Open Geospatial Data And Services Publication On The Cloud: The INGEOCLOUDS Open Source Approach


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Open Geospatial Data And Services Publication On The Cloud: The INGEOCLOUDS Open Source Approach
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Baurens, Benoit (AKKA Techologies)
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FOSS4G, Open Source Geospatial Foundation (OSGeo)
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The cloud can be used as an infrastructure, as a platform or as a (desktop) software replacement according to the three different paradigms that it supports (IaaS, PaaS and SaaS). On the other hand at the moment more and more applications are using the cloud as their backend since it promises (unlimited) scalability and elasticity in terms of storage and computing power. In the open source geospatial world a lot of effort has been invested in developing excellent software that can be used to store, manage, visualize and publish on the web geospatial data and services. But when it comes to the cloud those offerings are not always readily available since the software, we all build, does not scale in a way that can take advantage of the cloud. In that respect we worked towards providing scalability and elasticity capabilities for the storage, querying and visualization of geospatial data based on existing open source solutions like the Mapserver, PostGIS, Apache and so on. We also worked on the lower part of the software stack so that we can build an elastic file system for storing geospatial data. So we are in the process of offering a fully open source solution that can take advantage of the cloud and its properties. Moreover we have coupled this solution with support for publishing anyone’s geospatial data as Linked Open Data so that they can be readily combined with other data on the web. In that respect we are using an open source SPARQL endpoint (Virtuoso) that allows us to store geospatially enabled information given that a suitable conceptual model will be provided described in RDF. Thus we allow for seamless integration of published data on the semantic web and we provide the necessary services for integrating this kind of offering in other applications in the future. Additionally we identified an emerging need to allow end users to publish their own data and create dynamically their own customized services on the cloud. Thus we exploit cloud’s “unlimited” storage capabilities to allow end users to publish their own data (as long as it is cost effective, too), combine them with existing data and create their own WMS/WFS customized services and publish them on the web. This has a great value-added for the users since they can actually publish their own maps. Finally, we demonstrate the capabilities of our technical solution by building and offering a set of advanced geophysical services through the platform. These services include a service for creating shakemaps (maps the visualize the effects caused by an earthquake to the environment), predicting landslides (providing maps assessing the possibility of landslides) and handling pollution information in ground waters. In conclusion, we offer an open source software stack that is based on existing open source software and extends it as needed in order to take to the most possible advantage of the properties of the cloud. We have tried to keep the software agnostic for the specific cloud and its capabilities. The work is carried out within the INGEOCLOUDS FP7 Project, co-funded by the EU, and with the participation of companies (AKKA technologies, France), research centers (CNR, Italy and FORTH, Greece) and data providers like geological surveys (GEUS, Denmark; GEO-ZS, Slovenia; BRGM, France and EKBAA, Greece) and earthquake research institutes (EPPO, Greece).
Computer animation Web service Decision theory Open source Point cloud Division (mathematics) Open set
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