SMWCon Fall 2013 | |
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Potential analysis for hydro power using Semantic MediaWiki | |
Talk details | |
Description: | A short talk about how Semantic MediaWiki can be used for hydrological analysis |
Speaker(s): | Robert Ulrich |
Slides: | see here |
Type: | Talk |
Audience: | Everyone |
Event start: | 2013/10/29 05:30:00 PM |
Event finish: | 2013/10/29 06:00:00 PM |
Length: | 30 minutes |
Video: | click here |
Keywords: | Hydrology, Sparql, Scribunto |
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Robert Ulrich1, Jürgen Ihringer2, Benedikt Kämpgen3, Joachim Liebert2
1Fakultät für Wirtschaftswissenschaften, Karlsruher Institut für Technologie (KIT)
2Institut für Wasser und Gewässerentwicklung – Fachbereich Hydrologie, Karlsruher Institut für Technologie (KIT)
3Institut für Angewandte Informatik und Formale Beschreibungsverfahren – Forschungsgruppe Wissensmanagement, Karlsruher Institut für Technologie (KIT)
The wish for clean and ecologically sustainable energy lead to a stronger focus on renewable energy systems. Besides wind and solar power, the energy turnaround raises questions about an increased usage of water power as an energy source. In Germany, the unused potential is considered to be highest in the regions of Baden-Württemberg and Bavaria. Due to ecological and various other constraints for building power plants within the river basin, it is discussed controversially.
The catchment area of the Kocher in Baden-Württemberg was chosen as an exemplary subject for the hydrological and water management analysis. Semantic MediaWiki served as extensible tool for merging different data sources, calculating and presentation.
The first step covered the modelling and integration of the hydrological data provided as shape files, csv and other formats into a rdf triplestore, which SMW was connected to.
The second task was to query the data within the wiki and to apply the necessary calculations of the hydrological model. For this end scribunto has been extended and used besides it designate role as an improvement for templates.
Finally the results were illustrated together with the geographical data within the wiki. In a further step, the integration of open data from other sources was evaluated.