Friday, March 12th, 2010 | Author:

To improve the integration of the new faculty ITC (Geo-Information Science and Earth Observation) into the university, the boards of directors of ITC and UT decided some time ago to subsidize several cooperation projects with each two PhD students, one at ITC and one at the UT. I am involved in one: “Neogeography:┬áthe challenge of channelling large and ill-behaved data streams” (see description below). Rolf de By (ITC) and I presented our Neogeography project on the Kick-off meeting 12 March 2010 [presentation]. Rolf’s PhD student is Clarisse Kagoyire and she arrived in The Netherlands just in time to make it to the meeting. My PhD student is Mena Badieh Habib; he will start 1 May 2010.

Neogeography: the challenge of channelling large and ill-behaved data streams
In this project, we develop XML-based data technology to support the channeling of large and ill-behaved neogeographic data streams. In neogeography, geographic information is derived from end-users, not from official bodies like mapping agencies, cadasters or other official, (para-)governmental organizations. The motivation is that multiple (neo)geographic information sources on the same phenomenon can be mutually enriching.
Content provision and feedback from large communities of end-users has great potential for sustaining a high level of data quality. The technology is meant to reach a substantial user community in the less-developed world through content provision and delivery via cell phone networks. Exploiting such neogeographic data requires a.o. the extraction of the where and when from textual descriptions. This comes with intrinsic uncertainty in space, time, but also thematically in terms of entity identification: which is the restaurant, bus stop, farm, market, forest mentioned in this information source? The rise of sensor networks adds to the mix a badly needed verification mechanism for the real-time neogeographic data.
We strive for a proper mix of carefully integrated techniques in geoinformation handling, approaches to spatiotemporal imprecision and incompleteness, as well as data augmentation through sensors in a generic framework with which purpose- oriented end-user communities can be served appropriately.
The UT PhD position focuses on spatiotemporal data technology in XML databases and theory and support technology for storage, manipulation and reasoning with spatiotemporal and thematic uncertainty. The work is to be validated through testbed use cases, such as the H20 project with google.org (water consumers in Zanzibar), AGCommons project with the Gates Foundation (smallholder farmers in sub-Saharan Africa), and other projects with large user communities.

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