Topic type
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Target Type
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Case Studies: Relate your experiences.
Visualization: effective presentation of information.
Collaboration: data collection, data sharing, open standards.
New data: handling new data models, for example 3D & temporal data, or big data.
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Technical / Developer
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Additional Presenters
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Name
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Chris Johnson
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Organisation
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CERC
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Email
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chris.johnson@cerc.co.uk
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Name
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Uli MŸller
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Organisation
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geOps
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Email
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uli.mueller@geops.de
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Paper Title
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Cartaro - the Geospatial CMS
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I can give a practical demo
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yes
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Paper Abstract (short)
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A New Kid on the Block: Bringing together Open Source Geospatial and Content Mangement Software
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Paper Abstract (long)
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Cartaro is a new web mapping platform that makes the power of some of the best open source geospatial components available in a content management system (CMS). Cartaro allows to set-up and run small websites or complex web applications with maps and geodata. It is also suitable for geoportals and spatial data infrastructures whenever there is the need to get everything up and running without much individual programming. The geospatial software stack used in Cartaro consists of PostGIS, GeoServer, GeoWebCache and OpenLayers. The whole stack is managed from within the CMS Drupal. The geospatial components bring professional aspects of geodata management into the CMS. This is namely the ability to persist data as true geometries, thus allowing for complex and fast queries and analyses. It does also mean supporting a whole range of data formats and the most relevant OGC standards. For the latter Cartaro can extend the handling of user roles and permissions, which already exists in Drupal, to define fully granular read and write permissions for the web services, too. In the presentation we will first explain our basic motivation behind Cartaro: that is bringing geospatial functionality to the huge community of CMS developers and users. This community, which is of course much larger than the classical FOSS4G community, has a great potential to make more and better use of geodata than it was possible with most existing tools. We will then demonstrate how far the integration with the CMS reaches and present the Drupal user interface that allows to configure most features of Cartaro. We will show how to create, edit and map geospatial content with Cartaro and we will demonstrate the publication of this content as an OGC web service. We will also go into some details concerning the architecture of Cartaro and explain how we tackled specific problems. A glimpse of the some use cases will demonstrate the real potential of Cartaro. It will also show how the focus and functionality of a Cartaro based application can be extended with the installation of any of the Drupal modules that exist for almost every task one could imagine. The presentation will close with the future perspectives for Cartaro. From a technical point of view this includes the roadmap for the next months. But it also includes a discussion of our ideas about Cartaro's role as self-supporting bridge between the geo and not-so-geo world of open source software.
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Topic type
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Target Type
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Development: new developments in products.
Collaboration: data collection, data sharing, open standards.
Integration with Non-GIS Open Source Software
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Manager
Technical / Developer
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Name
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Javier de la Torre
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Organisation
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CartoDB
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Email
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jatorre@cartodb.com
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Paper Title
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CartoDB 2.1
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I can give a practical demo
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yes
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Paper Abstract (short)
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It has been an exciting year of development for CartoDB and itÕs technologies, here we will report those updated and the lessons we have learned in the projectÕs development.
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Paper Abstract (long)
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CartoDB is an open-source technology stack that offers mapping services for dynamic data, APIs for application development, and data management tools. CartoDB as a service wraps all those features into a secure, scalable, and powerful cloud based tool to drive geospatial applications on the web. CartoDB just passed the one-year mark since it's first public release and will soon close in on two years since the initial beta release. Over that time, CartoDB has grown and improved in many ways, we would like to share some of those advances and the lessons we have learned with you now. A primary area of development has been the speed and reliability of the dynamic tile service. Dynamic tiles, map tiles that change to reflect modifications in underlying data, are a key feature that sets CartoDB apart from other available services. To handle this feat, CartoDB uses a combination of database optimization, query optimization, and multi-tiered caching. For database optimization, CartoDB uses predictable schemas and automated geometry reprojection for web-based maps, queries are limited and tuned for tile-based visualizations, and caching happens from the database to the cloud to help deliver the fastest dynamic tiles available. CartoDB is also innovating on the web through the use of SQL everywhere. SQL everywhere means just what it says, SQL is used from the server, to CartoDB's administrative consoles, all the way to the client side JavaScript library. Exposing the full power of SQL, and geospatially enabled SQL through PostGIS, is helping to give our users access to the most powerful tool for building web-GIS tools and spatially enabled applications. These features and many more have made for an exciting pace of development since CartoDB's initial release. We will report here on a range of advances made in the software that are relevant to users and of interest to the open-source community.
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Topic type
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Target Type
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Case Studies: Relate your experiences.
Business Cases: building the economic case.
Development: new developments in products.
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People new to open source geospatial
Manager
End User
Technical / Developer
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Name
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Ian Edwards
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Organisation
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Met Office
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Email
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ian.edwards@metoffice.gov.uk
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Paper Title
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Cartopy and Iris: Open Source Python Tools for Analysis and Visualisation
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I can give a practical demo
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yes
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Paper Abstract (short)
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Cartopy is a new python mapping library for the transformation and visualisation of geospatial vector and raster data. Iris implements a generalised n-dimensional gridded data model, enabling powerful analysis of 3D, temporal and big data.
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Paper Abstract (long)
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The Python programming language has emerged as the ÒLanguage of GISÓ, providing a powerful geospatial and scientific development environment whilst also being ideal for rapid prototyping and a good introductory language for first-time programmers. The open source environment is strategically important to the Met Office as we strive to meet the increasing need to collaborate freely and openly in academic and commercial partnerships. The Met Office employs a team of software engineers to develop, simplify and improve its scientific capabilities by contributing to the the open source community. The focus of much of this effort has been on two new open source packages. Cartopy [1] is a new mapping library that builds on PythonÕs matplotlib module. Cartopy exposes an intuitive interface for the transformation and visualisation of geospatial vector and raster data. Iris [2], implements a generalised n-dimensional gridded data model to isolate analysis and visualisation code from file format specifics. The Iris data model is a result of close collaboration with the CF Data Model community. In addition to common GIS file formats, it also has read/write support for a variety of scientific file formats including NetCDF. This talk will give details of the Met Office's involvement in the open source community, including demonstrations of Iris and Cartopy and outline areas of future development. [1] - http://scitools.org.uk/cartopy/docs/latest/ [2] - http://scitools.org.uk/iris/docs/latest/
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Topic type
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Target Type
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Case Studies: Relate your experiences.
Business Cases: building the economic case.
Visualization: effective presentation of information.
Collaboration: data collection, data sharing, open standards.
New data: handling new data models, for example 3D & temporal data, or big data.
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End User
Technical / Developer
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Name
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Marcos Hermida Mera
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Organisation
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Unidata/UCAR
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Email
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mhermida@unidata.ucar.edu
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Paper Title
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CDM & TDS data server: Earth & Ocean Sciences meet GIS
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I can give a practical demo
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yes
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Paper Abstract (short)
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The Common Data Model and the THREDDS Data Server provide metadata and data access for scientific datasets using several remote data access protocols (OpeNDAP, NetCDF Subset Service, WMS, WCS) and have become an essential tool for interdisciplinary data sharing within the various domains of geosciences.
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Paper Abstract (long)
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Different geoscience disciplines have developed sophisticated domain-specific cyber infrastructures for data storage, manipulation, and visualization. NetCDF, HDF, and GRIB are multi-dimensional array-based data formats widely used in meteorology and oceanography. However, these formats are not fully compatible with the visualization and manipulation tools supported by Geographic Information Systems (GIS), which caters to the discrete vector features and 2D raster formats commonly used in the geography, hydrology, and cartography. By providing a higher level of abstraction and enabling spatial, rather than indexed, data access, the Unidata Common Data Model (CDM) facilitates integration of NetCDF, HDF, and GRIB data into GIS tools, fostering interdisciplinary communication. The THREDDS Data Server (TDS) utilizes the CDM to work efficiently with large, dynamic collections of observational and model data. The TDS organizes these collections into unified, logical datasets, simplifying their access and dissemination. TDS datasets are exposed via the WMS and WCS Open Geospatial Consortium specifications, with support for time and elevation standard dimensions. Alternatively, TDS datasets are accessible through specialized web services that provide subsetting capabilities. The NetCDF Subset Service allows for spatial subsetting, while OpenDAP subsets by index. Finally, metadata discovery systems such as Geoportal and GI-CAT harvest TDS catalog metadata. The TDS ncISO service also serves catalog metadata directly as ISO documents, enabling text searches and exposing a CSW interface on TDS instances through these discovery systems. The CDM & TDS are OpenSource projects (https://github.com/Unidata/thredds) with strong community support. Members have contributed key features, including the ncISO and WMS implementations. Moreover, many interdisciplinary Web-GIS applications have already been successfully developed combining TDS web services with resources from other spatial data infrastructures. Coupled with Unidata's governing committees, the projects provide a unique framework that establishes quality standards and ensures that development meets community needs.
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Topic type
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Target Type
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Case Studies: Relate your experiences.
Collaboration: data collection, data sharing, open standards.
New data: handling new data models, for example 3D & temporal data, or big data.
|
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People new to open source geospatial
End User
Technical / Developer
Scientist
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Additional Presenters
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Name
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Lansing Madry
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Organisation
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Unidata
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Email
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madry@unidata.ucar.edu
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|
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Name
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Ethan Davis
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Organisation
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Unidata
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Email
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edavis@unidata.ucar.edu
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Name
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Andrew Ross
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Organisation
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LocationTech
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Email
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andrew.ross@eclipse.org
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Paper Abstract (short)
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An architectural view of application data model and data storage technologies
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Paper Abstract (long)
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So you're going to build the next killer app? That's awesome! Flexible hosting solutions from Google, Amazon, Rackspace, and many others make it really easy to get started. You can reuse powerful open source libraries and services to focus your efforts on developing something unique. Ideally your technology choices support your application's architecture and your business model. Ideally you can scale up or out as your needs change. There are so many good technology choices, so which one(s) do you pick? This presentation focuses on storage technologies. It is a mixed database and architecture talk. We will examine some of the popular storage and processing technologies such as PostgreSQL, MongoDB, SQLite, Hadoop, and others. We'll play match maker and try to pair up the model each technology is ideal for. Do you need a small footprint for mobile devices? Do you low latency for web or mobile applications? Do you need a high degree of redundancy? What proportion of the time does your application read vs. write data? Do you need to optimize CPU for processing large data sets? Do you need to minimize bandwidth or disk space? What about support for spatial data types and spatial functions? After attending this talk, you should have a good idea of some of the important factors in choosing your data storage technology and a rough sense of some of the great open source options available to you.
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Topic type
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Target Type
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Benchmarks: Comparisons between packages.
New data: handling new data models, for example 3D & temporal data, or big data.
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People new to open source geospatial
Manager
End User
Technical / Developer
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