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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Overview Spatial information retrieval User requirements Spatial information seeking process Visualization framework Different ways of geovisualization

3. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich User’s Query SomethingSpatial RelationshipSomewhere Keywords near within x km within x min drive in walking distance from outside north of …. Ontology (Place name hierarchy) (Concepts of interest) /(Points of interest) HOTELS in CARDIFF

6. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Query results A set of geofootprints for each document. Spatial and contextual ranks Footprint type: polygon, bounding box, point, line DOC Location (geofootprint) What (contextual info like hotels, railway stations etc.) History (events like information from news site)

7. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Framework for Geovisualizations Results of Query (GML/XML) DIGESTER Framework TGN DATA Visualization Rules (XML) on the fly Customized Visualizations (SVG + JS) process Deegree Web Map Server Web Feature Server (SABE DATA /Tele Atlas) Conformance with spatial data and GIS interoperability standards, OpenGIS GML,SVG W3C,Digital Cartographic Data Standards. Jess Rules Engine apache commons lib GeoTools1.2 gazetteer Cartograms Holistic Hyperbolic browser Serialistic Touchgraph Serialistic

10. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Hyperbolic browser & Touch graph Input parameters. Topological neighbourhood Geometric distance (absolute & relative) Directional details Visualize spatial and contextual informational hierarchies

12. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 4 2 8 7 9 6 5 3 30 13 35 20 25 11 34 32 28 18 19 21 12 33 Most Relevant Document 14 31 17 29 26 Geometric distance 23 24 10 16 22 Size of the circle –contextual relevance Spatialized based on geometric distance &direction Query: Hotels in London

13. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Touch graph Directories France World Regional Europe Paris Lyon Marseille Provence Nice montpellier Nimes St.Tropez perpignan Toulon Rouen orleans Reims Haure Tours limoges Bordeaux Toulouse Perpignan Limoges Burgos Bilbao Gijon Related Features Related Resources + - Maps & Views Recreation& Sports + - + - Arts & Education + - St. Tropez A Peninsula on the Mediterranean coast of France. N Results > 1.BBC Weather centre-Travel 2.GeoPassage:France 3.Focus on France: 4.Just France Vacation Rentals 5.France Geography cities on the Mediterranean coast of France Travel & Tourism

14. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Categorization based on Cognitive Style Holistic Cartograms Present a broader overview initially Finer details on selection

15. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich 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. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Thanks for Listening!

19. © 2003 Syed Awase Khirni, GIS Division,Dept of Geography, University of Zurich Some facts WWW Surface web Deep Web A group that consists of static, publicly available web pages and which is relatively small portion of the entire web. Size : 4.28 billion pages approx, 50-75 Terabyte of information 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 Size: 550 billion web-connected documents 7500 terabytes of high-quality data 78% of all websites are English websites Indexed 800 million pages(2001) 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 BrightPlanet Claims ‘deep web’ contains 550 billion web connected documents Source: http://www.cyveillance.com/web/http://www.cyveillance.com/web/ downloads/sizing_the_internet.pdf – pg.2