Getting across information communities Embedding semantics in the SDI for the Amazon

Maue P, Ortmann J

Abstract

Amazon's deforestation affects citizens from varying information communities. Experts like scientists or journalists acquire relevant data on-site and publish valuable information on the Web. But different and sometimes conflicting views on reality impede sharing of information across communities, relevant content remains far too often undiscovered. We introduce rule-based semantic annotations as solution to facilitate the discovery and evaluation of geographical information. With the distinction between shared domain and local information source ontologies, the proposed architecture of a semantically supported SDI for the Amazon also takes the plethora of GI formats into account. Creating semantic annotations is challenging, a recommender system for semantic annotations enables even the non-IT experts to participate. The benefits of the proposed techniques are further illustrated by a scenario which spans across information communities of economics, ecology, and ethnology.