Interactive chart visualization widgets

 

Role

This component aims at providing interactive visualization of RDF data cubes, in particular, time series data. Moreover, this component provides basic utilities reused by other components, particularly, the R statistical analysis module and R2RML extensions for data cubes.

 

How it works

To implement the chart based visualization functionality, the amCharts stock chart component was reused and extended. While the basic IWB chart widgets implementation served as a basis, to enable working with RDF data cubes specific functionalities had to be developed both on the server and on the client side.
In particular, a Java API was developed to enable working with the RDF Data Cube ontology representation, realising such tasks as representing data cube OLAP operations with SPARQL queries, collecting cube metadata, etc. On the client side, the standard amCharts library was extended to enable dynamic loading of additional data from the server. In this way, the additional data are pulled from the server when the user selects the specific time series from the menu. That helps to avoid performance issues when visualizing large and multi-dimension data cubes.

 

Functionality

The component aims at extending the Information Workbench chart visualization capabilities to adapt them to the RDF data cube representation. The goal is to make it easier for the user to explore an RDF data cube by changing the visualized slice interactively and comparing different slices.
In particular, the required functionalities include:

  • Ability for the qualified users (application builders) to configure the visualizations easily for the specific dataset without the need to build complex SPARQL queries manually.
  • Ability for the end-users to change the time series they wish to see.
  • Ability for the end-users to compare different time series along a certain dimension.

The basic Information Workbench widget framework utilises the popular amCharts JavaScript library to visualize the results of SPARQL SELECT queries. Although slices of data represented as RDF data cubes are also extracted using SPARQL queries, constructing such queries manually is a time- consuming procedure even for a Semantic Web expert. To make this procedure more convenient, the chart widget configuration had to be extended.

Instructions

Installation guide:

  • See Installation.html inside the source distribution

Downloads

Get the latest version at:
Source code: Download (v.1.0)