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This paper introduces an approach illustrating how the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) framework can be used in order to build a franco-lebanese observatory. We present the practical application of SWE services as a source of real-time observation data and the associated technical architecture for making near real-time...
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... workflow of the system is shown in Fig. 5. The users use the 52N Sensor Web Client which provides easy access to snow weather time series data stored within the SOS. The clients can send a requestGetObservation to the SOS and receive the observation that is structured based on O&M. Through GetObservation operation, user can retrieve observations of interest for special ...
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... As described in [30], the O-LiFE observatory is implemented by relying on the 52 ? North German initiative for Geospatial Open Source software, Sensor Observation Service (SOS) and Observations and Measurements (O&M) The SOS is a web service to query real-time sensor data and sensor data time series and is part of the Sensor Web framework. ...
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.
... As described in [30], the O-LiFE observatory is implemented by relying on the 52 • North German initiative for Geospatial Open Source software, Sensor Observation Service (SOS) and Observations and Measurements (O&M) The SOS is a web service to query real-time sensor data and sensor data time series and is part of the Sensor Web framework. A 52 • North PostgreSQL database with a predefined schema by the 52 • North implementation of the SOS is used to store the sensors' data. ...
O-LiFE LIA is an observatory for the environment operating between fundamental and applied research. This platform was initiated between Lebanese and French teams. It focuses on the Mediterranean critical zone, inducing systemic observation of the
natural areas; its projects are revolving around water, biodiversity and environmental management. Organize, share, sustain and enhance environmental data are of its primary
objectives through exchanging of expertise and skills valorization towards building
environmental databases and innovative web services. The observatory aims at creating a strong lobbying effect in the circum Mediterranean network.
Environmental resources (e.g., air quality, water quantity) are needed to understand fundamental questions such as global change. Such resources are often collected from sensors, including humans acting as sensors. Tools have emerged to manage such data in the form of time series and, in particular, the Sensor Observation Service (SOS) which offers a framework based on predefined relational database schema. Environmental observatories can be built using such frameworks, allowing to address specific key scientific questions by collecting and sharing large-scale environmental data. However, the strict schema of SOS database makes it difficult to integrate some data that cannot be directly mapped to the schema. Guidelines and best practices are offered in the literature in order to reuse standards from the Semantic Web but they do not cover all needs. In particular, they do not help to reflect the fact that a single environmental database can lead to several SOS models. Since being aware of these multiple possibilities is crucial for a better use of the observatories, we argue that some extensions of the existing works are required. In this paper, we thus propose an extension of existing vocabularies to achieve this goal. Our contribution is illustrated on the real case of the Lebanese-French O-LiFE environmental observatory.
