Gahegan, Mark N.

Abstract: This paper describes efforts to extend educational descriptions of learning objects to enable semantic search for suitable resources held within digital libraries and cyberinfrastructure, and describes some further advantages that accrue from the use of formal description languages (ontologies) to describe both pedagogy and domain content. These advantages include: semantic browsing and visualization of learning object contents, advanced search capabilities linking to several different online collections, easy extension of learning objects with external content added by learners and educators, and utilization of the many rich models of education and educational domains now available as ontologies. As well as conceptual justifications and descriptions of our work, we provide examples throughout to concretize the ideas presented, using learning objects developed for college-level education in geography and the geosciences. We conclude with some thoughts on the further possibilities that arise from the application of detailed semantics, and associated reasoning, in the pursuit of genuinely reusable educational content that integrates more closely with community research activities such as exemplified by e-science.

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Abstract: Ontologies are being developed in many geoscientific domains. They are typically populated with two types of concepts: upper-level concepts that apply across many or all domains, and domain concepts that apply only within a specific domain. Previous work has refined this distinction by identifying a particular type of domain concept, called a situated concept, which is dependent on specific processes (natural, social, scientific, or possibly machine) for its meaning and is instantiated amongst entities within a specific geographical and historical context. In this paper we present new support for situated geoscientific concepts, building on our previous research that argues for the importance of situations in the development and use of concepts related to geoscientific field mapping. The new results are obtained by using statistical techniques to further analyze three geologists' field data over time, to better test the hypothesis that the concepts developed by the geologists to classify objects on the map are in fact situated. The field data are compared to each other, and to the concepts developed by the team. Differences found between and within individuals' data for three map concepts provide strong support for the idea that the concepts are variably influenced by data, theory, and natural and human situations. From this increased corroboration of situated concepts we suggest two implications for domain ontologies: (1) a delineation between situated domain concepts and non-situated domain concepts; and (2) recognition that representation of reliable meaning involves the capture of historical and geographical context for situated concepts.

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Abstract: Geovisualization is both a process for leveraging the data resources to meet scientific and societal needs and a research field that develops visual methods and tools to support a wide array of geospatial data applications. While researchers have made substantial advances in geovisualization over the past decade, many challenges remain. To support real-world knowledge construction and decision making, some of the most important challenges involve distributed geovisualization - that is, enabling geovisualization across software components, devices, people, and places.

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Abstract: The advent of remote sensing and survey technologies over the last decade has dramatically enhanced our capabilities to collect terabytes of geographic data on a daily basis. However, the wealth of geographic data cannot be fully realized when information implicit in data is difficult to discern. This confronts GIScientists with an urgent need for new methods and tools that can intelligently and automatically transform geographic data into information and, furthermore, synthesize geographic knowledge. It calls for new approaches in geographic representation, query processing, spatial analysis, and data visualization (Yuan 1998, Miller and Han 2000; Gahegan, 2000). Information scientists face the same challenge as a result of the digital revolution that expedites the production of terabytes of data from credit card transactions, medical examinations, telephone calls, stock values, and other numerous human activities. Collaborative efforts in artificial intelligence, statistics, and databases communities have been the underpinning technologies of knowledge discovery in databases to extract useful information from massive amounts of data in support of decision-making (Gardner 1996, Bhandari et al. 1997, Hedberg 1996).

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Abstract: Geographic information is acquired according to several different underlying models of geographic space. Any meaning inherent within a dataset is intrinsically connected to the model by which it was captured. A design is presented for an integrated geographic information system offering a number of distinct views onto geographic space, of varying degrees of abstraction, to support the needs of an expanded user base. An architecture for such a system is developed by an extension of the traditional three layer architecture used in database design. The movement of data from one level of abstraction to another is formalized by a series of dataset and model transformations operating between four different geographic data models. From this formalism, a functional taxonomy of GIS operations is developed.

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