Cyberneutics, Inc. is teamed with the University of Arkansas Center for Advanced Spatial Technologies (CAST) to develop Self-organizing Immersive Local Knowledge (SILK) to enable geospatial analysis with qualitative data. SILK is based on an underlying representation for qualitative topography combining autonomous self-organizing data structures, local knowledge containing multiple socio-cultural perspectives, and immersive user experience, which retains the power of Cartesian rigor inherent in traditional geographic information systems. Current efforts to extend GIS functionality all rely on manual generation of metadata (e.g., geocoding, categorizing, and tagging) for qualitative information artifacts. Analysis based on human-massaged qualitative data that is trapped in cartographic representation cannot supply users with unique socio-cultural perspectives critical to generating non-kinetic courses of action. SILKs transdisciplinary approach draws on swarm intelligence theory and leading edge e-commerce techniques. Self-directed qualitative data wrappers that populate the SILK environment with human terrain artifacts are enabled by social foraging theory and stigmergic collaboration. SILKs ontological framework, which supplies warfighters with tacit knowledge of local culture, is based on collective intelligence and collaborative filtering techniques. Our immersive geospatial interface for visualization and analysis of qualitative data is based on a collaborative prioritization and peering approach that improves over time as a function of use.
Keywords: Social Foraging, Collective Intelligence, Stigmergy, Collaborative Filtering, Human Terrain, Self-Organization, Emergent Phenomena, Qualitative Topography
