Tag Archives: Maps

The Triangle of Sustainability Awarded

Triangle of Sustainability show is a way to interact with large amounts of Linked Spatiotemporal Data to support understanding of the ecological, social and economical dimensions of sustainable development.

The Triangle of Sustainability (in German “Dreieck der Nachhaltigkeit”) by  Thomas Bartoscheck and Tomi Kauppinen from the Institute for Geoinformatics at the University of Münster was  awarded with a Finalist Position and is competing for the first prize  in Wissenschaft interaktiv 2012, June 2–6, 2012, Lübeck, Germany.

The Triangle of Sustainability is an interactive show to explore observations about deforestation of rainforests and related phenomena such as road networks, political situation, and market prices of agricultural products on maps and timelines.  The Triangle thus connects three important aspects–ecological, economical and social–of sustainability. By doing this the Triangle serves as a show of what is achievable by  interconnecting different scientific assets via the Linked Science approach. The goal is to raise the awareness, and understanding of different factors of sustainability. The Triangle thus serves as an example of how the research field of Geoinformatics, and more generally Geographic Information Science can serve the society in these tasks.

The resulting information can be explored on three screens (see the figure above). The interaction is made extremely simple yet powerful, no additional tools are required for the participants. All the spatial and temporal information can be zoomed and panned simply by making gestures using hands.

The technological basis is built on the power of Linked Data techniques for interconnecting these very heterogenous data about different environmental and social phenomena. The data used by the show is the Linked Brazilian Amazon Rainforest published at LinkedScience.org.


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).