Visualization

Visualization plays a unique role in understanding RDF Data because RDF
Graphs
are conceptually diagrammatic in nature. Because in RDF, “everything is data,” some of the tools usable for visualizing instance data may be used to visualize ontologies, while other tools may be used to explore the statistical, spatial, or temporal characteristics of datasets:

  • Generating a Linked Data cloud diagram
    • LOD cloud generators (e.g., CKAN)
  • Visually exploring statistical characteristics of large data sets
    • Statistical visualization tools (e.g., Spotfire)
  • Generating different visual views of data (e.g., on timelines or maps)
    • Visualization tools (e.g., Simile)

7 thoughts on “Visualization

  1. VisioOwl remains the most accurate graphical representation for OWL-based ontologies. It provides a good tool for instructors to use to teach students the basic concepts of OWL classes, subclasses, properties, subproperties and the formal relationships between them. Best of luck with your classes.

  2. Because RDF has graph theory basis, there are some JavaScript libraries to generate web-native visualization e.g., D3.js(formerly Protovis) could RDF data as Force-Directed Graph. There is a data transformation from RDF (single file or SPARQL Endpoint result) to JSON.
    D3 also could generate LOD cloud and circle packing.
    https://github.com/mbostock/d3/wiki/Gallery.

  3. We propose LodLive to browse the web of data in a new and exciting way: LodLive project provides a demonstration of the use of Linked Data standard (RDF, SPARQL) to browse RDF resources. With LodLive you can browse, explore, view on Map, view photos and more, of linked open data. LodLive offer a new way of browsing the web of data using SPARQL endpoint to obtain direct and inverse relations of a single resource.
    You can download the source code on github https://github.com/dvcama/LodLive

  4. The ontological community has been guilty for many years of fetishistically pursuing node/arc, rubber-band visualizations owing to their dubious *wow* factor. I would suggest keeping various visualization styles on an even keel, and spend as much or more time examining how RDF data can be put into more traditional visualizations, as when you seriously dig into the data the *cool* animated stuff rarely holds up as a way to actually perform analysis.

  5. Visualization would be wonderful for demonstrating the structure and elements of it. But it would be simple and clear (don’t add complexity!), and also cool and pretty. I agree that having multiple view types would be helpful.

  6. The final version of the Inventory of Learning Topics, with modifications in light of comments received, is posted here:

    http://lld.ischool.uw.edu/wp/learning/inventory/

    The project sponsors are grateful for the input received so far, and they invite additional comments on the page linked above. All additional input will inform future implementation plans for the Learning Linked Data project.

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