Techreport,
Data Visualization with GraphDB and Workbench
Ontotext Corp, (June 2017)
Abstract
Building Knowledge through Data Visualization. Data visualization enables analysts and organizations to see huge quantities of data clearly and identify patterns quickly. However, data volume, velocity and variety have increased immensely in recent years and so has the need to see the links between data from many sources. By creating visualizations with graph databases, organizations get insights from all perspectives they wish and need to explore. Even a quick glance at the relationship structure reveals where unusually large clusters of nodes or edges are. More traditional charts and statistical visualizations are also very useful to see the structure of data. Expressing relations, graphs and data trends in a visual way turns data into knowledge. The accompanying Webinar is designed to answer a common request from our community - how to make data visualisations from RDF datasets. Are there tools to help with developing queries? How can people who are not conversant with SPARQL get insights into data and understand its structure? How can they run SPARQL queries developed by others? We describe SPARQL editing and data visualization features available in GraphDB Workbench (GDB WB), or such that can be added with little programming. We will also describe SPARQL writing aids and visualization tools that can be integrated with GraphDB. Detailed topics: Writing SPARQL, Built-in SPARQL Result Visualizations, Using SPARQL Results in Spreadsheets, Invoking SPARQL Queries and Query Parameterization, Tools that Help With Writing SPARQL Queries, Translating natural language to SPARQL, Tools for Statistical Visualizations, Graph Visualizations: Built-in to GDB WB, Developing, Visualization Toolkits, Declarative Visualization, RDF by Example, JDBC Data Access API. Last updated: May 2019
