Linked data provides the basis for knowledge to be distributed, networked, and shared. The term Linked Data refers to a set of best practices for publishing and interlinking structured data on the Web. Creating a connection between data and its contexts could lead to the development of intelligent search engines which could explore the Web, moving from a keyword-based approach to a meaning-based approach. Researches can be more accurate by exploiting the relations between words. Linked Data can provide a benefit in several research areas like in the medical field for structuring the connections between various illness and the relative cures, in the scientific literature for structuring the citations between the million of documents published online. The potentialities of exploitation of Linked Data are countless.
On the other hand, given the wide availability of LD sources, it is crucial to provide intuitive tools enabling users without semantic technology background to explore, analyse and interact with increasingly large datasets. Visual analytics integrates the analytic capabilities of the computer and the abilities of the human analyst, allowing novel discoveries and empowering individuals to take control of the analytical process. Linked Data visualization aims to provide graphical representations of datasets with the aim to facilitate their analysis and the generation of insights out of complex interconnected information.
In this chapter, we will introduce why visualization is a powerful means for linked data exploration, then, the principles and technologies that are the bases for the creation of Linked Data are presented, and we also depict the incredible impact that Linked Data can have in the real world.
In the next section, we start illustrating how visualization is good way of interacting with the corresponding very large amounts of complex, interlinked, multidimensional data. The evolution of the web from Web 1.0 to Web 4.0. is depicted in Section 1.2. We highlight the principles of Linked Data in Section 1.3; after this, we describe the Linked Data Cloud (Section 1.4) that draws datasets that have been published according to those principles. Sections 1.5 and 1.6 are devoted to assessing the impact of Linked Data in our life and the opportunities they can generate. Finally, in Section 1.7, we introduce the theoretical basis of Linked Data by describing the Semantic Web technologies.

  • 1.1   The Power of Visualization on Linked Data
  • 1.2   The Web of Linked, Open, and Semantic Data
  • 1.3   Principles of Linked Data
  • 1.4   The Linked Open Data Cloud
  • 1.5   Web of Data in Numbers
  • 1.6   The Value and Impact of Linked and Open Data
  • 1.7   Semantic Web Technologies
  •       − RDF
          − RDFS & OWL
          − SPARQL
          − Storage Technologies
  • 1.8   Conclusions