Title: Using Combinatorial Auctions to Optimize Querying the Web of Data
Abstract: The Semantic Web is to computers what the traditional web is to humans. It structure data in a way that is easily accessible for computers and allows them to run efficient queries on this data. Unfortunately, this excludes advertisement, the main source of income of traditional websites and makes it difficult to make money. Most existing semantic web databases are parts of research projects funded by subsidies and run out of date or disappear once these projects end. We want to tackle this problem by introducing a new platform which uses a market-based approach, namely a combinatorial auction, to auction off access to semantic web data and determine prices based on supply and demand. We have run various simulations and will show the results to show advantages of such an approach and also talk about future work that still needs to be done in order to set up a platform that can ultimately match semantic web queries and providers of semantic web data to determine prices that encourage providers to keep their data up to date and offer it to the public.
