Automatic grounding of vague geographic ontology in data

In constructing an ontological theory of a domain such as geography, it is important not only to take account of the vagueness and ambiguity which is inherent in many of the relevant concepts, but also to be able to relate the high-level definitions of the theory to actual sets of data of varying kinds. Any attempt to ignore or remove vagueness and ambiguity risks errors and conflict in the ontological theory with the knowledge of different domain experts, while an inability to ground the theory in real data limits its practical use. We present here a means of structuring such a theory to handle these issues in a principled manner, which lends itself to concrete implementation. We illustrate with reference to several examples from the domain of hydrography

An Ontology for Grounding Vague Geographic Terms

Many geographic terms, such as “river” and “lake”, are vague, with no clear boundaries of application. In particular, the spatial extent of such features is often vaguely carved out of a continuously varying observable domain. We present a means of defining vague terms using standpoint semantics, a refinement of the philosophical idea of supervaluation semantics. Such definitions can be grounded in actual data by geometric analysis and segmentation of the data set. The issues raised by this process with regard to the nature of boundaries and domains of logical quantification are discussed. We describe a prototype implementation of a system capable of segmenting attributed polygon data into geographically significant regions and evaluating queries involving vague geographic feature terms

Geospatial Semantics

Geospatial semantics is a broad field that involves a variety of research areas. The term semantics refers to the meaning of things, and is in contrast with the term syntactics. Accordingly, studies on geospatial semantics usually focus on understanding the meaning of geographic entities as well as their counterparts in the cognitive and digital world, such as cognitive geographic concepts and digital gazetteers. Geospatial semantics can also facilitate the design of geographic information systems (GIS) by enhancing the interoperability of distributed systems and developing more intelligent interfaces for user interactions. During the past years, a lot of research has been conducted, approaching geospatial semantics from different perspectives, using a variety of methods, and targeting different problems. Meanwhile, the arrival of big geo data, especially the large amount of unstructured text data on the Web, and the fast development of natural language processing methods enable new research directions in geospatial semantics. This chapter, therefore, provides a systematic review on the existing geospatial semantic research. Six major research areas are identified and discussed, including semantic interoperability, digital gazetteers, geographic information retrieval, geospatial Semantic Web, place semantics, and cognitive geographic concepts.Comment: Yingjie Hu (2017). Geospatial Semantics. In Bo Huang, Thomas J. Cova, and Ming-Hsiang Tsou et al. (Eds): Comprehensive Geographic Information Systems, Elsevier. Oxford, U

Handling vagueness in ontologies of geographical information

This thesis presents a novel approach to the problem of handling vagueness in ontologies of geographical information. Ontologies are formal representations of a set of concepts and the relationships that hold between those concepts. They have been proposed as a method of representing geographical information logically, but existing limitations in ontology languages and approaches fail to handle aspects of the geographical domain adequately, such as vagueness. The technique introduced in this thesis does not seek to remove or ignore the inherent vagueness when reasoning about geographic features, but rather seeks to incorporate it into decisions made about features during this process. By improving themanner in which vagueness is handled in geographical information systems, we improve the usability and the functionality of such systems, and move towards a more natural method of interaction. A comparison of the principal vague reasoning approaches is presented, to show how there is not at present a universal approach that handles all forms of vagueness. Rather, there exist different forms of vagueness as well as different required outcomes of vague reasoning, which means we should instead consider the problem at hand and determine the most appropriate approach accordingly. The technique for handling vagueness proposed here is to provide a systemfor grounding an ontology upon a geographic dataset. This data is assumed to take the form of a set of 2-dimensional polygons, each of which may be associated with one or more labels describing the type of region that polygon represents and the attributes associated with it. By grounding the ontology onto the data, an explicit link is made between the ontology and the data. Thus, vagueness within the definitions at the ontology level can be handled within the context of the dataset used; “large” can be defined in terms of what it means to be “large” in this dataset. Further, I developed a system that allows querying of the data and returns features through spatial reasoning. This allows the extractio

A comprehensive evaluation of alternatives for the provision of health care to the medically indigent in Nebraska

Several alternatives for the provision of health care to the medically indigent of Nebraska were analyzed both quantitatively and qualitatively. These alternatives were: expansion of County Medical Assistance Programs, state-purchased health insurance policies, Medicaid expansion, revenue pool to redistribute charity care losses, all-payer rate system, mandated employer-purchased health insurance, and charity care districts. These alternatives were subjected to both cost and sensitivity analysis, then ranked on the basis of both quantitative and qualitative criteria. Qualitative criteria were: maintenance of the 1985 level of health, inclusion of preventive health measures, equity in distribution of unreimbursed medical expenses, and reduced incentives for cost-shifting. Quantitative criteria were cost, and percentage of medically indigent served. Qualitative criteria were integrated using the Delphi Method, and Saaty\u27s Analytical Hierarchy via Expert Choice. Impact analysis for each alternative on Nebraska\u27s health care delivery system was also performed, including the effect on total state disposable income. The alternatives were tested further under four scenarios representing expected future changes in the health care delivery system. These scenarios are: federal matching funds reduction, charity care reductions, state funding reduction, and increase in medical indigents. In this analysis the effects of varying factors, previously held constant at 1985 levels, were assessed for all criteria. The alternatives were then reranked, with state-purchased health insurance scoring highest most consistently. It is recommended that the state adopt a combination of Medicaid expansion and state-purchased health insurance. This combination would best meet all qualitative criteria at a minimum system cost per indigent served. If the recommended comprehensive program cannot be undertaken, a combination of programs is suggested for further research. These include Medicaid expansion, local health department expansion, state-paid insurance continuation, revenue pool, on-site medical teams and patient-imposed care limits. Because it is cost effective, prevention is emphasized by these programs