Linked Data Visualization: Techniques, Tools, and Big Data

Linked Data brings structured information from different domains together on the Web—but exploring those connections takes more than a large dataset. Linked Data Visualization: Techniques, Tools, and Big Data examines the visual methods and software that help people investigate this interconnected information, from core visualization principles to a comparative evaluation of tools.

See the structure behind the data

The book introduces Linked Data, the Web of Data, and related Semantic Web technologies before turning to the design principles that make information easier to interpret. Its examples of visualization types include patterns over time, proportions, graph relationships, and data on maps. Interactive visualization and the particular demands of Big Data also receive attention.

Explore a landscape of tools

A substantial section surveys Linked Data visualization tools, including browsers and exploratory tools, graph-based systems, tools that combine visualization types, and options focused on domains, vocabularies, devices, or ontologies. The breadth of this survey helps readers consider how different tools approach different kinds of data and exploration.

Compare tools against real tasks

Rather than stopping at a catalogue, the book develops use cases for visual exploration and evaluates tools in relation to them. The evaluation considers tool characteristics, how well they support the described use cases, and where their limitations emerge—useful context when assessing which approach may suit a particular Linked Data exploration task.

For readers working with data and the Web

Data scientists, domain experts, students, and practitioners interested in Linked Data or information visualization will find a clear route through the subject: foundations, techniques, tools, use cases, and evaluation. It can also serve as a course text or a primer for readers beginning to explore visual analysis of Linked Data.

Grounded in both visualization concepts and tool assessment, this volume offers a considered introduction to making the Web of Data more explorable—and to the challenges that remain.