From Semantic Web Standards

SynopsViz :: A Tool for Scalable Multiscale Visual Exploration & Analysis over Large Datasets

Name of the tool: SynopsViz :: A Tool for Scalable Multiscale Visual Exploration & Analysis over Large Datasets
Home page: The SynopsViz framework
Date of latest release:
Programming language(s) that can be used with the tool: Java
Relevant semantic web technologies: RDF, RDFS, OWL, SPARQL
Categories: Visualizer, RDF or OWL Browser, Special Browser, Search Engine
See also:
Public mailing list:
Preferred project URI: http://synopsviz.imis.athena-innovation.gr
DOAP reference:
Company or institution: NTUA GR & IMIS - ATHENA R.C. GR

(Tool description last modified on 2015-12-26.)


SynopsViz is a tool for scalable multi-level charting and visual exploration of very large RDF & Linked Data datasets. The adopted hierarchical model provides effective information abstraction and summarization. Also, it allows efficient -on the fly- statistic computations, using aggregations over the hierarchy levels.

Key Features

  • It adopts a hierarchical multi-level model for RDF data visualization, browsing and analysis.
  • It offers automatic on-the-fly hierarchy construction based on data distribution, as well as user-defined hierarchy construction based on user's preferences.
  • Provides faceted browsing and filtering over classes and properties.
  • Integrates statistics with visualization; visualizations have been enriched with useful statistics and data information.
  • Offers several visualizations techniques (e.g., timeline, chart, treemap).
  • Provides a large number of dataset's statistics regarding the: data-level (e.g., number of sameAs triples), schema-level (e.g., most common classes/properties), and structure level (e.g., entities with the larger in-degree).
  • Provides numerous metadata related to the dataset: licensing, provenance, linking, availability, undesirability, etc.


Bikakis N., Skourla M., Papastefanatos G.: "rdf:SynopsViz - A Framework for Hierarchical Linked Data Visual Exploration and Analysis". 11th Extended Semantic Web Conference (ESWC '14).

Bikakis N., Papastefanatos G., Skourla M., Sellis T.: "A Hierarchical Framework for Efficient Multilevel Visual Exploration and Analysis". 2015