Conceptual model for spatial data cubes: A UML profile and its automatic implementation

The interest in mobility data analysis has grown dramatically with the wide availability of devices that track the position of moving objects. Mobility analysis can be applied, for example, to analyze traffic flows. To support mobility analysis, trajectory data warehousing techniques can be used. Trajectory data warehouses typically include, as measures, segments of trajectories, linked to spatial and non-spatial contextual dimensions. This paper goes beyond this concept, by including, as measures, the trajectories of moving objects at any point in time. In this way, online analytical processing (OLAP) queries, typically including aggregation, can be combined with moving object queries, to express queries like "List the total number of trucks running at less than 2 km from each other more than 50% of its route in the province of Antwerp" in a concise and elegant way. Existing proposals for trajectory data warehouses do not support queries like this, since they are based on either the segmentation of the trajectories, or a pre-aggregation of measures. The solution presented here is implemented using MobilityDB, a moving object database that extends the PostgresSQL database with temporal data types, allowing seamless integration with relational spatial and non-spatial data. This integration leads to the concept of mobility data warehouses. This paper discusses modeling and querying mobility data warehouses, providing a comprehensive collection of queries implemented using PostgresSQL and PostGIS as database backend, extended with the libraries provided by MobilityDB.

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“…The notion of spatial OLAP (SOLAP) was introduced in [14], and it is reviewed in [15]. Other relevant work on SOLAP can be found in [16][17][18].…”

Section: Related Workmentioning

confidence: 99%

Mobility Data Warehouses

Vaisman

Zimányi

2019

IJGI

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“…The end result of WMS is to produce a map that is represented by an image stored as a png, gif or jpg format [47]. These analyzing techniques and the increasing availability of geo-referenced data facilitates an effective way to manage spatial information by providing large-scale storage, multidimensional data management, and OLAP querying capabilities, together in one system [48][49][50]. WMS is a standard widely used for accessing and retrieving maps from remote servers made available over the Internet.…”

Section: Graphic User Interface Designmentioning

confidence: 99%

Development of Framework for Aggregation and Visualization of Three-Dimensional (3D) Spatial Data

Miu

Zhang

Dewan

et al. 2018

BDCC

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Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in utilizing the available geospatial information. These disparate data sources must be aggregated before further extraction and analysis may be performed. The objective of this paper is to develop a framework called PlaniSphere, which aggregates various geospatial datasets, synthesizes raw data, and allows for third party customizations of the software. PlaniSphere uses NASA World Wind to access remote data and map servers using Web Map Service (WMS) as the underlying protocol that supports service-oriented architecture (SOA). The results show that PlaniSphere can aggregate and parses files that reside in local storage and conforms to the following formats: GeoTIFF, ESRI shape files, and KML. Spatial data retrieved using WMS from the Internet can create geospatial data sets (map data) from multiple sources, regardless of who the data providers are. The plug-in function of this framework can be expanded for wider uses, such as aggregating and fusing geospatial data from different data sources, by providing customizations to serve future uses, which the capacity of the commercial ESRI ArcGIS software is limited to add libraries and tools due to its closed-source architectures and proprietary data structures. Analysis and increasing availability of geo-referenced data may provide an effective way to manage spatial information by using large-scale storage, multidimensional data management, and Online Analytical Processing (OLAP) capabilities in one system.

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“…The forest SDW metamodel we propose is adapted from [35]. It allows representing the main static concepts of the SDW.…”

Section: Case Studymentioning

confidence: 99%

Users Integrity Constraints in SOLAP Systems. Application in Agroforestry

Charef¹,

Djamila²

2018

IJIMAI

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SpatialData Warehouse and Spatial On-Line Analytical Processing are decision support technologies which offer the spatial and multidimensional analysis of data stored in multidimensional structure. They are aimed also at supporting geographic knowledge discovery to help decision-maker in his job related to make the appropriate decision . However, if we don't consider data quality in the spatial hypercubes and how it is explored, it may provide unreliable results. In this paper, we propose a system for the implementation of user integrity constraints in SOLAP namely "UIC-SOLAP". It corresponds to a methodology for guaranteeing results quality in an analytical process effectuated by different users exploiting several facts tables within the same hypercube. We integrate users Integrity Constraints (IC) by specifying visualization ICs according to their preferences and we define inter-facts ICs in this case. In order to validate our proposition, we propose the multidimensional modeling by UML profile to support constellation schema of a hypercube with several fact tables related to subjects of analysis in forestry management. Then, we propose implementation of some ICs related to users of such a system.

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Conceptual model for spatial data cubes: A UML profile and its automatic implementation

Cited by 47 publications

References 8 publications

Mobility Data Warehouses

Mobility Data Warehouses

Development of Framework for Aggregation and Visualization of Three-Dimensional (3D) Spatial Data

Users Integrity Constraints in SOLAP Systems. Application in Agroforestry

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