Geovisual Representations for Spatially Aware Information Retrieved from the Internet

1. Geovisual Representations for Spatially Aware Information Retrieved from the Internet Syed Awase Khirni GIS Division,Dept of Geography University of Zurich. SPIRIT is funded by EU IST Programme Contract Number: IST-2001-35047

2. Overview • Spatial information retrieval • User requirements • Spatial information seeking process • Visualization framework • Different ways of geovisualization

3. Spatial information retrieval • A large proportion of documents refer to some location on earth. • “Spatially Aware” information retrieval is to provide access to information based not just on thematic, but also on spatial relevance. • Retrieved documents are ranked according to spatial and aspatial characteristics using a variety of algorithms.

4. Spatial information retrieval Task : • Representation of documents retrieved from the internet based on their spatial and contextual aspects. Constraints : • Representation for the internet • 2 Dimensional

5. User’s Query Something Spatial Relationship Somewhere HOTELS in CARDIFF Keywords Ontology (Place name hierarchy) near within x km within x min drive in walking distance from outside north of …. (Concepts of interest) /(Points of interest)

6. Query results • A set of geofootprints for each document. • Spatial and contextual ranks • Footprint type: polygon, bounding box, point, line Location (geofootprint) DOC What (contextual info like hotels, railway stations etc.) History (events like information from news site)

7. User requirements • Documents visualized by their spatial context – ordered by spatial & contextual rank • Uncluttered visual representation • Topographic/thematic details • Geographic concept expansion • Description of geographical features • Spatial activities they wish to perform at a particular geographic location – activity maps to support the results retrieved Based on the user studies carried out to assess SPIRIT user requirements

8. Spatial Information Seeking process • Literature • Berry-picking model (Bates,1999) • Cognitive Styles (Pask & Scott) • Holistic • Serialist • User studies • Map metaphor • Holistic users • Coarser LOD/broader picture • Minute details based on their tasks • Serialist users • Prefer finest details – region of interest • Coarser/finer details based on their tasks

9. Framework for Geovisualizations Results of Query (GML/XML) Deegree Web Map Server Web Feature Server (SABE DATA /Tele Atlas) TGN DATA process gazetteer apache commons lib DIGESTER Framework Visualization Rules (XML) GeoTools1.2 on the fly Jess Rules Engine Customized Visualizations (SVG + JS) Cartograms Holistic Hyperbolic browser Serialistic Touchgraph Serialistic Conformance with spatial data and GIS interoperability standards, OpenGIS GML ,SVG W3C,Digital Cartographic Data Standards.

10. Cartograms • Input parameters • Topological neighbourhood • Spatial relevance Natural History Museum Victoria and Albert Museum Science Museum Madame Tussuads Sherlock Holmes Museum Museums Near London

11. Hyperbolic browser & Touch graph • Input parameters. • Topological neighbourhood • Geometric distance (absolute & relative) • Directional details • Visualize spatial and contextual informational hierarchies

12. 24 11 33 34 Query: Hotels in London 12 30 13 8 2 23 17 35 9 20 4 7 Most Relevant Document 25 32 6 22 Geometric distance 14 10 3 16 5 31 29 28 18 Size of the circle –contextual relevance Spatialized based on geometric distance &direction 19 26 21

13. Directories Bordeaux Rouen Haure World Tours Lyon Regional limoges Reims Europe Paris Toulouse montpellier France orleans Perpignan perpignan Marseille Provence Rouen Gijon Nice Limoges Nimes - - - - + + + + St.Tropez Burgos Bilbao Toulon Touch graph cities on the Mediterranean coast of France Related Features St. Tropez A Peninsula on the Mediterranean coast of France. Results > 1.BBC Weather centre-Travel 2.GeoPassage:France 3.Focus on France: 4.Just France Vacation Rentals 5.France Geography Related Resources Travel & Tourism Maps & Views Recreation& Sports N Arts & Education

14. Categorization based on Cognitive Style • Holistic • Cartograms • Present a broader overview initially • Finer details on selection

15. Categorization based on cognitive style • Serialist • Hyperbolic browser • Finer details with geometric distances & directions • Overview details on user’s selection • Touchgraph • Finer details - spatial hierarchy, directions • Overview details on user’s selection

16. Open Questions • What are the metrics for judging a particular visualization is most suitable based on cognitive styles? • What information is useful for the users to help them visualize their spatial activity and generation of spatial activity maps on the fly? • How do we visualize the spatial characterization of spatial and non-spatial properties which are typical for the data available on the internet? • How do we represent vagueness? (hotels with in 5 min walk from Hauptbahnhof, Zurich)

17. Summary • Categorization of visualization based on cognitive styles adopted by the users • Spatial information retrieval • User requirements • Spatial information seeking process • Visualization framework • Different ways of geovisualization

18. Thanks for Listening!

19. Some facts Deep Web Surface web Specialized web-accessible databases And dynamic websites which are not widely known by ‘average’ surfers. 400 to 550 times larger than the information on the surface web A group that consists of static, publicly available web pages and which is relatively small portion of the entire web. WWW 78% of all websites are English websites Size : 4.28 billion pages approx, 50-75 Terabyte of information Size: 550 billion web-connected documents 7500 terabytes of high-quality data Indexed 800 million pages(2001) BrightPlanet Claims ‘deep web’ contains 550 billion web connected documents indexed 2.5 billion individual pages(2002) increasing to 3.1 billion by February 2003. Jan 2004 claimed to cover over 3,307,998,701 pages. Feb 2004, covered ‘6 billion items’: 4.28 billion web pages, 880 million images and 845 million usenet messages Source: http://www.cyveillance.com/web/ downloads/sizing_the_internet.pdf – pg.2