et al., 2014] offers several tools related to statistical LD. For example, OpenCube Browser explores RDF data cubes by presenting a two-dimensional table. Additionally, the OpenCube Map View offers interactive map-based visualizations of RDF data cubes based on their geospatial dimension. Finally, Petrou et al. [2014] offers several map and chart visualizations of demographic, social and statistical linked cube data.

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