Towards Integrating Heterogeneous Data: A Spatial DBMS Solution from a CRC-LCL Project in Australia

Over recent decades, more and more cities worldwide have created semantic 3D city models of their built environments based on standards across multiple domains. 3D city models, which are often employed for a large range of tasks, go far beyond pure visualization. Due to different spatial scale requi...

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Bibliographic Details
Main Authors: Wei Li, Sisi Zlatanova, Abdoulaye A. Diakite, Mitko Aleksandrov, Jinjin Yan
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:ISPRS International Journal of Geo-Information
Subjects:
pim
ifc
Online Access:https://www.mdpi.com/2220-9964/9/2/63
Description
Summary:Over recent decades, more and more cities worldwide have created semantic 3D city models of their built environments based on standards across multiple domains. 3D city models, which are often employed for a large range of tasks, go far beyond pure visualization. Due to different spatial scale requirements for planning and managing various built environments, integration of Geographic Information Systems (GIS) and Building Information Modeling (BIM) has emerged in recent years. Focus is now shifting to Precinct Information Modeling (PIM) which is in a more general sense to built-environment modeling. As scales change so do options to perform information modeling for different applications. How to implement data interoperability across these digital representations, therefore, becomes an emerging challenge. Moreover, with the growth of multi-source heterogeneous data consisting of semantic and varying 2D/3D spatial representations, data management becomes feasible for facilitating the development and deployment of PIM applications. How to use heterogeneous data in an integrating manner to further express PIM is an open and comprehensive topic. In this paper, we develop a semantic PIM based on multi-source heterogeneous data. Then, we tackle spatial data management problems in a Spatial Database Management System (SDBMS) solution for our defined unified model. Case studies on the University of New South Wales (UNSW) campus demonstrate the efficiency of our solution.
ISSN:2220-9964