Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data
Environmental data are currently gaining more and more interest as they are required to understand global changes. In this context, sensor data are collected and stored in dedicated databases. Frameworks have been developed for this purpose and rely on standards, as for instance the Sensor Observati...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-08-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | http://www.mdpi.com/2504-2289/2/3/25 |
| _version_ | 1818194332450029568 |
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| author | Hicham Hajj-Hassan Anne Laurent Arnaud Martin |
| author_facet | Hicham Hajj-Hassan Anne Laurent Arnaud Martin |
| author_sort | Hicham Hajj-Hassan |
| collection | DOAJ |
| description | Environmental data are currently gaining more and more interest as they are required to understand global changes. In this context, sensor data are collected and stored in dedicated databases. Frameworks have been developed for this purpose and rely on standards, as for instance the Sensor Observation Service (SOS) provided by the Open GeoSpatial Consortium (OGC), where all measurements are bound to a so-called Feature of Interest (FoI). These databases are used to validate and test scientific hypotheses often formulated as correlations and causality between variables, as for instance the study of the correlations between environmental factors and chlorophyll levels in the global ocean. However, the hypotheses of the correlations to be tested are often difficult to formulate as the number of variables that the user can navigate through can be huge. Moreover, it is often the case that the data are stored in such a manner that they prevent scientists from crossing them in order to retrieve relevant correlations. Indeed, the FoI can be a spatial location (e.g., city), but can also be any other object (e.g., animal species). The same data can thus be represented in several manners, depending on the point of view. The FoI varies from one representation to the other one, while the data remain unchanged. In this article, we propose a novel methodology including a crucial step to define multiple mappings from the data sources to these models that can then be crossed, thus offering multiple possibilities that could be hidden from the end-user if using the initial and single data model. These possibilities are provided through a catalog embedding the multiple points of view and allowing the user to navigate through these points of view through innovative OLAP-like operations. It should be noted that the main contribution of this work lies in the use of multiple points of view, as many other works have been proposed for manipulating, aggregating visualizing and navigating through geospatial information. Our proposal has been tested on data from an existing environmental observatory from Lebanon. It allows scientists to realize how biased the representations of their data are and how crucial it is to consider multiple points of view to study the links between the phenomena. |
| first_indexed | 2024-12-12T01:00:37Z |
| format | Article |
| id | doaj.art-e84bce5620c74edc9b71700db8df255c |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-12-12T01:00:37Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-e84bce5620c74edc9b71700db8df255c2022-12-22T00:43:45ZengMDPI AGBig Data and Cognitive Computing2504-22892018-08-01232510.3390/bdcc2030025bdcc2030025Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental DataHicham Hajj-Hassan0Anne Laurent1Arnaud Martin2National Council for Scientific Research Lebanon, 59 Zahia Salmane street, Jnah, 11-8281 Beirut, LebanonLIRMM, University of Montpellier, CNRS, 163 rue Auguste Broussonnet, 34090 Montpellier, FranceOREME, University of Montpellier, CNRS, IRD, 163 rue Auguste Broussonnet, 34090 Montpellier, FranceEnvironmental data are currently gaining more and more interest as they are required to understand global changes. In this context, sensor data are collected and stored in dedicated databases. Frameworks have been developed for this purpose and rely on standards, as for instance the Sensor Observation Service (SOS) provided by the Open GeoSpatial Consortium (OGC), where all measurements are bound to a so-called Feature of Interest (FoI). These databases are used to validate and test scientific hypotheses often formulated as correlations and causality between variables, as for instance the study of the correlations between environmental factors and chlorophyll levels in the global ocean. However, the hypotheses of the correlations to be tested are often difficult to formulate as the number of variables that the user can navigate through can be huge. Moreover, it is often the case that the data are stored in such a manner that they prevent scientists from crossing them in order to retrieve relevant correlations. Indeed, the FoI can be a spatial location (e.g., city), but can also be any other object (e.g., animal species). The same data can thus be represented in several manners, depending on the point of view. The FoI varies from one representation to the other one, while the data remain unchanged. In this article, we propose a novel methodology including a crucial step to define multiple mappings from the data sources to these models that can then be crossed, thus offering multiple possibilities that could be hidden from the end-user if using the initial and single data model. These possibilities are provided through a catalog embedding the multiple points of view and allowing the user to navigate through these points of view through innovative OLAP-like operations. It should be noted that the main contribution of this work lies in the use of multiple points of view, as many other works have been proposed for manipulating, aggregating visualizing and navigating through geospatial information. Our proposal has been tested on data from an existing environmental observatory from Lebanon. It allows scientists to realize how biased the representations of their data are and how crucial it is to consider multiple points of view to study the links between the phenomena.http://www.mdpi.com/2504-2289/2/3/25data modelsdata crossingdata mappingenvironmental observatory |
| spellingShingle | Hicham Hajj-Hassan Anne Laurent Arnaud Martin Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data Big Data and Cognitive Computing data models data crossing data mapping environmental observatory |
| title | Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data |
| title_full | Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data |
| title_fullStr | Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data |
| title_full_unstemmed | Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data |
| title_short | Exploiting Inter- and Intra-Base Crossing with Multi-Mappings: Application to Environmental Data |
| title_sort | exploiting inter and intra base crossing with multi mappings application to environmental data |
| topic | data models data crossing data mapping environmental observatory |
| url | http://www.mdpi.com/2504-2289/2/3/25 |
| work_keys_str_mv | AT hichamhajjhassan exploitinginterandintrabasecrossingwithmultimappingsapplicationtoenvironmentaldata AT annelaurent exploitinginterandintrabasecrossingwithmultimappingsapplicationtoenvironmentaldata AT arnaudmartin exploitinginterandintrabasecrossingwithmultimappingsapplicationtoenvironmentaldata |