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Managed Objects for Infrastructure Data

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Book cover 3D Geo-Information Sciences

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

Using data objects to describe features in the real world is a new idea and several approaches have already been shown to match scientific paradigms exceedingly well [1, 2, 3]. Depending on the required level of abstraction, it is possible to represent the world more or less closely to reality. In the realm of 3D Geoinformation research, this realism is often related to the way the spatial world is represented. By contrast, the 2D GIS community focuses on attribute data that describes additional states or characteristics of a feature. The main focus in 3D Geoinformation has always been on the representation of spatial objects, on relations like topology, ontology, and on storing and presenting them with more or less detail. The Centre for 3D GeoInformation (3DGI) at Aalborg University is currently participating in a project that explores objects that will not only contain geometry and associated attributive data but also will contain behavioural information. Our goal is to communicate the design and handling of these enhanced objects by means of the concept introduced in Java whereby objects are created in bytecode and subsequently executed within a Java virtual machine. This concept has already been implemented in the GRIFINOR (http://www.grifinor.net) platform [4]. This article will present the core ideas of relevance to this concept as it relates to current understanding of objects. Our work also offers suggestions on how to implemented such algorithms using real-life infrastructure data. Furthermore, we elaborate on the possibilities and challenges associated with moving from mostly static objects to dynamic objects in the area of 3D geoinformation.

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References

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© 2009 Springer-Verlag Berlin Heidelberg

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Kjems, E., Bodum, L., Kolar, J. (2009). Managed Objects for Infrastructure Data. In: Lee, J., Zlatanova, S. (eds) 3D Geo-Information Sciences. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87395-2_7

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