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Envision

Problems:

- Various formats of semantically linked data (RDF, etc.)
- The semantic web is limited to a scientific domain
- Data is raw, and has inconsistencies
- Most of the time you are not interested in the whole set of properties
- The vast amount of data and types often leads to disorientation

Desires:

- Operate on linked data
- See the data (connections, coherences, etc.)
- Analyze data (compare common properties of a set)
- Lowered barriers to ‘work’ with semantically rich data and in turn provide new data.

Goals:

- Definition of an object model that that provides a ‘view’ on linked data.
- Typed collections featuring properties can be distilled from linked data sources (RDF, Freebase, Last.fm, Delicious)
- A generic browser interface that allows to navigate and analyze such data
- Such a browser should allow filtering (faceted browsing principle) and provide various types of visualization to compare and analyze data.
- Describe a feasible approach to convert various data sources
– Can this be done automatically, semi-automatically?
– Because data is semantically annotated (RDF, OWL, etc.) software can reason about it and autonomously convert it to a defined collection format.

Intended Technology:

- Rich web interface
- HTML 5
- Visualizations are based on Canvas using the Processing.js visualization framework
- Ruby on Rails
- REDIS (fast storage engine)

State of the art

- Elastic Lists (Moritz Stefaner)
- Pivot (Microsoft)
- Parallax (Freebase Browser)
- SIMILE Projects at the MIT
- ASKKEN – Visual Freebase Resource browser

References

- Informationsvisualisierung_im_Semantic Web / Michael Aufreiter

From http://getpivot.com:
At the heart of Pivot are “Collections.” They combine large groups of similar items on the Internet, so we can begin viewing the relationships between individual pieces of information in a new way. By visualizing hidden patterns, Pivot enables users to discover new insights while interacting with thousands of things at once.

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