Joel da Silva

GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas

Data Warehouse (DW) is a dimensional database for providing decision support by means of on-line analytical processing (OLAP) techniques. Another technology also used to provide decision support is Geographical Information System (GIS). Much research aims at integrating these technologies, but there are still some open questions, particularly regarding the design of a geographical dimensional data schema. This paper discusses some related work and proposes GeoDWFrame that is a framework based on the star schema and has been specified as guidance for designing geographical dimensional schemas. Some experimental results are also given.

Modelling and querying geographical data warehouses

A number of proposals for integrating geographical (Geographical Information Systems-GIS) and multidimensional (data warehouse-DW and online analytical processing-OLAP) processing are found in the database literature. However, most of the current approaches do not take into account the use of a GDW (geographical data warehouse) metamodel or query language to make available the simultaneous specification of multidimensional and spatial operators. To address this, this paper discusses the UML class diagram of a GDW metamodel and proposes its formal specifications. We then present a formal metamodel for a geographical data cube and propose the Geographical Multidimensional Query Language (GeoMDQL) as well. GeoMDQL is based on well-known standards such as the MultiDimensional eXpressions (MDX) language and OGC simple features specification for SQL and has been specifically defined for spatial OLAP environments based on a GDW. We also present the GeoMDQL syntax and a discussion regarding the taxonomy of GeoMDQL query types. Additionally, aspects related to the GeoMDQL architecture implementation are described, along with a case study involving the Brazilian public healthcare system in order to illustrate the proposed query language.

An open source and web based framework for geographic and multidimensional processing

The development of Business Intelligence (BI) systems has been the destination of high investments made by several enterprises. The motivation is because an efficient decision support environment brings them several business world advantages, mainly if it provides integrated functionalities for the geographical and/or multidimensional processing. The intended goal is to provide users with a system capable of processing both geographic and multidimensional data in a seamless way, by abstracting the complexity of separately querying and analyzing these data in a decision making process. However, this integration may not be fully achieved yet or may be built using proprietary technologies. This paper presents an open source and web based framework for geographic and multidimensional decision support. Our approach uses a geographical data warehouse, a metadata source, a query language and a geographical and multidimensional engine for processing queries sent by a web based client application.

A set of aggregation functions for spatial measures

A number of studies have been developed in recent years aimed at integrating pertinent concepts and technologies for analytical multidimensional (OLAP) and geographic (GIS) processing environments. This type of integrated environment has been identified as SOLAP (Spatial OLAP). However, due to the fact that these two technologies were conceived with different purposes in mind, the interaction of the two environments is not an easy task and even with so much research being developed, there remain unresolved issues that merit exploration. One such issue refers to aggregation functions for measures. These functions are currently used in the definition of multidimensional and geographic data cubes. The aim of this paper is to present a set of aggregation functions for geographic measures. We also show these functions in practice, by taking into account their use with a SOLAP architecture prototype. This SOLAP prototype is based on a model for Geographic Data Warehouse (GDW), a data cube model and a geographic multidimensional query language.

A Metamodel for the Specification of Geographical Data

The decision-making processes can be supported by many tools such as Data Warehouse (DW), On-Line Analytical Processing (OLAP) and Geographical Information System (GIS). Much research found in literature is aimed at integrating these technologies, although most of these approaches do not provide formal definitions for a Geographical Data Warehouse (GDW) nor there is a consensus regarding the design of spatial dimensional schemas for GDW. To address this, GeoDWFrame was proposed as a set of guidelines to design spatial dimensional schemas. However, there is not a metamodel that implements its specifications, nor there is a metamodel that integrates GDW concepts with some standards. Then, in this paper we propose GeoDWM, which is a formally specified metamodel, that extends GeoDWFrame with spatial measures. We have instantiated our formal metamodel based on CWM and OGC standards to assist the conceptual modelling needs found in the development of GDW applications. Finally, some issues concerning the development of a CASE tool that is based on the GeoDWM metamodel and that provides a means of validating the application conceptual data model are given together with a discussion on GDW conceptual design aspects and some descriptions for future work.

Providing geographic-multidimensional decision support over the web

For the last years, many researchers have been addressing their efforts to try to solve the problem regarding the integration between analytic and geographic processing systems. The main goal is to provide users with a system capable of processing both geographic and multidimensional data by abstracting the complexity of separately querying and analyzing these data in a decision making process. However, this integration may not be fully achieved yet or may be built by using proprietary technologies. This paper presents a service integration model for supporting analytic and/or geographic requests over the Web. This model has been implemented by a Web Service, named GMLA WS, which is strongly based on standardized technologies such as Web Services, Java and XML. The GMLA WS query results are displayed using a Web browser as maps and/or tables for helping users in their decision making.