[SDI-AsiaPacific] Building a spatial decision support system for conflict prevention in the Caucasus
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Mon May 5 07:50:44 EDT 2008
Building a spatial decision support system for conflict prevention in the Caucasus (JRC Science and Technical Report, 2007)
Harmonization of heterogeneous sources and data quality assessment procedures
JRC started to work on this integrated approach within the context of Neighbouring Countries, on a
particular complex security region : the Caucasus. The geomodeling on the Caucasus aims to provide a holistic view that will include environmental issues related to the security of the region through a quantitative
analysis by means of a Spatial Decision Support System (SDSS). The first step of this approach
consisted of collecting information and data relevant to conflict in the Caucasus region.
Implementation of quality control methods is an initial and essential step in the integration of geodata inside a spatial regional model. This report provides tools for data harmonization that can be applied to other datasets and other region when existing data sources do not evaluate the quality of their information. The goal of this report is to provide a quality assessment of the Caucasian GIS dataset to build the Caucasus geomodel of instability/stability. This report evaluates qualitatively and quantitatively the adequacy of this dataset to the objective in following a structured quality assessment protocol (Johnston et al. 1999) and consolidates a final geodatabase. Integrating data from a multitude of derivative geospatial products produced by different sources pose severe problems. Challenges are also introduced by the GIS technology itself. Various data are introduced in this study but the main source of statistical and spatial information is
the acquisition of the geopolitical atlas dataset, the “Caucasian dataset” (Radvanyi, INALCO, 2006). In this report, four data quality elements are identified and described in the specific case of the Caucasian dataset. Lineage information, the three accuracy dimensions (positional, temporal and attribute), logical consistency and completeness evaluations are qualitatively and quantitatively assessed by various metrics. This paper illustrates the use of automatic cartographic and data cleanup techniques of Geographic Information System (GIS) to solve data issues (self overlapping, dangles, pseudonodes and gap in spatial data). This report can further be used as a reference for both the producer and the user to somewhat replace the missing metadata information. Clear statements on dataset quality allow to better communicate in a common goal of understanding the geopolitical Caucasus context.
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