Ontology and Geographic Kinds

Cognitive categories in the geographic realm appear to manifest certain special features as contrasted with categories for objects at surveyable scales. We have argued that these features reflect specific ontological characteristics of geographic objects. This paper presents hypotheses as to the nature of the features mentioned, reviews previous empirical work on geographic categories, and presents the results of pilot experiments that used English-speaking subjects to test our hypotheses. Our experiments show geographic categories to be similar to their non-geographic counterparts in the ways in which they generate instances of different relative frequencies at different levels. Other tests, however, provide preliminary evidence for the existence of important differences in subjects’ categorizations of geographic and non-geographic objects, and suggest further experimental work especially with regard to the role in cognitive categorization of different types of object-boundaries at different scales

Ontology with Human Subjects Testing: An Empirical Investigation of Geographic Categories

Ontology, since Aristotle, has been conceived as a sort of highly general physics, a science of the types of entities in reality, of the objects, properties, categories and relations which make up the world. At the same time ontology has been for some two thousand years a speculative enterprise. It has rested methodologically on introspection and on the construction and analysis of elaborate world-models and of abstract formal-ontological theories. In the work of Quine and others this ontological theorizing in abstract fashion about the world was supplemented by the study, based on the use of logical methods, of the ontological commitments or presuppositions embodied in scientific theories. In recent years both types of ontological study have found application in the world of information systems, for example in the construction of frameworks for knowledge representation and in database design and translation. As ontology is in this way drawn closer to the domain of real-world applications, the question arises as to whether it is possible to use empirical methods in studying ontological theories. More specifically: can we use empirical methods to test the ontological theories embodied in human cognition? We set forth the outlines of a framework for the formulation and testing of such theories as they relate to the specific domain of geographic objects and categories

Ontology, natural language, and information systems: Implications of cross-linguistic studies of geographic terms

Ontology has been proposed as a solution to the 'Tower of Babel' problem that threatens the semantic interoperability of information systems constructed independently for the same domain. In information systems research and applications, ontologies are often implemented by formalizing the meanings of words from natural languages. However, words in different natural languages sometimes subdivide the same domain of reality in terms of different conceptual categories. If the words and their associated concepts in two natural languages, or even in two terminological traditions within the same language, do not have common referents in the real world, an ontology based on word meanings will inherit the 'Tower of Babel' problem from the languages involved, rather than solve it. In this paper we present evidence from a preliminary comparison of landscape terms in English with those in the Yindjibarndi language of northwestern Australia demonstrating that this problem is not just hypothetical. Some possible solutions are suggested

Conceptualizing landscapes through anguage: the role of native language and expertise in the representation of waterbody related terms

Landscapes are essential to human life: they provide a multitude of material (food, water, pollination) and nonmaterial (beauty, tranquility, recreation) values. Their importance is enshrined in international conventions and treaties, committing signatories to protecting, monitoring, and managing all landscapes. Yet, relatively little is known about how people conceptualize “landscape” and its constituents. There is emerging evidence that conceptualizations of landscape entities may influence landscape management. This in turn raises the question as to how people speaking different languages, and with differing levels of expertise, may differ in conceptualizing landscape domains as a whole. In this paper, we investigated how people conceptualize landscape-related terms in a specific domain—waterbodies—by comparing German and English-speaking experts and nonexperts. We identified commonly used waterbody terms in sustainability discourses in both languages, and used those terms to collect sensory, motor, and affective ratings from participants. Speakers of all groups appear to conceptualize the domain of waterbody terms in comparable ways. Nevertheless, we uncovered subtle differences across languages for nonexperts. For example, there were differences in which waterbodies were associated with calm happiness in each language. In addition, olfaction seemingly plays a role in English speakers’ conceptualization of waterbodies, but not German speakers. Taken together, this suggests the ways in which people relate to landscape although shared in many respects may also be shaped in part by their specific language and culture

A Geographic Ontology and GIS Model for Carolina Bays

Carolina bays are a unique geomorphologic entity located along the Atlantic coastal plain. Even without the benefit of an overhead view, they have been noted as a distinct feature of the coastal plain as first described by the South Carolina Geological Survey of South Carolina in 1848. The first aerial photographs in the 1930 coastal South Carolina region revealed that the unique depression wetlands were more than just a strange local phenomenon. Aerial photos enabled observers to see qualities in addition to their relative distribution that make them unique: their oval shape, northwest to southeast orientation and the presence of raised sand rims along their eastern and southeastern edges in many instances. Being such a distinctive surface feature and recognized for their ecological value, it would seem that Carolina bays would have been defined within their own map coverage across the Atlantic Coastal plain. However, just two statewide inventories have been completed for South Carolina and Georgia, and one for North Carolina has never been conducted. While previous inventories have employed onscreen digitization with Geographic Information Systems (GIS) in order to inventory bays, researchers have raised concerns over how individuals define Carolina bay as a geographic entity. The differences in human perception make the classification of geographic entities that exist on a continuum such as Carolina bays a challenge and may have contributed to widely varying estimates of their numbers. In order to explore the classification issues related to Carolina bays, and the usefulness of geographic ontology and cartographic modeling for inventory, a cartographic model was constructed for use within the Ocean Bay quad in Francis Marion National Forest in Berkeley and Charleston Counties, South Carolina. To test the model’s selective ability, a comparison was made between Carolina bay features that a researcher selected and bays identified by a cartographic model. The model positively identified 76 percent of Carolina bays that a researcher identified in an image within a single quadrangle. The approach used in this model showed that the initial identification rule of any pixel within a bay’s border counted as a positive identification was inadequate. Other aspects not accounted for, including false positive identification, neither researcher nor model being able to identify a bay, or bays that the model was able to select that the researcher was not were added into a subsequent model. Results from the amended model show fewer researcher identified instances of Carolina bays, but a slightly higher rate of mutual identification by the model and the researcher. With these complications in mind, a similar approach was taken with Bladen County North Carolina, but with significant revisions. A cartographic model was created for Bladen County North Carolina in which bay characteristics were selected from the North Carolina Gap Analysis Program (GAP) land use/landcover dataset, the Soil Survey Geographic Database (SSURGO) and National Wetlands Inventory (NWI). The predictive ability of the model was assessed by manually selecting Carolina bays from a high resolution image and comparing the manually selected bays with the model identifications. In order to remedy the issue of forcing all instances of bays into one of two categories (either an object is a bay or it is not), a ranking system was developed that was based upon a core/radial cognitive model, and the approach taken with the Savannah River Ecology Lab (SREL) inventory. The rule for positive identification was changed from a single pixel to a visual estimation of 50 percent coverage of a Carolina bay. As a whole, the predictive model identified 57 percent of the features also identified manually by the researcher, but the bay ranking system gives a different breakdown of how well the model worked within each category: exemplar (86 percent), less distinct (79 percent), bay-like (53 percent), and destroyed (19 percent) show significant differences. In addition to the ranking system, other attributes were assessed, such as the presence or absence of a sand rim, water visibility, overlap, diverging, long axis length and orientation. The analysis shows that the model has the potential to identify well defined bays with at least 50 percent areal coverage, and as such offers the first iteration of a computational ontology for the Carolina bays of Bladen County, North Carolina. Results from this research may provide a basis for modeling the entire range of Carolina bays, defining one of the most curious features of the Atlantic Coastal Plain and uniting differing definitions under one digital concept

Microtheories for SDI - Accounting for diversity of local conceptualisations at a global level

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.The categorization and conceptualization of geographic features is fundamental to cartography, geographic information retrieval, routing applications, spatial decision support and data sharing in general. However, there is no standard conceptualization of the world. Humans conceptualize features based on numerous factors including cultural background, knowledge, motivation and particularly space and time. Thus, geographic features are prone to multiple, context-dependent conceptualizations reflecting local conditions. This creates semantic heterogeneity and undermines interoperability. Standardization of a shared definition is often employed to overcome semantic heterogeneity. However, this approach loses important local diversity in feature conceptualizations and may result in feature definitions which are too broad or too specific. This work proposes the use of microtheories in Spatial Data Infrastructures, such as INSPIRE, to account for diversity of local conceptualizations while maintaining interoperability at a global level. It introduces a novel method of structuring microtheories based on space and time, represented by administrative boundaries, to reflect variations in feature conceptualization. A bottom-up approach, based on non-standard inference, is used to create an appropriate global-level feature definition from the local definitions. Conceptualizations of rivers, forests and estuaries throughout Europe are used to demonstrate how the approach can improve the INSPIRE data model and ease its adoption by European member states

Ontology-Driven Geographic Information Systems

Information integration is the combination of different types of information in a framework so that it can be queried, retrieved, and manipulated. Integration of geographic data has gained in importance because of the new possibilities arising from the interconnected world and the increasing availability of geographic information. Many times the need for information is so pressing that it does not matter if some details are lost, as long as integration is achieved. To integrate information across computerized information systems it is necessary first to have explicit formalizations of the mental concepts that people have about the real world. Furthermore, these concepts need to be grouped by communities in order to capture the basic agreements that exist within different communities. The explicit formalization of the mental models within a community is an ontology. This thesis introduces a framework for the integration of geographic information. We use ontologies as the foundation of this framework. By integrating ontologies that are linked to sources of geographic information we allow for the integration of geographic information based primarily on its meaning. Since the integration may occurs across different levels, we also create the basic mechanisms for enabling integration across different levels of detail. The use of an ontology, translated into an active, information-system component, leads Ontology-Driven Geographic Information Systems. The results of this thesis show that a model that incorporates hierarchies and roles has the potential to integrate more information than models that do not incorporate these concepts. We developed a methodology to evaluate the influence of the use of roles and of hierarchical structures for representing ontologies on the potential for information integration. The use of a hierarchical structure increases the potential for information integration. The use of roles also improves the potential for information integration, although to a much lesser extent than did the use of hierarchies. The combined effect of roles and hierarchies had a more positive effect in the potential for information integration than the use of roles alone or hierarchies alone. These three combinations (hierarchies, roles, roles and hierarchies) gave better results than the results using neither roles nor hierarchies

Cognitive aspects of work with digital maps

Digital maps of geographic areas are increasingly common in many types of workplace, in education and in the public domain. Their interactivity and visual features, and the complexity of geographic(al) information systems (GIS) which create, edit and manipulate them, create special cognitive demands on the end-user which are not present in traditional cartographic maps or in most human-computer interaction (HCI). This thesis reviews cross-disciplinary literature regarding cognitive aspects of viewing and interacting with digital maps. Data from an observational study of GIS use, including real-time recordings of normal workplace activities, was analysed using various approaches to examine the interactive and visual aspects of people's work. The implications for cartographic, psychological and HeI aspects of GIS are discussed, in the context of the actual tasks people perform with them (rather than the computationally advanced analyses assumed by most literature). The second phase of the research examined the spatial knowledge attained and used during this interaction. The relevance of specific concepts in cognitive psychology, and of factors that create individual differences in cognition, are discussed in depth, alongside work in environmental and educational psychology, cartography and geography. A controlled experiment examined the degree to which task characteristics induce a different spatial model or reference frame when viewing a digital map. It was shown that even novice users can switch between considering the map as an abstract geometric display or as a geographical representation, without affecting performance. However, tasks forcing subjects to focus entirely on the geometry rather than the geography did affect performance in a surprise post-test photograph identification task. Map users' mental model or reference frame is apparently affected by these task constraints; this has implications for GIS design and practice as well as for understanding spatial cognition The study also considered the role of expertise and other individual difference factors, although conclusions were limited by sample size. Further research issues are highlighted, particularly regarding the knowledge structures and spatial language used in interpreting digital maps