Download PDF by Juan Trujillo, Gillian Dobbie, Hannu Kangassalo, Sven: Advances in Conceptual Modeling - Applications and

By Juan Trujillo, Gillian Dobbie, Hannu Kangassalo, Sven Hartmann, Markus Kirchberg, Matti Rossi, Iris Reinhartz-Berger, Esteban Zimányi, Flavius Frasincar

ISBN-10: 364216384X

ISBN-13: 9783642163845

This booklet constitutes the refereed complaints of workshops, held on the twenty ninth overseas convention on Conceptual Modeling, ER 2010, in Vancouver, Canada, in November 2010. The 31 revised complete papers provided have been rigorously reviewed and chosen from eighty two submissions. The papers are equipped in sections at the workshops Semantic and Conceptual concerns in GIS (SeCoGIS); Conceptual Modeling of lifestyles Sciences purposes (CMLSA); Conceptual Modelling of prone (CMS); energetic Conceptual Modeling of studying (ACM-L); internet details platforms Modeling (WISM); area Engineering (DE@ER); and Foundations and Practices of UML (FP-UML).

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Extra info for Advances in Conceptual Modeling - Applications and Challenges: ER 2010 Workshops ACM-L, CMLSA, CMS, DE@ER, FP-UML, SeCoGIS, WISM, Vancouver, BC, ... Applications, incl. Internet Web, and HCI)

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We show a scenario where an expert–user responsible for flood management searches for flood risk zones in Canada. The expert formulates that the zones returned by the required service should have elevation of 4 meters or less to be considered as flood risk zones. The expert’s request is formulated as a GWS description, based on the vocabulary of its ontology, shown in OWL abstract syntax: Class(input complete restriction(is-A someValuesFrom (GML: surface))) Class(pre-condition complete restriction(part-of someValuesFrom(Canada))) G-Map Semantic Mapping Approach to Improve Semantic Interoperability 19 Class(function complete restriction(is-A someValuesFrom(FindFloodRiskZone)) restriction (Before someValuesFrom(Storm)) Class(output complete restriction(is-A someValuesFrom(GML: surface) restriction (Elevation someValuesFrom(<=4m))) Class(post-condition complete restriction(hasSpatialAccuracy (10meters))) The following dependency augments the GWS query description: Elevation (GML: surface, low) → risk(GML: surface, high).

We define the MBR of a geographic object o, M BR(o) = I1 (o)× I2 (o) where Ii (o) = [li , ui ](li , ui ∈ E 1 ) is the minimum interval describing the extent of o along the dimension i. In the same way, we define a rectangle query q = [l1q , uq1 ] × [l2q , uq2 ]. Finally, the range query to find all the objects o having at least one point in common with q is defined as RQ(q) = {o | q ∩ M BR(o) = ∅}. g. g. STR R-tree) variants [11] are the most popular SAMs used to solve range queries in GIS. In Gaede and Gunther [5] these structures are presented in the group of SAMs based on the technique of overlapping regions.

Objects intersecting each band are the candidates to be part of the query result. Finally, those objects in the intersection of the bands are the actual results of the query. Note that this intersection can be performed on-line because the candidates of the first dimension turn on their bits on a bitmap and the candidates of the second one report the MBR identifier only if their associated bits are turned on in the bitmap (an array of counters allows the generalization to d dimensions). In both transformed grids there is only one point in each row and in each column, therefore we can build two wavelet trees as described in [3].

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Advances in Conceptual Modeling - Applications and Challenges: ER 2010 Workshops ACM-L, CMLSA, CMS, DE@ER, FP-UML, SeCoGIS, WISM, Vancouver, BC, ... Applications, incl. Internet Web, and HCI) by Juan Trujillo, Gillian Dobbie, Hannu Kangassalo, Sven Hartmann, Markus Kirchberg, Matti Rossi, Iris Reinhartz-Berger, Esteban Zimányi, Flavius Frasincar


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