Rdf:SynopsViz
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 |
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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.)
Description
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.
Publications
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
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