Semantically Enriched POI as Ontological Foundation for Web-Based and Mobile Spatial Applications

While developing a Web-based travel planning system, the necessity to implement a mobile component has been identified. Such a conception is aimed at a comprehensive support of a workflow that enables users to plan a trip in advance using the Web-based application, but to modify the original plan wherever and whenever they want while carrying out the journey. Within both components, Point-of-Interest (POI) plays a significant role to determine a tour. It is one claim of this chapter that the relevance of POI is dependent on the perspective of a user. As a consequence, the originally used POI database was replaced by a POI ontology which promised to support the workflow more comprehensively. This conceptual change raised several questions concerning the domain dependence of the POI ontology on the one side and universal aspects of the ontology on the other.

Geographical Process Representation

This chapter discusses the issues and challenges arising when building a general spatio-temporal ontology for representing and reasoning of geographical processes as part of a desired universal semantic reference system of geographic space. It examines the foundations and formalisms upon which the development of such an ontological model of geographical processes can be based. The chapter begins by providing a background of essential concepts related to the representation of geographical processes. Then overviews of several approaches to representing spatio-temporal processes and how to associate them with geographic space are given. Following this, the chapter discusses several open issues on the topic and presents a set of desiderata for representing and reasoning about real-world dynamic geographical phenomena. This discussion covers aspects of space, time, object, event, state, and process as the essential concepts to represent geo-processes. It also covers aspects of spatial-temporal granularity and spatio-temporal aggregation, describing how they relate to geographical processes. Finally, this chapter also explores the phenomenon of vagueness and how it affects the representation and reasoning about geo-processes. The chapter concludes by indicating directions for future research and recapitulating its overall coverage.

Geographic Space Ontology, Locus-Object, and Spatial Data Representation Semantic Theory

Within the general framework of the analysis of the geographic space and its ontological components by remote sensing, the author explores the ability of the morphogenetic modeling in the recognition of one major ontological and semantic concept of geography: the “locus-object.” The “locus-object” couple concept results from the interrelation formalization between the geographic locus, the geographic object, and the geo-localization notions. Geographic loci and objects are linked and both geo-localized. The links and relations between locus and object are mathematically formalized by geospatiology, the study of the logical role of space in the study of entities on the surface of the Earth. Morphogenetic modeling recognizes the loci of the geographic space by spatial discontinuities detection. The spatial discontinuities allow the identification of the types of spatial differentiations (boundaries, limits) between two geographic entities. The concept of “locus-object” is one of the key conceptual ontological elements of the geographic space.

Universal Geospatial Ontology for the Semantic Interoperability of Data

Ontologies have been used to support the interoperability of geospatial data by overcoming semantic problems related to semantic heterogeneities and to differences in data usage contexts. Ideally, to solve semantic heterogeneities, the data models involved in the interoperability process could be enriched, and the relationships between their elements could be defined based on a universal geospatial ontology. However, such ontology would encounter difficulties in achieving an efficient interoperability. This chapter aims to argue that universal ontology-based interoperability remains vulnerable to the risks of uncertain meaning of geospatial data that may go unnoticed during the interoperability process. The chapter discusses these risks and proposes a systematic approach to better support users dealing with them. The proposed approach identifies the risks, assesses their severity, and helps users to make decisions about them.

Ontology Engineering Method for Integrating Building Models

The Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) are the two most prominent semantic models for the representation of Building Information Models (BIM) and geospatial objects. IFC and CityGML use different terminologies to describe the same domain, and there is a great heterogeneity in their semantics. For bidirectional conversions between these models, an intermediate Unified Building Model (UBM) is proposed that facilitates the transfer of spatial information from IFC to CityGML and vice versa. A unified model in the current study is defined as a superset model that is extended to contain all the features and objects from both IFC and CityGML building models. The conversion is a two-steps process in which a model is first converted to the unified model and then to the target model.

Human Cognition

Human cognition is a complex process of processing information. It is highly influenced by different factors, such as general concepts, individual characteristics, etc. This chapter deals with the topic of cognition of spatial information. Evolution of cognition is described and evaluated in it. The adaptive function of cognition is discussed in the context of ecological psychology. The current approaches to cognition problems are introduced, and the basic terms and concepts are explained. The ratio of cultural influence is compared with the influence of personality traits and the developmental stage of the individual. The aim of the chapter is to outline possible difficulties of designing a universal ontology describing geographic space on an interregional and global scale.

Unified Rule Approach and the Semantic Enrichment of Economic Movement Data

This chapter suggests a methodology for semantic enrichment of spatial data resulting from economic behavior. The proposed methodology has a universal scope and could be applied to any behavior involving the movement of an entity for economic reasons. The proposed methodology has its foundations in an evolutionary approach and subscribes to the axioms of evolutionary ontology. The proposed methodology is in line with Kuhn’s claim for the design of ontologies with a focus on human activities in geographic space; but rather than applying text analysis and limiting the focus to ontology in information science, the author enriches the semantic reference system of economic movement data with an ontology based on the general analytical framework of economic evolution stated in terms of a unified rule approach. This, the authors argue, results in an analytical ontology of geographic space and an enhanced understanding of economic movement data. The ontological, analytical, and theoretical propositions are applied to a data set of historical ship movements.

Representing Geospatial Concepts

Knowledge representation of geospatial entities is dependent on the ability to share their structural properties along with their functional properties, which define their usage for human-society. However, geospatial ontologies have mainly relied on taxonomy-based and mereology-based ontologies. While structural properties of entities such as shape, topography, and orientation are considered important tools for geospatial ontologies, existence of structural properties are not sufficient conditions for the existence of functional properties. Contrastingly, a parallel approach assumes independent existence of function-based concept hierarchies and builds on the premise that human activities associated to any given geospatial entity are essential for specification of the entity concept itself. This chapter compares two diverging approaches based on cases drawn from physical geography, transportation, and hydrology. The differences in core concepts and tools are discussed in relation to universal ontologies of geographic space. It is argued that function representation in geospatial ontologies, in combination with structure-based concepts of geospatial entities, is both necessary and challenging.

Toward an Architecture for Enhancing Semantic Interoperability Based on Enrichment of Geospatial Data Semantics

Semantic interoperability is needed to support meaningful data exchanges in distributed environments such as ad hoc networks of geospatial databases and geospatial web services. Even with the increasing popularity of ontologies to capture semantics, semantics of geospatial data are often too weak to support meaningful exchanges. In this chapter, the authors argue that semantically weak geospatial data can be enriched to enhance semantic interoperability. They propose a conceptual architecture designed to support enhanced semantic interoperability in dynamic networks that focuses on semantic enrichment. The proposed conceptual architecture includes a coalition management module, an ontology enrichment module, and a semantic mapping module; the modules perform different types of semantic enrichment and can support various semantic interoperability tasks. Within the different enrichment methods, the authors explain the role of global ontologies, arguing that they play a key role in a semantic interoperability framework. Finally, the authors illustrate with an application example the possibilities of such architecture.

Ontologies for the Design of Ecosystems

Environmental regulations require that land development decisions have to be accompanied by clear, accountable decision-making processes to communicate to the possible public repercussions of development. The suitability mapping approach is widely adopted to fill this need. However, in typical applications of suitability mapping, the dynamics and interrelatedness of ecosystems’ structure and processes are often overlooked. Environmental assessment procedures require scientists and designers to join forces, and the demand for shared concepts and semantic language is growing. Better ways of interpreting and incorporating ecological principles, especially those that emphasize the probabilistic, dynamic nature of nature, into ecosystem design and planning are needed. This chapter presents guidelines and experiences about the modeling and implementation of utility ontologies for the design of ecosystems, together with a case study. Utility ontologies are knowledge representations that include general concepts that most services need to use to represent spatial and temporal data.