Formalization of families of categorical coverages

Frank, Andrew U.; Volta, Gary S.; McGranaghan, Matthew

doi:10.1080/136588197242365

Cited by 24 publications

(6 citation statements)

References 7 publications

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“…Both of the partitions involved satisfy all of the master conditions set forth above. The close relationship between the two partitions has been discussed for example by Beard (1988) and Frank at al. (1997).…”

Section: Categorical Coveragesmentioning

confidence: 56%

“…The fact that projection and location are here total, functional and mutually inverse is exploited extensively in the formalization and representation of categorical coverges (e.g. Frank at al 1997, Erwig and Schneider 1999, Bittner and Stell 1998. Fourthly, as mentioned above, spatial partitions recognize some of the mereotopological structure of their domains even though they fall short of being mereologically monotone in the sense of CS1.…”

Section: Categorical Coveragesmentioning

confidence: 99%

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A Taxonomy of Granular Partitions

Bittner

Smith

2001

Lecture Notes in Computer Science

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In this paper we propose a formal theory of partitions (ways of dividing up or sorting or mapping reality) and we show how the theory can be applied in the geospatial domain. We characterize partitions at two levels: as systems of cells (theory A), and in terms of their projective relation to reality (theory B). We lay down conditions of well-formedness for partitions and we define what it means for partitions to project truly onto reality. We continue by classifying well-formed partitions along three axes: (a) degree of correspondence between partition cells and objects in reality; (b) degree to which a partition represents the mereological structure of the domain it is projected onto; and (c) degree of completeness and exhaustiveness with which a partition represents reality. This classification is used to characterize three types of partitions that play an important role in spatial information science: cadastral partitions, categorical coverages, and the partitions involved in folk categorizations of the geospatial domain.

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Section: Categorical Coveragesmentioning

confidence: 56%

Section: Categorical Coveragesmentioning

confidence: 99%

A Taxonomy of Granular Partitions

Bittner

Smith

2001

Lecture Notes in Computer Science

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“…This is a fundamental problem for any object ontology: the division of the world into objects is not unique and depends on the observer and his intentions. A special case is given if a classification is finer than another [93] (Figure 2.23). There, the objects form a lattice [138].…”

Section: Geographic Objects Are Not Solid Bodiesmentioning

confidence: 98%

Chapter 2: Ontology for Spatio-temporal Databases

Frank

2003

Lecture Notes in Computer Science

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Ontology and the related term "semantics" have recently found increased attention in database discussions. Early discussions of ontology issues important for databases [126,78] were lost in a sea of papers on technical, mostly performance issues, despite the fact that textbooks as early as [134] discussed briefly the relationship between information system and real world. This is different today; interest in semantics has increased, and this will be more so in the future given the current interest in the Semantic Web [11,10] (see Chapter 9 of the book for related discussion).Information systems and their implementation as databases rest on ontological commitments. Decisions about the type system used, how identifiers are managed, and so on, are derived from a specific view of the world to which the database relates, in other words from a specific ontology. The ontologies of standard database models make very limited assumptions and therefore the data model is widely applicable. Spatio-temporal databases must make stronger commitments to capture the meaning of space and time. Such an ontology is necessarily more involved and the connection to the application area stronger. The designer of a database application has to reconcile the ontological concepts from the application area with the ontology built into the database. Optimally, a spatio-temporal database involves in its built-in ontology a minimal commitment on how space and time is structured and is thus most open for application specific refinements. Exploring the minimal set of ontological commitment is the goal of this chapter.The ontology built into a DBMS can be insufficient or it can be too restraining. It is insufficient if the ontological categories necessary for numerous applications are not available and must be reconstructed for each application anew; the resulting incompatibilities will be very costly to correct later [81]. It is too restraining if the ontology commits those who apply it to assumptions which do not hold for novel applications. Spatio-temporal databases are typically constructed to integrate the knowledge of many agents and face the problem of heterogeneous environments, a point already raised by Wiederhold et al. [190, Chapter 22]. Current databases do not allow us to model joint beliefs of groups of agents which do not correspond to similar beliefs of other groups of agents; for example, Reuter works with groups of scientists, who manage terabytes of reports of results from experiments in cellular biology, where the validity of the results and their interpretation are debated among the groups. Current ontological investigations related to databases and information systems have been

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“…Other common GIS zoom operations include content zooms where the classification scheme of a theme is adjusted leading to more or less differentiation among properties of an object (Volta 1992, Frank and Timpf 1994, Frank et al 1997). In addition, semantic zooming (Tanaka and Ichikawa 1988) allows users to control the selection of objects for display based on the relative importance of the object to the task at hand.…”

Section: Zoom Operations Based On Geometry or Properties Of Objectsmentioning

confidence: 99%

Temporal Zooming

Hornsby

2001

Transactions in GIS

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Spatio-temporal knowledge representation often requires changing from one level of detail or granularity to another so users can carry out a desired task. Meteorological occurrences, geological processes, or population movements, for example, can be examined at different granularities. This includes different spatial perspectives as well as temporal views where phenomena may be examined under real time conditions, or over hourly, daily, weekly, or longer periods. Moving back and forth among granularities is a necessary routine for many domain scientists. Changing to a more detailed view uncovers information that otherwise is unknown. Conversely, moving to a simpler view can improve our understanding of phenomena. Although people routinely abstract information from their environment at different granularities and perform mental shifts that increase or decrease detail, formalization of these alterations for use in information systems has proved difficult. Geographic information systems typically treat changes in granularity from the perspective of changes to the geometric properties of objects through graphic zooming. None of the current approaches to zooming offer support for performing this operation over time. This work focuses on the temporal aspects of changing granularity or temporal zooming. The approach is based on a model of change to identifiable objects. In this paper, temporal zooming involves expanding or collapsing the transitions among identity states of the same object as well as revealing or omitting other objects that are linked through transitions. A set of operations to support refining and coarsening the evolution of objects over time is presented. This work offers a new perspective on zooming important for spatio-temporal query languages and for users of large spatio-temporal databases who require the means to shift back and forth among simpler or summarized views of data and more detailed views.

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Formalization of families of categorical coverages

Cited by 24 publications

References 7 publications

A Taxonomy of Granular Partitions

A Taxonomy of Granular Partitions

Chapter 2: Ontology for Spatio-temporal Databases

Temporal Zooming

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