Construction Of The Geographic Scenario Data Model And Its Ontological Representation

Traditional Geographic Information Systems(GIS)represent the environment under reductionist thinking,which disaggregates a geographic environment into independent geographic themes.Such thinking affects the development of GIS data model,where most data models are originated from the map view.Current data model makes explicit the spatial,temporal and attributive characteristics of each single geo-feature,but neglects the holistic nature of the environment,such as the hierarchical structure and interactions among environmental elements.Thus,conventional models are insufficient in quering different relationships between features,and can not support complex geographic analysis,calculation and simulation.To fill this gap,this research reconsiders the connotation of geographic environment,and proposes a novel geographic scenario data model.The proposed data model is closer to the real world which follows the geographic laws.The research content can be summarized as follows:(1)This dissertation summarizes several basic theories of the cognitive science and discusses the deficiencies of applying reductionist thinking in GIScience.Thus,this research emphasizes the importance of holism,and integrates the concept geographic scenario with the fundamental principles of General System Theory to realize the environmental complexity in GIS.With the integration,a geographic scenario constitutes a hierarchy of spatiotemporal frameworks to organize environmental elements and subserve the exploration of their relationships.Moreover,principles of classification for the geographic scenario are made to describe its structure.Based on this,inner elements of the complex system are defined and their mutual relationships are explored according to the six elements of scenario.(2)Accoring to the basic characteristics of geographic features,this research proposes a unified geo-characterization framework,and considers both static and dynamic properties of a geographic scenario and prescribes spatial,temporal,semantic,and mutual relationships between different environmental elements.Among these characterizations,the contents and implementation methods of spatial,temporal,semantic and attributive properties are defined based on traditional approaches.The relational characteristic is further classified into four aspects,which are spatial relationship,temporal relationship,semantic relationship and attributive relationship.These relationships can describe unique features of the geographic scenario.With a reference to the ‘process-state’ representation method,this research integrates ideas from the linking mechanism of a DNA molecular,and proposes a multi-helix chain model to express the evolution of a geographic scenario.(3)Previous logic model is not proficient in representing the relationships between geo-features,while the ontology can meet the requirement,and has stronger semantic reasoning ability.Thus,this research implements the above geo-characterization framework with ontological commitments,and utilizes the OWL language to normalize the scenario as well as its components.Moreover,a corresponding ontological population method is proposed to expand the data.(4)Physical realization is important for a data model and closely related to the database.Since relational database is not suitable to store the ontological data,a graph database is selected in this dissertation.To accomplish this goal,the development and basic elements of Neo4 j database are analyzed firstly.Moreover,the database schema is designed for the geographic scenario data.(5)To test the utility of the proposed data model,this paper constructs a multi-hierarchical instance to represent the human scenario,which contains various elements.Rich query results can be obtained to describe the hierarchical structure of geographic scenarios,and interactions and evolution of each individual with the proposed data model.The proposed representation encodes geographic knowledge of the environment,makes explicit the interactions among environmental elements,supports geographic process simulation,opens opportunities for deep knowledge mining,and grounds a foundation for Geo AI to discover geographic complexity and dynamics beyond the support of conventional theme-centric inquiries in GIS.The innovation points of the research can be summarized as follows:(1)This paper proposes a novel cognitive approach which introduces the Gestalt Gognitive Theory and General System Theory to understand the holistic nature of geographic envrionement.(2)A multi-helix chain model is inspired by the structure of the DNA molecular,which can be used to present the evolution of multiple geographic features.Moreover,the conceptual model builds a hierarchical structure to express the complex relationship in the geographic world.(3)To generate and store the ontological data effectively,the corresponding data population method and Neo4 j database storage schema are proposed.The geographic scenario data model can be then realized to express the structure of geographic environment,the complex relationships between different features and the evolution process of each feature.