Category Archives: GIS

Demo and Poster today @ESWC2012

Today on May 29th a poster and a demo will be presented at the 9th Extended Semantic Web Conference (ESWC2012) related to Linked Science and LODUM projects. The poster and the demo will be presented next to each other at the Posters and Demos session for your convenience.

The poster

is about  Sharing and Analyzing Remote Sensing Observation Data for Linked Science and presents the Linked Brazilian Amazon Rainforest project. Below is a figure illustrating how to interact with these large amounts of Linked Spatiotemporal Data to support understanding of the ecological, social and economical dimensions of sustainable development. For more information see also the Triangle of Sustainability project.

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The demo

is about the Linked Open Data University of Münster – Infrastructure and Applications (see also the data portal)The idea is to open up the university’s data silos, integrate the data, and make it easy to build applications on top of the data collection. The productivity map shown as a video below is an example of such an application. It renders the university buildings in 3D—the building height indicates the number of publications written by researchers working in the respective building. The KML file is also available for download—just open it up in Google Earth to explore the productivity map.

 

Tutorial on SPARQL Package for R

Tools are major enablers of Linked Science. One crucial aspect is how to access and analyze data, and especially how to get only that part of data which is of interest for a given research question.  Linked Data solves the access part, and SPARQL allows to query only a subset of the data. For statistical computing there are tools like R. As a solution to bridge the two communities, those of statistical computing and  semantic web, there is now a SPARQL Package for R, which enables to get data from Linked Data services to R for analysis. At LinkedScience.org you may now find a tutorial on SPARQL Package for R. By following it you can learn:

  1. how to access and query Linked Spatiotemporal Data of the  deforestation statistics related to the Brazilian Amazon Rainforest, and
  2. how to analyze it within R (which is a free software environment for statistical computing).