Geospatial Narratives and Their Spatio-Temporal Dynamics: Commonsense Reasoning for High-Level Analyses in Geographic Information Systems

Abstract

Abstract:The modeling, analysis and visualization of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about space, events, actions and change. With this as a basis and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solution techniques chiefly involving qualitative abstraction, data integration and spatial consistency and practical geospatial abduction.Keywords: Geographic Information Systems; spatio-temporal dynamics; computational models of narrative; events and objects in GIS; geospatial analysis; ontology; qualitative ISPRS Int. J. Geo-Inf. 2014, 3 167 spatial modeling and reasoning; artificial intelligence; spatial assistance systems; decision-support systems

Logic Programming and Nonmonotonic Reasoning

“…Dynamic spatial systems are characterised by scenarios where spatial configurations of objects undergo a change as the result of interactions within a physical environment [9]; this requires explicitly identifying and formalising relevant actions and events at both an ontological and (qualitative and geometric) spatial level, e.g. formalising desertification and population displacement based on spatial theories about appearance, disappearance, splitting, motion, and growth of regions [10]. This calls for a deep integration of spatial reasoning within KR-based non-monotonic reasoning frameworks [7].…”

Non-monotonic spatial reasoning with answer set programming modulo theories

“…CLP(QS) marks a clear departure from other relational algebraically founded methods and reasoning tools by its use of the constraint logic programming framework for formalising the semantics of qualitative spatio-temporal relations and formal spatial calculi. CLP(QS) has demonstrated applications in a range of domains including: architectural design cognition , cognitive vision Suchan et al 2014;Suchan and Bhatt 2016a;Suchan and Bhatt 2016b), geospatial dynamics (Bhatt and Wallgrün 2014), and cognitive robotics (Eppe and Bhatt 2013;Spranger et al 2014;Spranger et al 2016). …”

“…• within the context of geographical information systems, formalising high-level processes such as desertification and population displacement based on spatial theories about appearance, disappearance, splitting, motion, and growth of regions (Bhatt and Wallgrün 2014);…”

Data Association at the Level of Narrative Plots to Support Analysis of Spatiotemporal Evolvement of Conflict: A Case Study in Nigeria

“…However, these approaches are unsuitable for modeling unclear objects, and they must mine notable items in a preprocessing step through the use of data mining techniques [36], e.g., the Apriori association rule mining [37]. For data organization based on more general semantics, the narrative framework is often taken as a platform for shipping various types of data [17]. When integrating data at the semantic level, such a framework can provide an effect similar to storytelling.…”