Data mash-up: A winning thesis
The Danish Society for Computer Science has announced the award of the best thesis in computer science for 2009.
The announcement states:
“The prize for the best thesis in computer science was shared by two winning theses, who shared the honour and Danish IT's premium. The two winning thesis will be presented in a double lecture in Danish Society for Computer Science Thursday 9th September 2010. At the Society’s meeting on Thursday 3 June 2010 awarded the Danish Society for Computer Science year thesis prize in Computer Science. The prize was shared by two winning theses, which were named among the eight nominated theses, of which five were selected for the finals:
Jacob Aarøe Dam, Department of Computer Science, Aalborg University "A web-based weather service for wind sports." Supervisor: Olivier Danvy, CS AU
Rasmus Fonseca, Datalogisk Institut, Københavns Universitet
"Ab Initio Protein Structure Prediction using Bezier Curve Representation." Associate Professor Pawel Winter, DIKU Besides honour comes a cheque for DKr 10,000 donated by DANISH IT - this was this year divided between the two.
Jacob Aarøe Dam’s thesis seeks Web-based help with kite-and wind-surfers, and Jacob make a state-of the art of Web service via Google's App Engine "at one end" and a mobile phone interface in the other. In each of the many steps needed to move towards a service running, considering he thoroughly all realistic alternatives, their possibilities and limitations, and argues for his election. There is a neat distinction between the generic Web service part of Jacob Example application and Web service component is described thoroughly and serve as a recipe for others who will realize a similar Web service for a second application.”
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Extract from the We Love Wind web service:
“About We Love Wind
We Love Wind is the means to realize my MSc thesis: that online weather data can be harvested and combined with new data in a mashup to assist the practitioners of wind sports. Such a mashup is a global weather service that provides users with relevant wind information tailored for the individual users. In particular, this means that 1) wind data is synthesized and transformed to weather information in a way that is relevant for wind sports; 2) only wind information relevant for the user’s location is served; and 3) wind information is accessible through the means of its user such as a standard computer or a cell phone.
The dissertation ("A Web-Based Weather Service for Wind Sports") describes the foundations, design, and implementation of the mashup (We Love Wind) that assists practitioners of wind sports. The problem consists of three parts: (1) obtaining weather forecasts and weather observations from weather resources; (2) creating Web Services that serve representations of relevant data; and (3) creating a Web Service client that presents the data in a comprehensible matter for users.”
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