geovisual representations for spatially aware information retrieved from the internet

Geovisual Representations for Spatially Aware Information Retrieved from the Internet

Syed Awase KhirniGIS Division,Dept of Geography

University of Zurich.

SPIRIT is funded by EU IST ProgrammeContract Number: IST-2001-35047

© 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


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.


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


User’s Query

Something Spatial Relationship Somewhere

Keywords nearwithin x kmwithin x min drivein walking distance fromoutside north of ….

Ontology(Place name hierarchy)

(Concepts of interest)/(Points of interest)

HOTELS in CARDIFF


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)


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


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


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

CartogramsHolistic

Hyperbolic browserSerialistic

TouchgraphSerialistic


Cartograms

•Input parameters•Topological neighbourhood• Spatial relevance

Natural History MuseumVictoria and Albert MuseumScience MuseumMadame TussuadsSherlock Holmes Museum

Museums Near London


Hyperbolic browser & Touch graph

Input parameters. Topological neighbourhood Geometric distance (absolute & relative) Directional details

Visualize spatial and contextual informational hierarchies


4

28

7

9

6

5

3

30

13

35

20

25

1134

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


Touch graph

Directories

France

World

Regional

EuropeParis

Lyon

MarseilleProvence

Nice

montpellier

NimesSt.Tropez

perpignan

Toulon

Rouen

Rouen

orleans

Reims

HaureTours

limoges

Bordeaux

Toulouse

Perpignan

Limoges

Burgos Bilbao

Gijon

Related Features

Related Resources

+-

Maps & Views

Recreation& Sports

+-

+-Arts & Education +-

St. TropezA 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


Categorization based on Cognitive Style

Holistic Cartograms

Present a broader overview initially Finer details on selection


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


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)


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


Thanks for Listening!


Some facts

WWW

Surface webDeep 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 documents7500 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

BrightPlanetClaims ‘deep web’ contains550 billion web connected documents

Source: http://www.cyveillance.com/web/downloads/sizing_the_internet.pdf – pg.2

geovisual representations for spatially aware information retrieved from the internet

Documents

spatial data

university of zurich

spatial relevance

dept of geographyuniversity

gis interoperability

aware information retrieval

retrieved documents

contextual aspects