Big Data Visualization (Visualizing large datasets in the Semantic Web)

  • LECTURER: Mariano Rico
  • AFFILIATION: ETSIInf, UPM

Outline

The semantic web (also know as the Linked Data Cloud) is a huge graph that requires powerful tools to allow an appropriate visualization of its content. In this seminar we will have a practical approach by means of a powerful tool: Gephi. Although this tools is aimed at visualizing and analyzing any graph, we will use specific plugins to analyze large linked-data datasets like DBpedia.

Syllabus

  1. DBpedia and the Spanish DBpedia (esDBpedia) as a big data use case.
  2. Big graphs with Gephi.
  3. Displaying linked data with Gephi.

Assessment Method

Attendance and a written work on practical cases.

Prerequisites

Basic programming skills.

During the course Moodle will be used, so prior to the start of the course it will be necessary for the students to be logged into Moodle with their University credentials.

Lective hours

3

Remarks

Participants should use their laptop with Internet connection for practical sessions.

Recommended Reading

  • Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. From AAAI.
  • Richard Brath and David Jonker (2015). Graph Analysis and Visualization. Discovering Business Opportunity in Linked Data.
  • D.E. Knuth, The Stanford GraphBase: A platform for Combinatorial Computing, Addison-Wesley 1993.

Timetable

  • 20 March, 15:00-18:00

Lecture Theatre

  • A-6205

Tuition Language

English.