Academic literature on the topic 'Geographic data warehouses'
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Journal articles on the topic "Geographic data warehouses"
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Kasprzyk, Jean-Paul, and Guénaël Devillet. "A Data Cube Metamodel for Geographic Analysis Involving Heterogeneous Dimensions." ISPRS International Journal of Geo-Information 10, no. 2 (February 19, 2021): 87. http://dx.doi.org/10.3390/ijgi10020087.
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Due to their multiple sources and structures, big spatial data require adapted tools to be efficiently collected, summarized and analyzed. For this purpose, data are archived in data warehouses and explored by spatial online analytical processing (SOLAP) through dynamic maps, charts and tables. Data are thus converted in data cubes characterized by a multidimensional structure on which exploration is based. However, multiple sources often lead to several data cubes defined by heterogeneous dimensions. In particular, dimensions definition can change depending on analyzed scale, territory and time. In order to consider these three issues specific to geographic analysis, this research proposes an original data cube metamodel defined in unified modeling language (UML). Based on concepts like common dimension levels and metadimensions, the metamodel can instantiate constellations of heterogeneous data cubes allowing SOLAP to perform multiscale, multi-territory and time analysis. Afterwards, the metamodel is implemented in a relational data warehouse and validated by an operational tool designed for a social economy case study. This tool, called “Racines”, gathers and compares multidimensional data about social economy business in Belgium and France through interactive cross-border maps, charts and reports. Thanks to the metamodel, users remain independent from IT specialists regarding data exploration and integration.
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Bimonte, Sandro. "A Web-Based Tool for Spatio-Multidimensional Analysis of Geographic and Complex Data." International Journal of Agricultural and Environmental Information Systems 1, no. 2 (July 2010): 42–67. http://dx.doi.org/10.4018/jaeis.2010070103.
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Spatial OLAP (SOLAP) integrates spatial data into OLAP systems, and SOLAP models define spatial dimensions while measuring spatio-multidimensional operators. In this paper, the author presents the concepts of geographic and complex measures that allow integrating geographic and complex information as subjects of analysis in spatial data warehouses. The concept of geographic measure extends the concept of spatial measure to the semantic component of geographic information. The concept of complex measure allows introducing complex data as subjects of multidimensional analysis. To reduce the gap in flexibility between spatial and multidimensional analysis, this paper proposes a symmetrical representation of measures and dimensions. Additionally, the author presents a Web-based SOLAP prototype, GeWOlap, that enriches existing SOLAP tools by effectively and easily supporting symmetrical geographic/complex measures and dimensions for modeling and visualization. To validate this approach, the simulated environmental data concerning the pollution of the Venice lagoon is used.
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Azaiez, Noura, and Jalel Akaichi. "What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?" International Journal of Information Systems in the Service Sector 8, no. 1 (January 2016): 1–12. http://dx.doi.org/10.4018/ijisss.2016010101.
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Classic data seems unable to keep pace with the technology era. In fact, the incredible progress related to geographic information systems, pervasive computing, and positioning technologies have motivated classic data to evolve towards new data kind called mobility data. For decisional purposes, these later have to be analysed; therefore, their integration into a decision support system becomes a must. However, the data warehouse used to store classical data seems to be inadequate for mobility data storage and analysis. This gave the birth of a new central repository type called trajectory data warehouse which is able to support mobility data extraction, transformation, loading, and analysis and/or mining. As classic data warehouses, the trajectory one often changes its content as well as its structure for various reasons such as the organizational business processes progressing over time, the evolving needs of decision makers that lead to DW structure enrichment with additional analyses axes, or even the incompleteness of needs initially captured during the design phase of the DW . This work proposes a survey that gathers the research works that deal with the issue of trajectory data warehouse modelling and evolution; then the authors present comparative study of the proposed solutions.
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Bimonte, Sandro, Omar Boucelma, Olivier Machabert, and Sana Sellami. "A Generic Spatial OLAP Model for Evaluating Natural Hazards in a Volunteered Geographic Information Context." International Journal of Agricultural and Environmental Information Systems 5, no. 4 (October 2014): 40–55. http://dx.doi.org/10.4018/ijaeis.2014100102.
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Spatial data warehouses (SDW) and spatial OLAP (SOLAP) systems are well-known business intelligence technologies that aim to support a multidimensional and online analysis for a large volume of geo-referenced datasets. SOLAP systems are already used in the context of natural hazards for analyzing sensor data and experts' measurements. Recently, new data gathering tools coined as volunteered geographic information systems (VGI) have been adopted especially by non-expert users. Hence, (spatial) application development is facing a new challenge, which is the integration of expert-oriented data with citizen-provided data. In this paper, we propose a new generic spatio-multidimensional model based on the question/answer risk evaluation model that allows the integration of VGI data with classical SDW and SOLAP systems for the online analysis of natural hazards monitored by volunteers.
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Ahanotu, Dike N., Michael J. Fischer, and Hugh W. Louch. "Developing a Commodity Flow Database from Transearch Data." Transportation Research Record: Journal of the Transportation Research Board 1855, no. 1 (January 2003): 14–21. http://dx.doi.org/10.3141/1855-02.
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A procedure is described for analyzing Reebie Transearch data to create a commodity flow database that is useful for transportation planning purposes. Several elements of the procedure were recently applied as part of the development of a commodity flow database for the Portland metropolitan area. The procedure begins with an overview of the robustness of various Transearch data elements. For less robust data elements, specific processes are described to improve on the Transearch data. This process generally includes acquiring additional data from federal and state agencies, acquiring additional information from primary industry sources, and applying these data to the geographic area of concern for the commodity flow database. A methodology for estimating the commodity distribution for goods movement that originates in warehouses and distribution centers is also described. Supplemental freight data sources are identified, and elements of these data sources that can be used to verify and refine the Transearch data are highlighted. In the case of discrepancies between the Transearch data and other freight data sources, a process is described to determine potential sources of the discrepancy and further improve on the Transearch data toward the creation of a full commodity flow database.
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da Silva, Joel, Anjolina G. de Oliveira, Robson N. Fidalgo, Ana Carolina Salgado, and Valéria C. Times. "Modelling and querying geographical data warehouses." Information Systems 35, no. 5 (July 2010): 592–614. http://dx.doi.org/10.1016/j.is.2009.10.005.
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Greenhalgh, Paul, Helen M. King, Kevin Muldoon-Smith, and Josephine Ellis. "The New Distribution: Spatio-Temporal Analysis of Large Distribution Warehouse Premises in England and Wales." Urban Planning 6, no. 3 (September 23, 2021): 399–414. http://dx.doi.org/10.17645/up.v6i3.4222.
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This research addresses the deficit of empirical investigation of changes in industrial and warehouse property markets in the UK. It uses business rates (rating list) data for England and Wales to reveal changes in the quantum and distribution of premises over the last decade. Spatio-temporal analysis using geographical information systems identifies where new industrial and warehouse premises have been developed and examines spatial changes in the distribution of premises between the two sectors. The research focuses on the development of new large distribution warehouses (LDWs) to investigate whether there is a new pattern of warehouse premises located in close proximity to junctions on the national highway network. Findings confirm the emergence of a dynamic distribution warehouse property market where “super sheds” have been developed in areas with high levels of multi-modal connectivity. The comprehensive spatio-temporal analysis of all industrial and warehouse premises in England and Wales reconfigures the previously recognised Midlands “Golden Triangle” of distribution warehouses to a “Golden Pointer” and reveals the emergence of a rival “Northern Dumbbell” of distribution warehouse premises in the North of England. Further analysis using isochrones confirms that 85% of the population of Great Britain is situated within four hours average heavy goods vehicle drive time of these two concentrations of super sheds and over 60% of all LDWs floorspace is within 30 minutes’ drive of intermodal rail freight interchanges.
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Yardley, A. J. "THE NEXT GENERATION SPATIAL DATA WAREHOUSE." APPEA Journal 42, no. 1 (2002): 633. http://dx.doi.org/10.1071/aj01039.
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Woodside Energy, based in Perth, Western Australia, has commenced the implementation of its next generation spatial data warehousing and visualisation system. The warehouse facilitates access to data in various corporate geoscience data sets, as well as up-to-date cultural and environmental data. It expands the capabilities of the existing geoscience database by providing a facility to handle spatial data at the database level rather than in files and maps. Spatial data can now be kept in the database, in its correct spatial location, and with a known provenance.Woodside’s worldwide exploration, development and production activities require the use of a wide variety of geographic data such as seismic, bathymetry, wells, permits, coastlines, political boundaries, navigation charts, remote sensing and geological interpretations.Geo-spatial data comes to Woodside in a variety of formats, datums and conditions. The Geomatics Department, through the Geoscience Database and Spatial Information Management teams, loads, maintains and manages all data considered to be corporate. It is quality controlled and placed into the warehouse, where it is readily accessible to technical and administrative staff.Location is an essential element in most Woodside decisions. Because of the new spatial capabilities, a number of geographic information processes are now possible. Additionally information can also be made available through the internet if required.Reliable geographic information will become more widely available in the organisation, and be more easily merged with traditional data types, enhancing the decision-making process.
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Jordhus-Lier, David, Anders Underthun, and Kristina Zampoukos. "Changing workplace geographies: Restructuring warehouse employment in the Oslo region." Environment and Planning A: Economy and Space 51, no. 1 (July 12, 2018): 69–90. http://dx.doi.org/10.1177/0308518x18787821.
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The article examines changing employment relations in Norwegian warehouses, and conceptualises the increasing use of temporary agency workers as a redrawing of workplace geographies. The empirical basis for the analysis is four qualitative warehouse workplace studies, including focus group and interview data. The theoretical framework of the article combines an adapted version of the territory-place-scale-network (TPSN) framework developed by Bob Jessop, Neil Brenner and Martin Jones with the concepts of labour control and labour agency. The analysis shows how a networked recruitment system based on Swedish labour migrants, mediated via temporary work agencies, encourage workers to work their way through levels of employment insecurity in order to secure permanent employment. The article argues that the blurring and redrawing of legal boundaries through labour hire can be understood as a territorial strategy of control that affects the workplace as a scale of justice for trade unions. Moreover, the analysis shows how managerial control is conditioned by workers’ individual, habitual and collective agency.
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Agapito, Giuseppe, Chiara Zucco, and Mario Cannataro. "COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data." International Journal of Environmental Research and Public Health 17, no. 15 (August 3, 2020): 5596. http://dx.doi.org/10.3390/ijerph17155596.
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The management of the COVID-19 pandemic presents several unprecedented challenges in different fields, from medicine to biology, from public health to social science, that may benefit from computing methods able to integrate the increasing available COVID-19 and related data (e.g., pollution, demographics, climate, etc.). With the aim to face the COVID-19 data collection, harmonization and integration problems, we present the design and development of COVID-WAREHOUSE, a data warehouse that models, integrates and stores the COVID-19 data made available daily by the Italian Protezione Civile Department and several pollution and climate data made available by the Italian Regions. After an automatic ETL (Extraction, Transformation and Loading) step, COVID-19 cases, pollution measures and climate data, are integrated and organized using the Dimensional Fact Model, using two main dimensions: time and geographical location. COVID-WAREHOUSE supports OLAP (On-Line Analytical Processing) analysis, provides a heatmap visualizer, and allows easy extraction of selected data for further analysis. The proposed tool can be used in the context of Public Health to underline how the pandemic is spreading, with respect to time and geographical location, and to correlate the pandemic to pollution and climate data in a specific region. Moreover, public decision-makers could use the tool to discover combinations of pollution and climate conditions correlated to an increase of the pandemic, and thus, they could act in a consequent manner. Case studies based on data cubes built on data from Lombardia and Puglia regions are discussed. Our preliminary findings indicate that COVID-19 pandemic is significantly spread in regions characterized by high concentration of particulate in the air and the absence of rain and wind, as even stated in other works available in literature.
Dissertations / Theses on the topic "Geographic data warehouses"
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Yu, Chi-kit, and 余智傑. "A study of GIS data warehouses in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29967636.
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Brito, Jaqueline Joice. "Processamento de consultas SOLAP drill-across e com junção espacial em data warehouses geográficos." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18022013-090739/.
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Um data warehouse geográco (DWG) é um banco de dados multidimensional, orientado a assunto, integrado, histórico, não-volátil e geralmente organizado em níveis de agregação. Além disso, também armazena dados espaciais em uma ou mais dimensões ou em pelo menos uma medida numérica. Visando oferecer suporte à tomada de decisão, é possível realizar em DWGs consultas SOLAP (spatial online analytical processing ), isto é, consultas analíticas multidimensionais (e.g., drill-down, roll-up, drill-across ) com predicados espaciais (e.g., intersecta, contém, está contido) denidos para range queries e junções espaciais. Um desafio no processamento dessas consultas é recuperar, de forma eficiente, dados espaciais e convencionais em DWGs muito volumosos. Na literatura, existem poucos índices voltados à indexação de DWGs, e ainda assim nenhum desses índices dedica-se a indexar consultas SOLAP drill-across e com junção espacial. Esta dissertação visa suprir essa limitação, por meio da proposta de estratégias para o processamento dessas consultas complexas. Para o processamento de consultas SOLAP drill-across foram propostas duas estratégias, Divide e Única, além da especicação de um conjunto de diretrizes que deve ser seguido para o projeto de um esquema de DWG que possibilite a execução dessas consultas e da especicação de classes de consultas. Para o processamento de consultas SOLAP com junção espacial foi proposta a estratégia SJB, além da identicação de quais características o esquema de DWG deve possuir para possibilitar a execução dessas consultas e da especicação do formato dessas consultas. A validação das estratégias propostas foi realizada por meio de testes de desempenho considerando diferentes congurações, sendo que os resultados obtidos foram contrastados com a execução de consultas do tipo junção estrela e o uso de visões materializadas. Os resultados mostraram que as estratégias propostas são muito eficientes. No processamento de consultas SOLAP drill-across, as estratégias Divide e Única mostraram uma redução no tempo de 82,7% a 98,6% com relação à junção estrela e ao uso de visões materializadas. No processamento de consultas SOLAP com junção espacial, a estratégia SJB garantiu uma melhora de desempenho na grande maioria das consultas executadas. Para essas consultas, o ganho de desempenho variou de 0,3% até 99,2%A geographic data warehouse (GDW) is a special kind of multidimensional database. It is subject-oriented, integrated, historical, non-volatile and usually organized in levels of aggregation. Furthermore, a GDW also stores spatial data in one or more dimensions or at least in one numerical measure. Aiming at decision support, GDWs allow SOLAP (spatial online analytical processing) queries, i.e., multidimensional analytical queries (e.g., drill-down, roll-up, drill-across) extended with spatial predicates (e.g., intersects, contains, is contained) dened for range and spatial join queries. A challenging issue related to the processing of these complex queries is how to recover spatial and conventional data stored in huge GDWs eciently. In the literature, there are few access methods dedicated to index GDWs, and none of these methods focus on drill-across and spatial join SOLAP queries. In this master\'s thesis, we propose novel strategies for processing these complex queries. We introduce two strategies for processing SOLAP drill-across queries (namely, Divide and Unique), dene a set of guidelines for the design of a GDW schema that enables the execution of these queries, and determine a set of classes of these queries to be issued over a GDW schema that follows the proposed guidelines. As for the processing of spatial join SOLAP queries, we propose the SJB strategy, and also identify the characteristics of a DWG schema that enables the execution of these queries as well as dene the format of these queries. We validated the proposed strategies through performance tests that compared them with the star join computation and the use of materialized views. The obtained results showed that our strategies are very ecient. Regarding the SOLAP drill-across queries, the Divide and Unique strategies showed a time reduction that ranged from 82,7% to 98,6% with respect to star join computation and the use of materialized views. Regarding the SOLAP spatial join queries, the SJB strategy guaranteed best results for most of the analyzed queries. For these queries, the performance gain of the SJB strategy ranged from 0,3% to 99,2% over the star join computation and the use of materialized view
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Carniel, Anderson Chaves. "Incorporando dados espaciais vagos em data warehouses geográficos: a proposta do tipo abstrato de dados vaguegeometry." Universidade Federal de São Carlos, 2014. https://repositorio.ufscar.br/handle/ufscar/582.
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Previous issue date: 2014-10-09Universidade Federal de Minas Gerais
A data warehouse is a solution for organizing and storing multidimensional data related to decision-making processes in companies, generating a historical, highly voluminous, subject-oriented and nonvolatile database. A geographic data warehouse (GDW) additio¬nally to the conventional data storage (i.e. numeric and alphanumeric data), stores spatial data as attributes in dimension tables or as measures in fact tables, storing data represented by geometries. Points, lines and polygons are examples of spatial data types. While spatial data currently stored in GDWs are crisp, i.e., they have exact location in the space, strict interiors and well-defined boundaries, geographic applications have required the storage of vague spatial data, which have inaccurate location, inexact interiors or uncertain bounda¬ries. This Master s research aims at incorporating vague spatial data to GDWs. More speci¬fically, we propose and implement a new abstract data type (ADT) called VagueGeometry to represent vague spatial data in the Spatial Database Management System (SDBMS) Post- greSQL/PostGIS. The proposal of the ADT VagueGeometry encompasses the issue of phy¬sical storage for vague spatial data, which are complex and can have several disjoint parts. It also focuses on definitions of operations to handle vague spatial objects, such as vague topological predicates and its operators. Experimental evaluations were conducted in order to assess the performance of the ADT VagueGeometry in comparison to available solutions, such as implementation of vague topological predicates utilizing existing operations of the PostGIS. The proposed ADT VagueGeometry shown reductions in query processing with vague topological predicates from 81.63% to 90.34% in spatial databases and reductions from 92.46% a 95.20% in GDW environments. This Master s project, therefore, advances in the state of art in GDWs to study this gap in the literature. Additionally, fuzzy models to represent vague spatial data was also studied, and as a result, a preliminary proposal of a ADT, called as FuzzyGeometry, was also developed.
Um data warehouse é uma solução para a organização e o armazenamento de dados mul-tidimensionais relacionados a tomada de decisão estratégica em empresas, constituindo um banco de dados histórico, volumoso, orientado ao assunto e não volátil. Um data warehouse geográfico (DWG) adicionalmente ao armazenamento de dados convencionais (tais como dados numéricos e alfanuméricos), armazena dados espaciais como atributos em tabelas de dimensão ou como medidas em tabelas de fatos, ou seja, armazena dados representados por meio de geometrias. Pontos, linhas e polígonos são exemplos de dados espaciais armazena¬dos. Enquanto estes dados armazenados atualmente em DWGs sao crisp, ou seja, possuem localização, interiores e fronteiras bem definidas, aplicações geográficas tem demandado o armazenamento de dados espaciais vagos, os quais possuem localização, interiores ou fronteiras incertas. Esta pesquisa de mestrado visa incorporar dados espaciais vagos em DWGs. Mais especificamente, foi proposto e implementado um novo tipo abstrato de dados (TAD), denominado VagueGeometry, para representar dados espaciais vagos no Sistema Gerenciador de Banco de Dados (SGBD) PostgreSQL com a extensão espacial PostGIS. A proposta do TAD VagueGeometry engloba a proposta de uma forma de armazenamento interna para os dados espaciais vagos, os quais são complexos e podem possuir diversas partes disjuntas. Isso também inclui a definição de operações para manipular objetos espa¬ciais vagos, tais como os relacionamentos topológicos vagos e seus operadores. Avaliações experimentais foram conduzidas para medir o desempenho do TAD VagueGeometry frente a soluções existentes, tal como a implementação de predicados topológicos vagos reuti¬lizando operações existentes do PostGIS. A proposta do TAD VagueGeometry apresentou reduções no tempo de processamento de predicados topológicos vagos de 81,63% a 90,34% em bancos de dados espaciais e reduções de 92,46% a 95,20% em ambientes de DWG. Este trabalho, portanto, avança no estado da arte em DWGs de forma a preencher essa lacuna existente na literatura. Adicionalmente, modelos fuzzy para representação dos dados espa¬ciais vagos também foram estudados e uma proposta preliminar de um TAD, denominado FuzzyGeometry, também foi desenvolvida.
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Siqueira, Thiago Luís Lopes. "SB-Index : um índice espacial baseado em bitmap para data warehouse geográfico." Universidade Federal de São Carlos, 2009. https://repositorio.ufscar.br/handle/ufscar/418.
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Previous issue date: 2009-08-26Universidade Federal de Minas Gerais
Geographic Data Warehouses (GDW) became one of the main technologies used in decision-making processes and spatial analysis since they provide the integration of Data Warehouses, On-Line Analytical Processing and Geographic Information Systems. As a result, a GDW enables spatial analyses together with agile and flexible multidimensional analytical queries over huge volumes of data. On the other hand, there is a challenge in a GDW concerning the query performance, which consists of retrieving data related to ad-hoc spatial query windows and avoiding the high cost of star-joins. Clearly, mechanisms to provide efficient query processing, as index structures, are essential. In this master s thesis, a novel index for GDW is introduced, namely the SB-index, which is based on the Bitmap Join Index and the Minimum Bounding Rectangle. The SB-index inherits the Bitmap Index legacy techniques and introduces them in GDW, as well as it enables support for predefined spatial attribute hierarchies. The SB-index validation was performed through experimental performance tests. Comparisons among the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicated that the SB-index significantly improves the elapsed time in query processing from 76% up to 96% with regard to queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. In addition, the impact of the increase in data volume on the performance was analyzed. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Moreover, in this master s thesis there is an experimental investigation on how does the spatial data redundancy affect query response time and storage requirements in a GDW? . Redundant and non-redundant GDW schemas were compared, concluding that redundancy is related to high performance losses. Then, aiming at improving query performance, the SB-index performance was evaluated on the redundant GDW schema. The results pointed out that SB-index significantly improves the elapsed time in query processing from 25% up to 99%. Finally, a specific enhancement of the SB-index was developed in order to deal with spatial data redundancy. With this enhancement, the minimum performance gain observed became 80%.
O Data Warehouse Geográfico (DWG) tornou-se uma das principais tecnologias de suporte à decisão, pois promove a integração de data warehouses, On-Line Analytical Processing e Sistemas de Informações Geográficas. Por isso, um DWG viabiliza a análise espacial aliada à execução de consultas analíticas multidimensionais envolvendo enormes volumes de dados. Por outro lado, existe um desafio relativo ao desempenho no processamento de consultas, que envolvem janelas de consulta espaciais ad-hoc e várias junções entre tabelas. Claramente, mecanismos para aumentar o desempenho do processamento de consultas, como as estruturas de indexação, são essenciais. Nesta dissertação, propõe-se um novo índice para DWG chamado SB-index, baseado no Índice Bitmap de Junção e no Retângulo Envolvente Mínimo. O SB-index herda todo o legado de técnicas do Índice Bitmap e o introduz no DWG. Além disso, ele provê suporte a hierarquias de atributos espaciais predefinidas. Este índice foi validado por meio de testes experimentais de desempenho. Comparações entre o SB-index, a junção estrela auxiliada pela R-tree e a junção-estrela auxiliada por GiST indicaram que o SB-index diminui significativamente o tempo de resposta do processamento de consultas roll-up e drill-down relacionadas aos predicados espaciais intersecta , está contido e contém , promovendo ganhos de 76% a 96%. Mostrou-se ainda que a variação do volume de dados não prejudica o desempenho do SB-index. Esta dissertação também investiga a seguinte questão: como a redundância de dados espaciais afeta um DWG? . Foram comparados os esquemas de DWG redundante e não-redundante. Observou-se que a redundância de dados espaciais acarreta prejuízos ao tempo de resposta das consultas e aos requisitos de armazenamento do DWG. Então, visando melhorar o desempenho do processamento de consultas, introduziu-se o SB-index no esquema de DWG redundante. Os ganhos de desempenho obtidos a partir desta ação variaram de 25% a 99%. Por fim, foi proposta uma melhoria sobre o SB-index a fim de lidar especificamente com a questão da redundância de dados espaciais. A partir desta melhoria, o ganho mínimo de desempenho tornou-se 80%.
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Koylu, Caglar. "A Case Study In Weather Pattern Searching Using A Spatial Data Warehouse Model." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609573/index.pdf.
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Data warehousing and Online Analytical Processing (OLAP) technology has been
used to access, visualize and analyze multidimensional, aggregated, and summarized
data. Large part of data contains spatial components. Thus, these spatial components
convey valuable information and must be included in exploration and analysis phases
of a spatial decision support system (SDSS). On the other hand, Geographic
Information Systems (GISs) provide a wide range of tools to analyze spatial
phenomena and therefore must be included in the analysis phases of a decision
support system (DSS). In this regard, this study aims to search for answers to the
problem how to design a spatially enabled data warehouse architecture in order to
support spatio-temporal data analysis and exploration of multidimensional data.
Consequently, in this study, the concepts of OLAP and GISs are synthesized in an
integrated fashion to maximize the benefits generated from the strengths of both
systems by building a spatial data warehouse model. In this context, a
multidimensional spatio-temporal data model is proposed as a result of this synthesis.
This model addresses the integration problem of spatial, non-spatial and temporal
data and facilitates spatial data exploration and analysis. The model is evaluated by
implementing a case study in weather pattern searching.
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Bejaoui, Lofti. "Qualitative topological relationships for objects with possibly vague shapes: implications on the specification of topological integrity constraints in transactional spatial databases and in spatial data warehouses." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2009. http://tel.archives-ouvertes.fr/tel-00725614.
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Dans les bases de données spatiales actuellement mises en oeuvre, les phénomènes naturels sont généralement représentés par des géométries ayant des frontières bien délimitées. Une telle description de la réalité ignore le vague qui caractérise la forme de certains objets spatiaux (zones d'inondation, lacs, peuplements forestiers, etc.). La qualité des données enregistrées est donc dégradée du fait de ce décalage entre la réalitée et sa description. Cette thèse s'attaque à ce problème en proposant une nouvelle approche pour représenter des objets spatiaux ayant des formes vagues et caractériser leurs relations topologiques. Le modèle proposé, appelé QMM model (acronyme de Qualitative Min-Max model), utilise les notions d'extensions minimale et maximale pour représenter la partie incertaine d'un objet. Un ensemble d'adverbes permet d'exprimer la forme vague d'un objet (ex : a region with a partially broad boundary), ainsi que l'incertitude des relations topologiques entre deux objets (ex : weakly Contains, fairly Contains, etc.). Cette approche est moins fine que d'autres approches concurrentes (modélisation par sous-ensembles flous ou modélisation probabiliste). Mais elle nécessite un processus d'acquisition complexe des données. De plus elle est relativement simple à mettre en oeuvre avec les systèmes existants de gestion de bases de données. Cette approche est ensuite utilisée pour contrôler la qualité des données dans les bases de données spatiales et les entrepôts de données spatiales en spécifiant les contraintes d'intégrité basé sur les concepts du modèle QMM. Une extension du langage de contraintes OCL (Object Constraint Language) a été étudiée pour spécifier des contraintes topologiques impliquant des objets ayant des formes vagues. Un logiciel existant (outil OCLtoSQL développé à l'Université de Dresden) a été étendu pour permettre la génération automatique du code SQL d'une contrainte lorsque la base de données est gérée par un système relationnel. Une expérimentation de cet outil a été réalisée avec une base de données utilisée pour la gestion des épandages agricoles. Pour cette application, l'approche et l'outil sont apparus très efficients. Cette thèse comprend aussi une étude de l'intégration de bases de données spatiales hétérogènes lorsque les objets sont représentés avec le modèle QMM. Des résultats nouveaux ont été produits et des exemples d'application ont été explicités.
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Marques, Delano Brandes. "SISTEMA INTEGRADO DE MONITORAMENTO E CONTROLE DA QUALIDADE DE COMBUSTÍVEL." Universidade Federal do Maranhão, 2004. http://tedebc.ufma.br:8080/jspui/handle/tede/348.
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Previous issue date: 2004-02-27This work aims the implantation of an Integrated System that, besides allowing a better, more efficient and more practical monitoring, makes possible the control and optimization of problems related to the oil industry. In order to guarantee fuel s quality and normalization, the development of efficient tools that allow it s monitoring of any point (anywhere) and for any type of fuel is indispensable. Considering the variety of criteria, a decision making should be based on the evaluation of the most varied types of space data and not space data. In this sense, Knowledge Discovery in Databases process is used, where the Data Warehouse and Data Mining steps allied to a Geographic Information System are emphasized. This system presents as objective including several fuel monitoring regions. From different information obtained in the ANP databases, an analysis was carried out and a Data Warehouse model proposed. In the sequel, Data Mining techniques (Principal Component Analysis, Clustering Analysis and Multiple Regression) were applied to the results in order to obtain knowledge (patterns).
O presente trabalho apresenta estudos que visam a implantação de um Sistema Integrado que, além de permitir um melhor monitoramento, praticidade e eficiência, possibilite o controle e otimização de problemas relacionados à indústria de petróleo. Para garantir qualidade e normalização do combustível, é indispensável o desenvolvimento de ferramentas eficientes que permitam o seu monitoramento de qualquer ponto e para qualquer tipo de combustível. Considerando a variedade dos critérios, uma tomada de decisão deve ser baseada na avaliação dos mais variados tipos de dados espaciais e não espaciais. Para isto, é utilizado o Processo de Descoberta de Conhecimento, onde são enfatizadas as etapas de Data Warehouse e Data Mining aliadas ao conceito de um Sistema de Informação Geográfica. O sistema tem por objetivo abranger várias regiões de monitoramento de combustíveis. A partir do levantamento e análise das diferentes informações usadas nos bancos de dados da ANP foi proposto um modelo de data warehouse. Na seqüência foram aplicadas técnicas de mineração de dados (Análise de Componentes Principais, Análise de Agrupamento e Regressão) visando à obtenção de conhecimento (padrões).
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Guénec, Nadège. "Méthodologies pour la création de connaissances relatives au marché chinois dans une démarche d'Intelligence Économique : application dans le domaine des biotechnologies agricoles." Phd thesis, Université Paris-Est, 2009. http://tel.archives-ouvertes.fr/tel-00554743.
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Le décloisonnement des économies et l'accélération mondiale des échanges commerciaux ont, en une décennie à peine, transformés l'environnement concurrentiel des entreprises. La zone d'activités s'est élargie en ouvrant des nouveaux marchés à potentiels très attrayants. Ainsi en est-il des BRIC (Brésil, Russie, Inde et Chine). De ces quatre pays, impressionnants par la superficie, la population et le potentiel économique qu'ils représentent, la Chine est le moins accessible et le plus hermétique à notre compréhension de par un système linguistique distinct des langues indo-européennes d'une part et du fait d'une culture et d'un système de pensée aux antipodes de ceux de l'occident d'autre part. Pourtant, pour une entreprise de taille internationale, qui souhaite étendre son influence ou simplement conserver sa position sur son propre marché, il est aujourd'hui absolument indispensable d'être présent sur le marché chinois. Comment une entreprise occidentale aborde-t-elle un marché qui de par son altérité, apparaît tout d'abord comme complexe et foncièrement énigmatique ? Six années d'observation en Chine, nous ont permis de constater les écueils dans l'accès à l'information concernant le marché chinois. Comme sur de nombreux marchés extérieurs, nos entreprises sont soumises à des déstabilisations parfois inimaginables. L'incapacité à " lire " la Chine et à comprendre les enjeux qui s'y déroulent malgré des effets soutenus, les erreurs tactiques qui découlent d'une mauvaise appréciation du marché ou d'une compréhension biaisée des jeux d'acteurs nous ont incités à réfléchir à une méthodologie de décryptage plus fine de l'environnement d'affaire qui puisse offrir aux entreprises françaises une approche de la Chine en tant que marché. Les méthodes de l'Intelligence Economique (IE) se sont alors imposées comme étant les plus propices pour plusieurs raisons : le but de l'IE est de trouver l'action juste à mener, la spécificité du contexte dans lequel évolue l'organisation est prise en compte et l'analyse se fait en temps réel. Si une approche culturelle est faite d'interactions humaines et de subtilités, une approche " marché " est dorénavant possible par le traitement automatique de l'information et de la modélisation qui s'en suit. En effet, dans toute démarche d'Intelligence Economique accompagnant l'implantation d'une activité à l'étranger, une grande part de l'information à portée stratégique vient de l'analyse du jeu des acteurs opérants dans le même secteur d'activité. Une telle automatisation de la création de connaissance constitue, en sus de l'approche humaine " sur le terrain ", une réelle valeur ajoutée pour la compréhension des interactions entre les acteurs car elle apporte un ensemble de connaissances qui, prenant en compte des entités plus larges, revêtent un caractère global, insaisissable par ailleurs. La Chine ayant fortement développé les technologies liées à l'économie de la connaissance, il est dorénavant possible d'explorer les sources d'information scientifiques et techniques chinoises. Nous sommes en outre convaincus que l'information chinoise prendra au fil du temps une importance de plus en plus cruciale. Il devient donc urgent pour les organisations de se doter de dispositifs permettant non seulement d'accéder à cette information mais également d'être en mesure de traiter les masses d'informations issues de ces sources. Notre travail consiste principalement à adapter les outils et méthodes issues de la recherche française à l'analyse de l'information chinoise en vue de la création de connaissances élaborées. L'outil MATHEO, apportera par des traitements bibliométriques une vision mondiale de la stratégie chinoise. TETRALOGIE, outil dédié au data-mining, sera adapté à l'environnement linguistique et structurel des bases de données scientifiques chinoises. En outre, nous participons au développement d'un outil d'information retreival (MEVA) qui intègre les données récentes des sciences cognitives et oeuvrons à son application dans la recherche de l'information chinoise, pertinente et adéquate. Cette thèse étant réalisée dans le cadre d'un contrat CIFRE avec le Groupe Limagrain, une application contextualisée de notre démarche sera mise en œuvre dans le domaine des biotechnologies agricoles et plus particulièrement autour des enjeux actuels de la recherche sur les techniques d'hybridation du blé. L'analyse de ce secteur de pointe, qui est à la fois une domaine de recherche fondamentale, expérimentale et appliquée donne actuellement lieu à des prises de brevets et à la mise sur le marché de produits commerciaux et représente donc une thématique très actuelle. La Chine est-elle réellement, comme nous le supposons, un nouveau territoire mondial de la recherche scientifique du 21e siècle ? Les méthodes de l'IE peuvent-elles s'adapter au marché chinois ? Après avoir fourni les éléments de réponses à ces questions dans es deux premières parties de notre étude, nous poserons en troisième partie, le contexte des biotechnologies agricoles et les enjeux mondiaux en terme de puissance économico-financière mais également géopolitique de la recherche sur l'hybridation du blé. Puis nous verrons en dernière partie comment mettre en œuvre une recherche d'information sur le marché chinois ainsi que l'intérêt majeur en terme de valeur ajoutée que représente l'analyse de l'information chinoise
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Tzeng, Se-Min, and 曾世民. "Design and Implementaion of Geographic Data Warehouse in Flower Supply Chain." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/05077418900121275821.
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碩士國立交通大學
工業工程與管理系
91
Visual information has a better display effect for reducing the cognitive overload problem than the text-based information in data warehouses. From this viewpoint, a geographic interface is proposed between the users and the data warehouse owned by Taipei Flower Auction Limited Company (TFALC). Also how to visualize the business intelligence of the data warehouse becomes the major research topic of this thesis. The process of visualization includes the analysis of business intelligence requirements, design of geographic maps, and interface implementation for connecting the maps with related flower data in the data warehouse. Several software modules are involved in this process such as Impromptu, PowerPlay, Visualizer, etc. The addition of visual feature makes the data warehouse much easier to use in the TFALC-centered flower supply chain.
Book chapters on the topic "Geographic data warehouses"
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Siqueira, Thiago Luís Lopes, Cristina Dutra de Aguiar Ciferri, Valéria Cesário Times, and Ricardo Rodrigues Ciferri. "Towards Vague Geographic Data Warehouses." In Geographic Information Science, 173–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33024-7_13.
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Siqueira, Thiago Luís Lopes, Rodrigo Costa Mateus, Ricardo Rodrigues Ciferri, Valéria Cesário Times, and Cristina Dutra Aguiar de Ciferri. "Querying Vague Spatial Information in Geographic Data Warehouses." In Lecture Notes in Geoinformation and Cartography, 379–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19789-5_19.
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Brito, Jaqueline Joice, Thiago Luís Lopes Siqueira, Valéria Cesário Times, Ricardo Rodrigues Ciferri, and Cristina Dutra de Ciferri. "Efficient Processing of Drill-across Queries over Geographic Data Warehouses." In Data Warehousing and Knowledge Discovery, 152–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23544-3_12.
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Glorio, Octavio, and Juan Trujillo. "Designing Data Warehouses for Geographic OLAP Querying by Using MDA." In Computational Science and Its Applications – ICCSA 2009, 505–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02454-2_36.
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de Moura, Ana Maria C., Marcio Victorino, and Asterio Tanaka. "Combining Mediator and Data Warehouse Technologies for Developing Environmental Decision Support Systems." In Geographic Information Science, 196–208. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45799-2_14.
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Rocha, Guilherme M., Piero L. Capelo, and Cristina D. A. Ciferri. "Healthcare Decision-Making Over a Geographic, Socioeconomic, and Image Data Warehouse." In ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium, 85–97. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55814-7_7.
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Savary, Lionel, Georges Gardarin, and Karine Zeitouni. "GeoCache." In Geographic Information Systems, 550–68. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2038-4.ch034.
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GML is a promising model for integrating geodata within data warehouses. The resulting databases are generally large and require spatial operators to be handled. Depending on the size of the target geographical data and the number and complexity of operators in a query, the processing time may quickly become prohibitive. To optimize spatial queries over GML encoded data, this paper introduces a novel cache-based architecture. A new cache replacement policy is then proposed. It takes into account the containment properties of geographical data and predicates, and allows evicting the most irrelevant values from the cache. Experiences with the GeoCache prototype show the effectiveness of the proposed architecture with the associated replacement policy, compared to existing works.
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Layouni, Olfa, and Jalel Akaichi. "Personalized Spatio-Temporal OLAP Queries Suggestion Based on User Behavior and a New Similarity Measure." In Emerging Perspectives in Big Data Warehousing, 105–28. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5516-2.ch005.
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Spatio-temporal data warehouses store enormous amount of data. They are usually exploited by spatio-temporal OLAP systems to extract relevant information. For extracting interesting information, the current user launches spatio-temporal OLAP (ST-OLAP) queries to navigate within a geographic data cube (Geo-cube). Very often choosing which part of the Geo-cube to navigate further, and thus designing the forthcoming ST-OLAP query, is a difficult task. So, to help the current user refine his queries after launching in the geo-cube his current query, we need a ST-OLAP queries suggestion by exploiting a Geo-cube. However, models that focus on adapting to a specific user can help to improve the probability of the user being satisfied. In this chapter, first, the authors focus on assessing the similarity between spatio-temporal OLAP queries in term of their GeoMDX queries. Then, they propose a personalized query suggestion model based on users' search behavior, where they inject relevance between queries in the current session and current user' search behavior into a basic probabilistic model.
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Bimonte, Sandro, Omar Boucelma, Olivier Machabert, and Sana Sellami. "A Generic Spatial OLAP Model for Evaluating Natural Hazards in a Volunteered Geographic Information Context." In Geospatial Research, 485–501. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9845-1.ch021.
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Spatial data warehouses (SDW) and spatial OLAP (SOLAP) systems are well-known business intelligence technologies that aim to support a multidimensional and online analysis for a large volume of geo-referenced datasets. SOLAP systems are already used in the context of natural hazards for analyzing sensor data and experts' measurements. Recently, new data gathering tools coined as volunteered geographic information systems (VGI) have been adopted especially by non-expert users. Hence, (spatial) application development is facing a new challenge, which is the integration of expert-oriented data with citizen-provided data. In this paper, we propose a new generic spatio-multidimensional model based on the question/answer risk evaluation model that allows the integration of VGI data with classical SDW and SOLAP systems for the online analysis of natural hazards monitored by volunteers.
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Gamidullaeva, Leyla Ayvarovna, Sergey Mikhailovich Vasin, Nadezhda Chernetsova, Elena Shkarupeta, Dina Kharicheva, and Maria Gerasimenko. "Emerging Perspectives on Using Avatar-Based Management Techniques for Internet User Investigations." In Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms, 268–80. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1581-5.ch014.
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This chapter shows that statistics collection methods are the same for various types of websites. Often, a simple “counter” is used for both unique visitors to the site and the total number of hits to the site from unique and previously registered users. Speaking of a “digital” or “smart” economy, authors distinguish different categories (levels) of development: analysis, content of business intelligence, large data warehouses. Business analytics can be divided into a number of parts: modeling and analysis of system dynamics, expert systems and databases; knowledge and technology; geographic information (geo location); system analysis and design. The various methods and forms of information (statistical models) used to identify non-trivial patterns and propose solutions are often associated today with the concept of data mining. Intelligent data analysis involves the use of knowledge from a complex of data (databases). According to experts, data mining is one of the elements that is part of the process (database management system), which includes the analysis and cleaning of data.
Conference papers on the topic "Geographic data warehouses"
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van Wyngaarden, Robert, and Mel VanderWal. "Managing GIS and Spatial Data to Support Effective Decision Making Throughout the Pipeline Lifecycle." In 2006 International Pipeline Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/ipc2006-10472.
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Many pipeline industry managers and senior officials intuitively understand that location is important to most aspects related to pipelines throughout the life-cycle — from project concept, through construction and operations and finally to decommissioning. However, many organizations are not taking full advantage of location as being a vital component to support business decision-making across the entire range of activities undertaken by pipeline companies. A Geographic Information System (GIS) is a tool that takes advantage of geography. GIS is ideally suited for the storage, display, and output of geographic data, and moreover, the analysis and modeling of geographic data. While GIS has been around as a technology for over 30 years it is only in the last several years that it has started to be extensively used within the pipeline industry. Most managers have heard about GIS. Many organizations have already started to implement GIS and CAD-based solutions through individual projects and with a technical focus of automating work flows or business processes such as generating alignment sheets, regulatory compliance, integrity management, and land management to name a few. Given that many of these applications tend to be stand-alone or isolated developments, pipeline companies need to look at the complete spatial environment of all potential tools and applications, and support this with a vision of a common spatial data warehouse in a holistic sense. Any company that embraces a continuous gathering of spatial data throughout the pipeline life-cyle will have a significant knowledge base whose value will increase over time. A spatial data warehouse of truly integrated environmental, engineering and socioeconomic factors related to a pipeline during the entire lifecycle will have a total value that transcends the value of the individual factors. The Return on Investment (ROI) of a properly developed GIS framework and spatial data warehouse looking at all operational demands and support applications will certainly be many times over the original expenditure as measured in cost savings as well as better decision making. This paper will present insights and approaches into how to properly and effectively leverage the spatial data asset and in deploying GIS throughout the enterprise. These include addressing all of the elements that are key in implementing GIS — hardware, software, data, people and methods — as well as considering some of the ROI and value-based measures for GIS success.
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Selmoune, Nazih, Nadia Abdat, and Zaia Alimazighi. "Towards a Geographic Data Warehouse for Water Resources Management." In 2012 Second International Workshop on Advanced Information Systems for Enterprises (IWAISE). IEEE, 2012. http://dx.doi.org/10.1109/iwaise.2012.12.
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Lopes Siqueira, Thiago Luís, Ricardo Rodrigues Ciferri, Valéria Cesário Times, and Cristina Dutra de Aguiar Ciferri. "A spatial bitmap-based index for geographical data warehouses." In the 2009 ACM symposium. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1529282.1529582.
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Ezzedine, Sana, Sami Yassine Turki, and Sami Faiz. "An automatic transition from geographic CIM to Spatial Data Warehouse." In 2013 International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2013. http://dx.doi.org/10.1109/codit.2013.6689562.
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Colonese, Giovanni, Rodrigo Soares Manhães, Sahudy Montenegro González, Rogério Atem De Carvalho, and Asterio Kiyoshi Tanaka. "PostGeoOlap: an Open-Source Tool for Decision Support." In II Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação, 2005. http://dx.doi.org/10.5753/sbsi.2005.14976.
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This work describes PostGeoOlap, a decision support tool that integrates OLAP (On-Line Analytical Processing) and GIS (Geographical Information System) technologies in a single application. PostGeoOlap is an open source and a general-purpose tool to be used by application developers to easily develop their decision support applications. This tool works on the PostGreSQL DBMS using its spatial extensions (PostGIS) and performs the analytical and geographical functionalities using data warehouses.
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Luo, Xian, Youpeng Xu, and Feng Zhou. "Research on the integration of data warehouse, virtual reality and geographical information system in water resources management." In 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM). IEEE, 2011. http://dx.doi.org/10.1109/icsdm.2011.5969095.
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