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Journal articles on the topic 'SOLAP'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Bimonte, Sandro, Michela Bertolotto, Jérôme Gensel, and Omar Boussaid. "Spatial OLAP and Map Generalization." International Journal of Data Warehousing and Mining 8, no. 1 (January 2012): 24–51. http://dx.doi.org/10.4018/jdwm.2012010102.

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Map generalization can be used as a central component of Spatial Decision Support Systems to provide a simplified and more readable cartographic visualization of geographic information. Indeed, it supports the user mental process for discovering important and unknown geospatial relations, trends and patterns. Spatial OLAP (SOLAP) integrates spatial data into OLAP and data warehouse systems. SOLAP models and tools are based on the concepts of spatial dimensions and measures that represent the axes and the subjects of the spatio-multidimensional analysis. Although powerful under some respect, current SOLAP models cannot support map generalization capabilities. This paper provides the first effort to integrate Map Generalization and OLAP. Firstly the authors define all modeling and querying requirements to do this integration, and then present a SOLAP model and algebra that support map generalization concepts. The approach extends SOLAP spatial hierarchies introducing multi-association relationships, supports imprecise measures, and it takes into account spatial dimensions constraints generated by multiple map generalization hierarchies.

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Edoh-Alove, Elodie, Sandro Bimonte, François Pinet, and Yvan Bédard. "New Design Approach to Handle Spatial Vagueness in Spatial OLAP Datacubes." International Journal of Agricultural and Environmental Information Systems 6, no. 3 (July 2015): 29–49. http://dx.doi.org/10.4018/ijaeis.2015070103.

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Spatial-OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatial data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state. Also, analyzing multidimensional data with metadata brought by the exploitation of the new models can be too complex and demanding for decision-makers. To help reduce spatial vagueness consequences on the exactness of SOLAP analysis queries, the authors present a new approach for designing SOLAP datacubes based on end-users' tolerance to the risks of misinterpretation of fact data. An experimentation of the new approach on agri-environmental data is also proposed.

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3

Bimonte, Sandro. "Current Approaches, Challenges, and Perspectives on Spatial OLAP for Agri-Environmental Analysis." International Journal of Agricultural and Environmental Information Systems 7, no. 4 (October 2016): 32–49. http://dx.doi.org/10.4018/ijaeis.2016100103.

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Spatial OLAP (SOLAP) systems are powerful GeoBusiness Intelligence tools for analysing massive volumes of geo-referenced datasets. Therefore, these technologies are receiving considerable attention in the research community and in the database industry as well. Applications of these technologies are current in several domains such as ad marketing, healthcare, and urban development, to name a few. Contrary to other application domains, in the context of agri-environmental data and analysis, SOLAP systems have been underexploited. Therefore, in this paper, the author makes an exhaustive survey of most of the published studies in the domain of the SOLAP analysis of agri-environmental data with an emphasis on the reasons why only few recent works investigate the use of SOLAP systems in the agri-environmental context. In particular, the author focuses on the complexity of the spatio-multidimensional model and its implementation. Moreover, based on surveying the state of the art in this domain, this paper identifies some general guidelines that must be considered by the scientific community to design and implement efficient SOLAP approaches to the analysis of geo-referenced agri-environmental datasets. Finally, open issues about warehousing and OLAPing agri-environmental data are also shown in the paper.

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4

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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5

Edoh-Alove, Elodie, Sandro Bimonte, and François Pinet. "An UML Profile and SOLAP Datacubes Multidimensional Schemas Transformation Process for Datacubes Risk-Aware Design." International Journal of Data Warehousing and Mining 11, no. 4 (October 2015): 64–83. http://dx.doi.org/10.4018/ijdwm.2015100104.

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Spatial Data Warehouses (SDWs) and Spatial On-Line Analytical Processing (SOLAP) systems are new technologies for the integration and the analysis of huge volume of data with spatial reference. Spatial vagueness is often neglected in these types of systems and the data and analysis results are considered reliable. In a previous work, the authors provided a new design method for SOLAP datacubes that allows the handling of vague spatial data analysis issues. The method consists of tailoring SOLAP datacubes schemas to end-users tolerance levels to identified potential risks of misinterpretation they encounter when exploiting datacubes containing vague spatial data. It this paper, the authors further their previous proposal by presenting different formal tools to support their method: it is an UML profile providing stereotypes needed to add vague, risks and tolerance levels information on datacubes schemas plus the formal definition of SOLAP datacubes schemas transformation process and functions.

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6

Bimonte, Sandro, Anne Tchounikine, Maryvonne Miquel, and François Pinet. "When Spatial Analysis Meets OLAP." International Journal of Data Warehousing and Mining 6, no. 4 (October 2010): 33–60. http://dx.doi.org/10.4018/jdwm.2010100103.

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Introducing spatial data into multidimensional models leads to the concept of Spatial OLAP (SOLAP). Existing SOLAP models do not completely integrate the semantic component of geographic information (alphanumeric attributes and relationships) or the flexibility of spatial analysis into multidimensional analysis. In this paper, the authors propose the GeoCube model and its associated operators to overcome these limitations. GeoCube enriches the SOLAP concepts of spatial measure and spatial dimension and take into account the semantic component of geographic information. The authors define geographic measures and dimensions as geographic and/or complex objects belonging to hierarchy schemas. GeoCube’s algebra extends SOLAP operators with five new operators, i.e., Classify, Specialize, Permute, OLAP-Buffer and OLAP-Overlay. In addition to classical drill-and-slice OLAP operators, GeoCube provides two operators for navigating the hierarchy of the measures, and two spatial analysis operators that dynamically modify the structure of the geographic hypercube. Finally, to exploit the symmetrical representation of dimensions and measures, GeoCube provides an operator capable of permuting dimension and measure. In this paper, GeoCube is presented using environmental data on the pollution of the Venetian Lagoon.

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7

Zemri, Farah Amina, and Hamdadou Djamila. "SOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems." International Journal of Interactive Multimedia and Artificial Intelligence 5, no. 7 (2019): 96. http://dx.doi.org/10.9781/ijimai.2019.10.002.

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8

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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9

Ghita, Farah, and Rina Trisminingsih. "Pengujian Data Warehouse SOLAP untuk Komoditas Pertanian Indonesia." Jurnal Ilmu Komputer dan Agri-Informatika 8, no. 1 (May 31, 2021): 42–56. http://dx.doi.org/10.29244/jika.8.1.42-56.

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Pengujian merupakan tahapan yang sangat penting dalam pengembangan data warehouse, karena analisis dan keputusan dibuat berdasarkan informasi yang dihasilkan dari data warehouse. Terdapat sistem yang memungkinkan analisis pada data spasial dengan interaktif dan efisien, yaitu sistem spatial OLAP (SOLAP). Dalam pembangunan data warehouse terdapat tahapan penting, yaitu proses extract, transform, load (ETL). Penelitian ini melakukan pengujian data warehouse, khususnya pengujian modul ETL pada SOLAP komoditas pertanian Indonesia yang telah dikembangkan pada penelitian sebelumnya. Hasil pengujian proses ETL menunjukkan adanya ketidaksesuaian antara data sumber dan data warehouse. Dalam penelitian ini, pengujian modul ETL dilakukan dengan pengujian fungsional, yaitu memvalidasi data target dengan data sumber. Pengujian modul ETL diawali dengan membuat source-to-target mappings dan aturan kualitas data sebagai acuan untuk pembuatan kasus uji. Pengujian proses ETL terdiri atas pengujian kualitas data dan keseimbangan data yang dilakukan dengan menjalankan kueri pada sistem manajemen basis data (DBMS). Pengujian keseimbangan data menggunakan metode simple random sampling dan systematic sampling. Hasil pengujian dianalisis dan ditemukan letak kesalahan pengembangan pada proses ETL, tampilan aplikasi SOLAP dan pengambilan data sumber. Kata Kunci: Data warehouse, ETL, komoditas pertanian, pengujian data warehouse.

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10

Ali, Ben, and Samar Mouakket. "Integrating OLAP/SOLAP in E-Business Domains." Information Resources Management Journal 24, no. 3 (July 2011): 45–60. http://dx.doi.org/10.4018/irmj.2011070104.

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E-business domains have been considered killer domains for different data analysis techniques. Most researchers have examined data mining (DM) techniques to analyze the databases behind E-business websites. DM has shown interesting results, but this technique presents some restrictions concerning the content of the database and the level of expertise of the users interpreting the results. In this paper, the authors show that successful and more sophisticated results can be obtained using other analysis techniques, such as Online Analytical Processing (OLAP) and Spatial OLAP (SOLAP). Thus, the authors propose a framework that fuses or integrates OLAP with SOLAP techniques in an E-business domain to perform easier and more user-friendly data analysis (non-spatial and spatial) and improve decision making. In addition, the authors apply the framework to an E-business website related to online job seekers in the United Arab Emirates (UAE). The results can be used effectively by decision makers to make crucial decisions in the job market of the UAE.

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11

McHugh, Rosemarie, Stéphane Roche, and Yvan Bédard. "Towards a SOLAP-based public participation GIS." Journal of Environmental Management 90, no. 6 (May 2009): 2041–54. http://dx.doi.org/10.1016/j.jenvman.2008.01.020.

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12

Qahhariana, Anna, and Imas Sukaesih Sitanggang. "Peningkatan Kinerja Sistem Spatial Online Analytical Processing (SOLAP) Titik Panas Kebakaran Hutan." Jurnal Ilmu Komputer dan Agri-Informatika 5, no. 1 (July 25, 2018): 21. http://dx.doi.org/10.29244/jika.5.1.21-30.

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Data histori titik panas sebagai salah satu indikator kebakaran hutan dan lahan dapat dikelola dengan teknologi data warehouse dan sistem spatial online analytical processing (SOLAP). Pada penelitian sebelumnya telah dilakukan peningkatan kinerja terhadap sistem tersebut sehingga titik panas yang mampu dihasilkan meningkat menjadi 1500 titik. Penelitian ini bertujuan untuk meningkatkan kinerja sistem SOLAP data titik panas yang telah dibangun dalam penelitian sebelumnya. Peningkatan kinerja meliputi konfigurasi dari sisi perangkat lunak seperti peningkatan Java runtime environment (JRE), peningkatan server Apache Tomcat, dan peringkasan proses Javascript object notation (JSON) sedangkan spesifikasi perangkat keras menggunakan spesifikasi RAM dan processor yang sama dengan penelitian sebelumnya. Jumlah titik panas hasil query yang mampu dihasilkan dari konfigurasi tersebut meningkat menjadi 5344 titik.<br /><br />Kata kunci: kebakaran hutan, spatial data warehouse, spatial OLAP, titik panas

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13

S Sitanggang, I., R. Trisminingsih, H. Khotimah, and M. Syukur. "Usability testing of SOLAP for Indonesia agricultural commodity." IOP Conference Series: Earth and Environmental Science 299 (July 29, 2019): 012054. http://dx.doi.org/10.1088/1755-1315/299/1/012054.

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14

Badard, Thierry, Yvan Bedard, Frederic Hubert, Eveline Bernier, and Etienne Dube. "Web services-oriented architectures for mobile SOLAP applications." International Journal of Web Engineering and Technology 4, no. 4 (2008): 434. http://dx.doi.org/10.1504/ijwet.2008.019943.

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15

Amorim, Brunna De Sousa Pereira, Daniel Farias Batista Leite, and Cláudio De Souza Baptista. "An exploratory SOLAP tool for linked open data." International Journal of Business Information Systems 31, no. 3 (2019): 391. http://dx.doi.org/10.1504/ijbis.2019.10022645.

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16

Leite, Daniel Farias Batista, Cláudio De Souza Baptista, and Brunna De Sousa Pereira Amorim. "An exploratory SOLAP tool for linked open data." International Journal of Business Information Systems 31, no. 3 (2019): 391. http://dx.doi.org/10.1504/ijbis.2019.101115.

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17

Bimonte, Sandro, François Pinet, André Miralles, and Petraq Papajorgji. "Special section on “Spatial data warehouses and SOLAP”." GeoInformatica 18, no. 2 (November 30, 2013): 269–72. http://dx.doi.org/10.1007/s10707-013-0196-9.

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18

Bimonte, Sandro, Marilys Pradel, Daniel Boffety, Aurelie Tailleur, Géraldine André, Rabi Bzikha, and Jean-Pierre Chanet. "A New Sensor-Based Spatial OLAP Architecture Centered on an Agricultural Farm Energy-Use Diagnosis Tool." International Journal of Decision Support System Technology 5, no. 4 (October 2013): 1–20. http://dx.doi.org/10.4018/ijdsst.2013100101.

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Agricultural energy consumption is an important environmental and social issue. Several diagnosis tools have been proposed to define indicators for analyzing the large-scale energy consumption of agricultural farm activities (year, farm, production activity, etc.). In Bimonte, Boulil, Chanet and Pradel (2012), the authors define (i) new appropriate indicators to analyze agricultural farm energy-use performance on a detailed scale and (ii) show how Spatial Data Warehouse (SDW) and Spatial OnLine Analytical Processing (SOLAP) GeoBusiness Intelligence (GeoBI) technologies can be used to represent, store, and analyze these indicators by simultaneously producing graphical and cartographic reports. These GeoBI technologies allow for the analysis of huge volumes of georeferenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical, and cartographic displays. However, existing data collection systems based on sensors are not well adapted for agricultural data. In this paper, the authors show the global architecture of our GeoBI solution and highlight the data collection process based on agricultural ad hoc sensor networks, the associated transformation and cleaning operations performed by means of Spatial Extract Transform Load (ETL) tools, and a new implementation of the system using a web-services-based loosely coupled SOLAP architecture to provide interoperability and reusability of the complex multi-tier GeoBI architecture. Moreover, the authors detail how the energy-use diagnosis tool proposed in Bimonte, Boulil, Chanet and Pradel (2012) theoretically fits with the sensor data and the SOLAP approach.

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Silva, Ricardo, João Moura-Pires, and Maribel Yasmina Santos. "Spatial Clustering in SOLAP Systems to Enhance Map Visualization." International Journal of Data Warehousing and Mining 8, no. 2 (April 2012): 23–43. http://dx.doi.org/10.4018/jdwm.2012040102.

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The emergence of the SOLAP concept supports map visualization for improving data analysis, enhancing the decision making process. However, in this environment, maps can easily become cluttered losing the benefits that triggered the appearance of this concept. In order to overcome this problem, a post-processing model is proposed, which relies on Geovisual Analytics principles. Namely, it takes advantage from the user interaction and the spatial clustering approach in order to reduce the number of elements to be visualized when this number is inadequate to a proper map analysis. Moreover, a novel heuristic to identify the threshold value from which the clusters must be generated was developed. The proposed post-processing model takes into account the query performed, i.e., the number of spatial attributes, the number of spatial dimensions, and the type of spatial objects selected from dimensions. The results obtained so far show: (i) the novel approach to support queries with two spatial attributes from different dimensions allows useful analysis; (ii) the proposed post-processing model is very effective in maintaining a map suitable to the user’s cognitive process; and, (iii) the heuristic proposed provide the user participation in the clustering process, in a user-friendly way.

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20

Charef, Abdallah Bensalloua, and Hamdadou Djamila. "Users Integrity Constraints in SOLAP Systems. Application in Agroforestry." International Journal of Interactive Multimedia and Artificial Intelligence 5, no. 1 (2018): 47. http://dx.doi.org/10.9781/ijimai.2018.01.003.

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21

Siqueira, Thiago Luís Lopes, Cristina Dutra de Aguiar Ciferri, Valéria Cesário Times, Anjolina Grisi de Oliveira, and Ricardo Rodrigues Ciferri. "The impact of spatial data redundancy on SOLAP query performance." Journal of the Brazilian Computer Society 15, no. 2 (June 2009): 19–34. http://dx.doi.org/10.1590/s0104-65002009000200003.

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Siqueira, Thiago Luís Lopes, Cristina Dutra de Aguiar Ciferri, Valéria Cesário Times, Anjolina Grisi de Oliveira, and Ricardo Rodrigues Ciferri. "The impact of spatial data redundancy on SOLAP query performance." Journal of the Brazilian Computer Society 15, no. 2 (June 2009): 19–34. http://dx.doi.org/10.1007/bf03194499.

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23

Gómez, Leticia Irene, Silvia Alicia Gómez, and Alejandro Vaisman. "Modeling and Querying Continuous Fields with OLAP Cubes." International Journal of Data Warehousing and Mining 9, no. 3 (July 2013): 22–45. http://dx.doi.org/10.4018/jdwm.2013070102.

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The notion of SOLAP (Spatial On-Line Analytical Processing) is aimed at exploring spatial data in the same way as OLAP operates over tables. SOLAP, however, only accounts for discrete spatial data. Current decision support systems are increasingly being needed for handling more complex types of data, like continuous fields, which describe physical phenomena that change continuously in time and/or space (e.g., temperature). Although many models have been proposed for adding spatial (continuous and discrete) information to OLAP tools, no one is general enough to allow users to just perceive data as a cube, and analyze any type of spatial data together with typical alphanumerical discrete OLAP data, using only the classic OLAP operators (e.g., Roll-up, Drill-down). In this paper the authors propose a model and an algebra supporting it, that allow operating over data cubes, independently of the underlying data types and physical data representation. That means, in this approach, the final user only sees the typical OLAP operators at the query level, whereas at lower abstraction levels the authors provide discrete and continuous spatial data support as well as different ways of partitioning the space. As far as the authors are aware of, this is the first proposal, which provides such a general framework for spatiotemporal data analysis.

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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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aissi, Saida, Mohamed Salah Gouider, Tarek Sboui, and Lamjed Ben Said. "Personnalisation OLAP et SIG : Etude comparative et perspectives de personnalisation SOLAP." Journal of Decision Systems 25, no. 1 (October 19, 2015): 42–55. http://dx.doi.org/10.1080/12460125.2015.1081049.

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26

Mahboubi, Hadj, Sandro Bimonte, Guillaume Deffuant, Jean-Pierre Chanet, and François Pinet. "Semi-Automatic Design of Spatial Data Cubes from Simulation Model Results." International Journal of Data Warehousing and Mining 9, no. 1 (January 2013): 70–95. http://dx.doi.org/10.4018/jdwm.2013010104.

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In this paper the authors present a semi-automatic method for designing and generating spatial data cubes in order to visualize and analyze the results of simulation models. In the authors approach users choose their fact of analysis, then the system derives automatically a set of possible measures, dimensions of analysis, and generates the corresponding spatial data cubes. The analysis and visualization of the spatial data cubes are carried out using appropriate SOLAP tools. They also present the SimOLAP system, developed to validate their approach.

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27

Younsi, Fatima-Zohra. "Multicriteria decision making with ELECTRE III, SOLAP and GIS for spatiotemporal tuberculosis analytics." Medical Technologies Journal 1, no. 3 (September 28, 2017): 57–58. http://dx.doi.org/10.26415/2572-004x-vol1iss3p57-58.

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28

Li, Jiyuan, Lingkui Meng, Frank Z. Wang, Wen Zhang, and Yang Cai. "A Map-Reduce-enabled SOLAP cube for large-scale remotely sensed data aggregation." Computers & Geosciences 70 (September 2014): 110–19. http://dx.doi.org/10.1016/j.cageo.2014.05.008.

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29

Dubé, Etienne, Thierry Badard, and Yvan Bédard. "Une architecture orientée service web pour la constitution de minicubes SOLAP pour clients mobiles." Revue internationale de géomatique 19, no. 2 (June 30, 2009): 211–30. http://dx.doi.org/10.3166/geo.19.211-230.

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Kyung, Min-Ju, and Jae-Hong Yom. "Implementation of Open Source SOLAP Decision-Making System for Livestock Epidemic Surveillance and Prevention." Korean Journal of Geomatics 30, no. 3 (June 30, 2012): 287–94. http://dx.doi.org/10.7848/ksgpc.2012.30.3.287.

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31

Bensalloua, Charef Abdallah, and Djamila Hamdadou. "Spatial OLAP and Multicriteria Integrated Approach for Decision Support System." International Journal of Decision Support System Technology 10, no. 3 (July 2018): 1–26. http://dx.doi.org/10.4018/ijdsst.2018070101.

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This article describes how Spatial On-Line Analytical Processing, such a decisional technology, offers the possibilities of spatial and multidimensional analysis of data stored in multidimensional structure namely spatial data warehouse. However, this technology is limited in the quality aspect of the decision related to the multicriteria consideration. In the current article, the objective is to propose a Spatial Decision Support System namely “Silvicultura” for facilitating decision making in complex situations. This approach is based on integrating multicriteria analysis with SOLAP in order to enrich the spatial and multidimensional analysis with the contribution of MCA tools for mitigating conflict situations. The authors have based their proposal modeling on Unified Modeling language, since it is a well-known standard modeling language and can be easily extended for multidimensional modeling. Finally, in order to validate their proposal, the authors present a case study to show how to use it in the agroforestry management.

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Derbal, Khalissa Amieur, Zioual Tahar, Kamel Boukhalfa, Ibtissem Frihi, and Zaïa Alimazighi. "From spatial data warehouse and decision-making tool to SOLAP generalisation approach for efficient road risk analysis." International Journal of Information Technology and Management 15, no. 4 (2016): 364. http://dx.doi.org/10.1504/ijitm.2016.079605.

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Alimazighi, Zaïa, Ibtissem Frihi, Kamel Boukhalfa, Zioual Tahar, and Khalissa Amieur Derbal. "From spatial data warehouse and decision-making tool to SOLAP generalisation approach for efficient road risk analysis." International Journal of Information Technology and Management 15, no. 4 (2016): 364. http://dx.doi.org/10.1504/ijitm.2016.10000286.

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Rivest, Sonia, Yvan Bédard, Marie-Josée Proulx, Martin Nadeau, Frederic Hubert, and Julien Pastor. "SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data." ISPRS Journal of Photogrammetry and Remote Sensing 60, no. 1 (December 2005): 17–33. http://dx.doi.org/10.1016/j.isprsjprs.2005.10.002.

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Yazidi Alaoui, O., S. Hamdoune, H. Zili, H. Boulassal, M. Wahbi, and O. El Kharki. "CREATING STRATEGIC BUSINESS VALUE FROM BIG DATA ANALYSIS – APPLICATION TELECOM NETWORK DATA AND PLANNING DOCUMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 691–95. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-691-2019.

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Abstract. Mobile networks carrier gather and accumulate in their database system a considerable volume of data, that carries geographic information which is crucial for the growth of the company. This work aimed develop a prototype called Spatial On -Line Analytic Processing (SOLAP) to carry out multidimensional analysis and to anticipate the extension of the area of radio antennas.To this end, the researcher started by creating a Data warehouse that allows storing Big Data received from the Radio antennas. Then, doing the OLAP(online analytic processing) in order to perform multidimensional Analysis which used through GIS to represent the Data in different scales in satellite image as a topographic background). As a result, this prototype enables the carriers to receive continuous reports on different scales (Town, city, country) and to identify the BTS that works and performs well or shows the rate of its working (the way behaves) its pitfalls. By the end, it gives a clear image on the future working strategy respecting the urban planning, and the digital terrain model (DTM).

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Ibtisam, Ferrahi Ibtisam, Sandro Bimonte, and Kamel Boukhalfa. "Logical and Physical Design of Spatial Non-Strict Hierarchies in Relational Spatial Data Warehouse." International Journal of Data Warehousing and Mining 15, no. 1 (January 2019): 1–18. http://dx.doi.org/10.4018/ijdwm.2019010101.

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The emergence of spatial or geographic data in DW Systems defines new models that support the storage and manipulation of the data. The need to build an SDW and to optimize SOLAP queries continues to attract the interest of researchers in recent years. Several spatial data models have been investigated to extend classical multidimensional data models with spatial concepts. However, most of existing models do not handle a non-strict spatial hierarchy. Moreover, the complexity of the spatial data makes the execution time of spatial queries very considerable. Often, spatial indexation methods are applied to optimizing access to large volumes of data and helps reduce the cost of spatial OLAP queries. Most of existing indexes support predefined spatial hierarchies. The authors show, in this article, that the logical models proposed in the literature and indexing techniques are not suitable to non-strict hierarchies. The authors propose a new logical schema supporting the non-strict hierarchies and a bitmap index to optimize queries defined by spatial dimensions with several non-strict hierarchies.

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Younsi, Fatima-Zohra, Ahmed Bounnekar, Djamila Hamdadou, and Omar Boussaid. "Integration of Multiple Regression Model in an Epidemiological Decision Support System." International Journal of Information Technology & Decision Making 18, no. 06 (November 2019): 1755–83. http://dx.doi.org/10.1142/s0219622019500408.

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Prevention and control of influenza epidemics are major challenges for public health care services. Early identification of flu outbreak is an important step towards implementing effective disease interventions for reducing mortality and morbidity in human populations. Indeed, health officials need a real geo-making tool for monitoring and prediction. The aim of the current study is to discuss a novel spatiotemporal tool for monitoring and predicting the phenomenon of the seasonal influenza epidemic spread in the human population using multiple regression analysis. The suggested tool is mainly based on three sub-systems. It allows generating simulation data by the use of a simulation system, integrating data sources in a data warehouse (DW) system and performing a specific online analysis Spatial On-Line Analytical Processing (SOLAP). Our proposal enables also to illustrate evolution of disease through visualizations in time and space. It can examine social network effects to better understand the topological structure of social contact and the impact of its properties. A regression analysis is performed on the influenza epidemic to examine the main factors influencing flu incidence number and therefore to predict and track influenza epidemic.

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Ranjbar Nooshery, N., M. Taleai, R. Kazemi, and K. Ebadi. "DEVELOPING A WEB-BASED PPGIS, AS AN ENVIRONMENTAL REPORTING SERVICE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 12, 2017): 115–21. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-115-2017.

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Today municipalities are searching for new tools to empower locals for changing the future of their own areas by increasing their participation in different levels of urban planning. These tools should involve the community in planning process using participatory approaches instead of long traditional top-down planning models and help municipalities to obtain proper insight about major problems of urban neighborhoods from the residents’ point of view. In this matter, public participation GIS (PPGIS) which enables citizens to record and following up their feeling and spatial knowledge regarding problems of the city in the form of maps have been introduced. In this research, a tool entitled CAER (Collecting & Analyzing of Environmental Reports) is developed. In the first step, a software framework based on Web-GIS tool, called EPGIS (Environmental Participatory GIS) has been designed to support public participation in reporting urban environmental problems and to facilitate data flow between citizens and municipality. A web-based cartography tool was employed for geo-visualization and dissemination of map-based reports. In the second step of CAER, a subsystem is developed based on SOLAP (Spatial On-Line Analytical Processing), as a data mining tools to elicit the local knowledge facilitating bottom-up urban planning practices and to help urban managers to find hidden relations among the recorded reports. This system is implemented in a case study area in Boston, Massachusetts and its usability was evaluated. The CAER should be considered as bottom-up planning tools to collect people’s problems and views about their neighborhood and transmits them to the city officials. It also helps urban planners to find solutions for better management from citizen’s viewpoint and gives them this chance to develop good plans to the neighborhoods that should be satisfied the citizens.

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Bender, Kimlyn J. "The Sola behind the Solas: Martin Luther and The Unity and Future of the Five Solas of the Reformation." Evangelical Quarterly 90, no. 2 (April 26, 2019): 109–31. http://dx.doi.org/10.1163/27725472-09002002.

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The five Solas of the Reformation have a complex history and remain sources not only of doctrinal coalition but conflict. This essay examines the traditional five Solas – sola fide, sola gratia, sola scriptura, solus Christus, and soli Deo gloria – as present in nascent form in the writings of Martin Luther. While the technical terms themselves and their grouping are a later development, the incipient form of each sola is nevertheless evidenced in Luther’s corpus of writing. Having surveyed their presence and inter-relationship in Luther’s thought, the essay argues for the unity of the Solas and their continuing and valuable ability to express and articulate facets of the one revelatory and salvific economy of God, particularly when their function is seen not only as serving polemical ends of rejection and negation, but also and more beneficially outlining positive and properly ordered relations between faith and works, grace and gratitude, Scripture and tradition, Christ and the church, and God and the world. The essay concludes that if one of the Solas serves as the first among equals and the interpretive key to the others, it is that of Christ alone, and thus argues for a Christological interpretation of them all.

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Chaplin, W. J., Y. Elsworth, B. A. Miller, G. A. Verner, and R. New. "Solarp‐Mode Frequencies over Three Solar Cycles." Astrophysical Journal 659, no. 2 (April 20, 2007): 1749–60. http://dx.doi.org/10.1086/512543.

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Manchandani, Hanshul. "Space based solar power versus ground based solar power." International Journal of Research and Engineering 4, no. 11 (December 13, 2017): 260–62. http://dx.doi.org/10.21276/ijre.2017.4.11.1.

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Changhui Rao, Changhui Rao, Lei Zhu Lei Zhu, Xuejun Rao Xuejun Rao, Lanqiang Zhang Lanqiang Zhang, Hua Bao Hua Bao, Lin Kong Lin Kong, Youming Guo Youming Guo, et al. "Second generation solar adaptive optics for 1-m New Vacuum Solar Telescope at the Fuxian Solar Observatory." Chinese Optics Letters 13, no. 12 (2015): 120101–3. http://dx.doi.org/10.3788/col201513.120101.

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P.L.Verma, P. L. Verma, Anita Shukla, and Prabhat Pandey. "Solar Cycle Variability of Solar Activity Parameters and Cosmic Ray Intensity." International Journal of Scientific Research 3, no. 3 (June 1, 2012): 1–4. http://dx.doi.org/10.15373/22778179/march2014/138.

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Mondragón González, Carlos. "El quehacer filosófico en América Latina: notas sobre la obra de Horacio Cerutti Guldberg." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 7–14. http://dx.doi.org/10.20939/solar.2014.10.0101.

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Reding Blase, Sofía. "Soñar despiertos: La propuesta de Horacio Cerutti." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 25–33. http://dx.doi.org/10.20939/solar.2014.10.0103.

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Ibarra Peña, Alex. "Filosofía para la liberación, pensamiento utópico y marxismo latinoamericano." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 35–61. http://dx.doi.org/10.20939/solar.2014.10.0104.

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García Clarck, Rubén R. "Arturo Andrés Roig y Horacio Cerutti: compañeros de ruta." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 63–70. http://dx.doi.org/10.20939/solar.2014.10.0105.

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Martínez, Oscar. "Más allá de la filosofía de la liberación: Horacio Cerutti frente Enrique Dussel." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 71–86. http://dx.doi.org/10.20939/solar.2014.10.0106.

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Gómez Arredondo, David. "Temporalidad y filosofar desde nuestra América en Horacio Cerutti." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 87–94. http://dx.doi.org/10.20939/solar.2014.10.0107.

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Montoya Huamaní, Segundo. "Sobrevilla, David. Escritos mariateguianos. Artículos y reseñas en torno a José Carlos Mariátegui y su obra. Lima, UIGV, 2012; 244 pp." Solar, Revista de Filosofía Iberoamericana 10, no. 1 (July 1, 2014): 97–107. http://dx.doi.org/10.20939/solar.2014.10.0108.

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