Neogeography : the challenge of channelling large and ill-behaved data streams
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Transcript of Neogeography : the challenge of channelling large and ill-behaved data streams
Neogeography: the challenge of channelling large and ill-behaved data streamsMaurice van Keulen and Rolf de By
Spatial information is becoming an ordinary commodity Google Earth & Maps, MS Bing, NASA’s WorldWind Geo-tagging of visited places, meetings, activities; automatic geo-
tagging by personal devices: photo/video camera, cell phone Social networks with location intelligence
In the less developed world, serious applications are slowly becoming a reality Location intelligence for agriculture, health, transportation and
traffic, education, emergency mitigation, electronic payments, election monitoring, market prices etc.
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FOR SERIOUS APPLICATIONS IN THE LESS DEVELOPED WORLDLOCATION INTELLIGENCE
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SOCIAL NETWORK APPLICATIONS
Trucking and road availability
Farming and field suitability
Traffic and car-pooling
Emergency response
Crime and neighbour-hood vigilance
Urban utility monitoring
Neogeography: applications in which geographic information derives from end-users, not only from official bodies like mapping agencies, cadastres or other official, (semi-)governmental entities.
Central problems User community is dynamic Users contribute information and expect something in return Contributed information is not necessarily of good quality or trust Contributed information is somewhat unstructured
(contributors cannot be expected to follow strict data schemes and they may only have access to a cell-phone operated network)
Need for a new brand of location-based information management
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NEOGEOGRAPHY
Example neogeo sites
Importance of neogeography in disaster response
In disaster events: In situ real-time data
may be scarce, may be mutually inconsistent, and may change over time is needed to augment partial knowledge and understanding.
Communication infrastructure may be damaged. All data is welcome, all kinds of data also:
witness reports photos audio videos human and machine sensor readings
General public is a powerful information source, and generally has an incentive to report (911).
The neogeographers in disasters
People on site People affected Rescuers and other professionals Mobile telephone providers Press
Biggest challenge: how to make sense of large amounts of not very trustworthy information:
Can you rely on what unknown sources inform you about?
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SYSTEM OBJECTIVE
XML
sms / sensor & satellite data / data from official bodies
geoservices
Open source XML-based spatial data
infrastructure capable of
orchestrating & processing
ambiguous/vague semi/unstructured
geodata workflows delivering
personalized geoservices
Spatiotemporal features Extend XML database technology to fully include spatial feature
support (OGC) and support for fully XML-based development of geoservices and spatiotemporal analysis
Spatiotemporal vagueness Extend information extraction technology to handle ambiguity and
spatiotemporal vagueness in sensor data and explicit natural language references to the where and when
Data augmentation and data quality improvement Spatiotemporal profiling
Provide better understanding of user’s information needs by analyzing historic requests and offered neogeographic data
User profile pattern matching: finding like-minded users
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SCIENTIFIC CHALLENGES
Space and time issues Uncertainty and trust Role of the volunteered information
Difference: handling the map versus handling the data
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CONNECTION WITH OTHER NEOGEO PROJECT
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THE TEAM
Rolf de By(ITC)
Mauricevan Keulen
(UT)
Jan Flokstra(UT)
ClarisseKagoyire (ITC)
Mena Badieh Habib (UT)
PhD student @ITCBackground: Master @ITC about “Web geoprocessing services on GML with a fast
XML database”She proved the feasibility of some this project’s ideas.
PhD student @UTBackground: Master @Ain Shams University, Cairo about “Automated Arabic
Text Categorization”Strong background in
natural language processing and text/data mining.
Think outside the box