Open source Geospatial Business Intelligence in action with GeoMondrian and S...Thierry Badard
This document introduces GeoMondrian and SOLAPLayers, open source geospatial business intelligence tools. GeoMondrian is a spatially-enabled version of the Pentaho Mondrian OLAP server that integrates spatial data and analysis capabilities into OLAP data cubes. SOLAPLayers is a lightweight cartographic component that enables interactive map-based exploration of geospatial data cubes from servers like GeoMondrian. The document discusses the architecture and capabilities of both tools, demonstrates them, and outlines the roadmap for future development including more advanced SOLAPLayers components for creating geospatial dashboards.
The document discusses Mondrian, an open source OLAP server written in Java. It can be used to develop a trajectory data warehouse and interactively analyze large datasets stored in SQL databases without writing SQL. Mondrian uses MDX and XML for querying and cube definition. It provides an OLAP view of relational data and enables fast, on-line analytical processing through aggregation and caching. GeoMondrian extends it with spatial/GIS data types and functions for geographical analysis.
Geospatial Business Intelligence made easy with GeoMondrian & SOLAPLayersThierry Badard
Slides of the presentation about GeoMondrian and SOLAPLayers I gave during the 1st rendez-vous OSGeo-Quebec (http://rendez-vous-osgeo-qc.org/2010) at Saguenay, Quebec, Canada on June 15-16, 2010.
Spatially enabled open source BI (GeoBI) with GeoKettle, GeoMondrian & SOLAPL...Thierry Badard
This document discusses spatially enabled open source business intelligence (GeoBI) tools including GeoKettle, GeoMondrian, and SOLAPLayers. GeoKettle adds spatial capabilities to Pentaho Data Integration. GeoMondrian does the same for Pentaho Analysis Services (Mondrian) by integrating spatial objects into OLAP data cubes. SOLAPLayers provides a lightweight framework for building interactive geospatial dashboards using these tools. The document demonstrates the capabilities and architecture of these projects.
Open Source Geospatial Business Intelligence (GeoBI): Definition, architectur...Thierry Badard
The document discusses geospatial business intelligence (GeoBI), including its definition, architectures, open source solutions, and outlook. Specifically, it defines GeoBI as bringing maps and geospatial analysis tools into BI systems to fully analyze spatial dimensions in corporate data. It presents open source GeoBI solutions like GeoKettle and GeoMondrian, describing their roles in extracting, transforming, loading, and analyzing geospatial data in BI systems.
GeoKettle: A powerful open source spatial ETL toolThierry Badard
GeoKettle is an open source spatial ETL tool that is part of a geospatial business intelligence software stack. It is based on Pentaho Data Integration and provides consistent integration of spatial data types and capabilities. GeoKettle allows automated extraction, transformation, and loading of data across various sources into data warehouses. It supports spatial operations and can be deployed in cloud environments for scalable geospatial data processing.
GeoKettle, GeoMondrian et Spatialytics : une suite open source de GeoBIACSG Section Montréal
Avec la disponibilité croissante de données très diverses, géospatiales ou non, liés aux efforts et argents investis dans la collection et mise en place de nombreux référentiels ou bases de données tant dans les entreprises que dans les institutions gouvernementales, se fait jour le besoin de plus en plus important et pressant de croiser ces différentes sources de données afin d'appuyer la prise de décision et ceci dans des domaines très variés : banque, assurance, environnement, infrastructures, santé, changements climatiques, ... Les technologies de Business Intelligence (Intelligence d'affaires) permettent le croisement de telles masses de données et leur exploration interactive et rapide afin de dégager des tendances ou mettre en lumière différents phénomènes et ainsi prendre en pleine connaissance de cause des décisions éclairées afin de contrer les effets, corriger ou améliorer la situation observée. La pile logicielle open source disponible et supportée à Spatialytics.org a été développée par l’équipe de recherche GeoSOA mené par le Dr. Thierry Badard de l’Université Laval. La suite Geo-BI est constituée de GeoKettle (un outil ETL spatial), GeoMondrian (un serveur Spatial OLAP ou SOLAP) et SOLAPLayers (un composant cartographique permettant la navigation dans les cubes de données géo-décisionnelles) et permet la pleine prise en compte de la composante spatiale dans l'analyse de ces grandes masses d'information. Il devient ainsi possible d'observer certaines tendances, et ceci à différents niveaux de détails et différentes époques, par le biais de cartes qui viennent s'ajouter aux moyens usuels de représentation des données de synthèse que sont les tableaux croisés et les graphiques dans les outils décisionnels (tableau de bord, outil de reporting, ...). L'estimation de la répartition spatiale de tels ou tels phénomènes ou de son évolution spatiotemporelle est rendue possible et facile. Cette présentation se veut donc une vitrine technologique dans laquelle seront présentés les différents outils géo-décisionnels disponibles à Spatialytics.org , des exemples et démonstrations permettront d'en comprendre le fonctionnement, la portée et pertinence.
Open Source Geospatial Business Intelligence (Geo-BI)Thierry Badard
The document discusses geospatial business intelligence (Geo-BI). It defines BI as using data analysis to understand business operations and support decision making. Geo-BI adds spatial analysis and maps to allow exploration of spatial relationships in data. About 80% of corporate data has a spatial component, and representing some phenomena on maps can better aid interpretation and decisions. The document introduces open source Geo-BI software from Spatialytics, including Pentaho tools for ETL, OLAP, and reporting integrated with geospatial capabilities.
Bringing Geospatial Business Intelligenceto the Enterprisemkarren
KOREM provides geospatial business intelligence (location intelligence) solutions to help organizations understand how location impacts business operations. They offer consulting, data management, software integration, and training services. Their solutions integrate spatial data and analysis with existing business intelligence tools to provide strategic, operational, and analytic insights. KOREM works across industries with both public and private sector customers to develop customized geospatial business intelligence applications.
State of GeoServer provides an update on our community and reviews the new and noteworthy features for the Project. The community has a lot to cover in 2.12 and the recently released 2.13.
Each release provides exciting new features. This talk covers our work on supporting Java 9 and diverse improvements across GeoServer.
Attend this talk for a cheerful update on what is happening with this popular OSGeo project. Whether you are an expert user, a developer, or simply curious what GeoServer can do for you.
Giving MongoDB a Way to Play with the GIS CommunityMongoDB
The Geographic Information System (GIS), industry is booming, especially with the continued reliance on online maps and the rise of location-aware mobile devices. GIS tech can be one of the key players in the mobile internet, big data, and the internet of things, and is an essential tool for the next generation of the global IT industry.
Yet, the GIS community is not prepared. With all the data available, GIS experts lack an off-the-shelf solutions to manage the growing volume of spatial data. Relational spatial databases (RSDB) were the leader in this field for decades, but RSDBs have failed to innovate to handle massive volumes of data coming in at high velocity.
Fortunately, MongoDB a useful tool for this challenge, but needs some tooling to create a connector to the GIS tech ecosystem. In order to bridge the gap, we built a pipeline to comply with the architecture of the Geospatial Data Abstraction Library (GDAL), so that MongoDB can work with most of popular GIS tools such as OpenLayers, Mapserver, GeoServer, QGIS, ArcGIS and others with ease. In this talk, I'll go through this pipeline tool and showcase some examples of how you can use this in your next application.
This document provides an overview of geoprocessing, which allows users to define, manage, and analyze spatial information to support decision making. It discusses how geoprocessing works in ArcGIS through tools, models, scripts, and toolboxes. Specific geoprocessing tasks like overlay, proximity, surfaces, and statistics are examined. The document also covers data sources, running tools, and settings. It provides examples of creating a model and script to automate repetitive geoprocessing work.
The document discusses the roles of Google and the Open Geospatial Consortium (OGC) in geospatial information systems and web mapping. It provides an overview of Google's geospatial technologies like Google Maps, Google Earth, and KML. It then introduces the OGC, its standards including GML and Web Map Service (WMS), and how these standards enable interoperability between different systems. The document argues that while Google is useful for many applications, the OGC is still needed for applications involving custom basemaps, connecting desktop GIS to web services, mixing data from different sources, or creating complex geospatial models.
New tools are being developed by Czech Living Lab WirelessInfo, which allow users to easily publish their data and metadata as part of a Spatial Data Infrastructure (SDI). The paper describes the design of a Technological Infrastructure on the basis of ISO and OGC Standards and also the implementation of a prototype and first experiences. The solution is designed in distributed system form, which provides the connection to metadata about spatial data and services. This solution tests the principle of catalogue services at both national and international level which could be used in the UN SDI context. A catalogue portal is one of the independent components of GeoHosting complex system for raster and vector spatial data sharing. The catalogue portal provides data source searching on the basis of their metadata records through structure queries. The portal also contains edit functionality for new metadata records creating or editing. The metadata catalogue system corresponds to ISO 19115/19119/19139 standards [1], [2], [3], [4] and provides for cascade searching on the other standardized catalogue systems. The difference is, there exist different other initiatives offering publishing of own content like Google technology or OpenStreet Map, that GeoHosting is based fully on INSPIRE European standards and support establishing of network of distributed servers.
ESRI's ArcGIS software allows CAD data to be directly imported and used within the GIS platform without conversion. CAD data is represented as feature classes within ArcGIS and maintains geometry and attributes. Tools exist for exporting GIS data back to CAD formats while maintaining relationships. The Mapping Specification for DWG standard developed by ESRI helps improve interoperability between CAD and GIS data.
This document describes the DA_MAP project, which aims to create a desktop application for METOC (meteorology and oceanography) data analysis and modeling. The application will integrate data access, visualization, and analysis tools to allow users to more easily find, access, and analyze diverse METOC data. Key aspects of the project include using Java and XML technologies, providing search and query of metadata stored in XML format, and including interactive visualization and analysis modules. Screenshots show examples of the data registration, search and query, and analysis modules with features like model output overlays, time series plots, and difference maps.
Spark SQL allows users to perform relational operations on Spark's RDDs using a DataFrame API. It addresses challenges in existing systems like limited optimization and data sources by providing a DataFrame API that can query both external data and RDDs. Spark SQL leverages a highly extensible optimizer called Catalyst to optimize logical query plans into efficient physical query plans using features of Scala. It has been part of the Spark core distribution since version 1.0 in 2014.
The document provides an introduction to the ArcGIS Pipeline Data Model (APDM), which is a standardized data model for storing pipeline geospatial data. It describes the core components of a geographic information system (GIS) and how the APDM implements these components using ESRI's geodatabase tools. This includes discussions of feature classes, object classes, attributes, relationships, and how the pipeline data is structured and related within the APDM schema.
Generating Pipeline Alignment Sheets Using FMESafe Software
Presented by Jerrod Stutzman & Kyle Brock of Devon Energy
Abstract: The standard workflow for converting pipeline survey data into alignment sheets is a tedious and repetitive process. Using Data Interoperability (FME) via ArcGIS Server geoprocessing, we can automate the entire process, saving many man hours while also retiring a 3rd party application.
This presentation will dive into a development team’s use case for choosing MongoDB as their spatially enabled NoSQL solution. The talk will also cover how the integration of GeoServer can expand the accessibility of your data. GeoServer is the open source implementation of Open Geospatial Consortium (OGC) standards and a core component of the Geospatial Web.
Graph Databases, The Web of Data Storage EnginesPere Urbón-Bayes
Graph databases are a type of database that uses graph structures with nodes, edges and properties to represent and store information. They are distinct from specialized graph databases like triple stores and network databases. Some key graph database vendors include Neo4j, InfiniteGraph and OrientDB. Graph databases are well suited for applications that involve relationships, like recommendations, social networks, knowledge graphs and location-based services.
The document discusses the new features and improvements in QGIS 2.0, including enhanced atlas/mapbook generation, composer improvements, new symbology options, an improved attribute table, integration of SEXTANTE processing capabilities, and a redesigned user interface. It also provides an overview of adoption of QGIS, the current release plan, and a call for help finding and fixing bugs prior to the June public release.
Taming the Survey Data "Tower of Babel"mercatorlem
The document discusses managing diverse survey data from multiple sources in AutoCAD. It recommends using field codes and layers to organize data by type and source. Direct survey measurements are given prominent styles, while indirect data like scans use subdued styles. The goal is to make the nature and quality of data self-evident in CAD files to avoid mixing hazards and ensure clarity for clients.
How The Weather Company Uses Apache Spark to Serve Weather Data Fast at Low CostDatabricks
The Weather Company (TWC) collects weather data across the globe at the rate of 34 million records per hour, and the TWC History on Demand application serves that historical weather data to users via an API, averaging 600,000 requests per day. Users are increasingly consuming large quantities of historical data to train analytics models, and require efficient asynchronous APIs in addition to existing synchronous ones which use ElasticSearch. We present our architecture for asynchronous data retrieval and explain how we use Spark together with leading edge technologies to achieve an order of magnitude cost reduction while at the same time boosting performance by several orders of magnitude and tripling weather data coverage from land only to global.
This document provides an overview of graph databases, including their basic components and structure. It discusses graph database vendors like Neo4j and OrientDB and how they are implemented. Examples of use cases for graph databases include social network analysis, recommendations, knowledge graphs, and routing. The document also mentions graph processing frameworks and APIs that can interact with graph databases.
The document discusses various topics related to mapping, GIS and geolocating data in Java using open source software. It covers GIS basics like layers, tiles, features and geometries. It also discusses data formats, database options, Java libraries for GIS like JTS and GeoTools, and Java servers and frameworks like GeoServer and Geomajas.
OpenLayers (OL) is an open-source JavaScript library for displaying map data in web applications. It can display data from various sources like GeoJSON, WMS, WFS and supports interactions like querying, filtering and overlaying layers. OL has evolved over the years with new versions introducing features like improved projections support, 3D rendering and compatibility with modern standards. While Leaflet is better for simpler uses due to its large plugin ecosystem, OL is more powerful and flexible for complex GIS applications and supports advanced OGC protocols out of the box.
Bringing Geospatial Business Intelligenceto the Enterprisemkarren
KOREM provides geospatial business intelligence (location intelligence) solutions to help organizations understand how location impacts business operations. They offer consulting, data management, software integration, and training services. Their solutions integrate spatial data and analysis with existing business intelligence tools to provide strategic, operational, and analytic insights. KOREM works across industries with both public and private sector customers to develop customized geospatial business intelligence applications.
State of GeoServer provides an update on our community and reviews the new and noteworthy features for the Project. The community has a lot to cover in 2.12 and the recently released 2.13.
Each release provides exciting new features. This talk covers our work on supporting Java 9 and diverse improvements across GeoServer.
Attend this talk for a cheerful update on what is happening with this popular OSGeo project. Whether you are an expert user, a developer, or simply curious what GeoServer can do for you.
Giving MongoDB a Way to Play with the GIS CommunityMongoDB
The Geographic Information System (GIS), industry is booming, especially with the continued reliance on online maps and the rise of location-aware mobile devices. GIS tech can be one of the key players in the mobile internet, big data, and the internet of things, and is an essential tool for the next generation of the global IT industry.
Yet, the GIS community is not prepared. With all the data available, GIS experts lack an off-the-shelf solutions to manage the growing volume of spatial data. Relational spatial databases (RSDB) were the leader in this field for decades, but RSDBs have failed to innovate to handle massive volumes of data coming in at high velocity.
Fortunately, MongoDB a useful tool for this challenge, but needs some tooling to create a connector to the GIS tech ecosystem. In order to bridge the gap, we built a pipeline to comply with the architecture of the Geospatial Data Abstraction Library (GDAL), so that MongoDB can work with most of popular GIS tools such as OpenLayers, Mapserver, GeoServer, QGIS, ArcGIS and others with ease. In this talk, I'll go through this pipeline tool and showcase some examples of how you can use this in your next application.
This document provides an overview of geoprocessing, which allows users to define, manage, and analyze spatial information to support decision making. It discusses how geoprocessing works in ArcGIS through tools, models, scripts, and toolboxes. Specific geoprocessing tasks like overlay, proximity, surfaces, and statistics are examined. The document also covers data sources, running tools, and settings. It provides examples of creating a model and script to automate repetitive geoprocessing work.
The document discusses the roles of Google and the Open Geospatial Consortium (OGC) in geospatial information systems and web mapping. It provides an overview of Google's geospatial technologies like Google Maps, Google Earth, and KML. It then introduces the OGC, its standards including GML and Web Map Service (WMS), and how these standards enable interoperability between different systems. The document argues that while Google is useful for many applications, the OGC is still needed for applications involving custom basemaps, connecting desktop GIS to web services, mixing data from different sources, or creating complex geospatial models.
New tools are being developed by Czech Living Lab WirelessInfo, which allow users to easily publish their data and metadata as part of a Spatial Data Infrastructure (SDI). The paper describes the design of a Technological Infrastructure on the basis of ISO and OGC Standards and also the implementation of a prototype and first experiences. The solution is designed in distributed system form, which provides the connection to metadata about spatial data and services. This solution tests the principle of catalogue services at both national and international level which could be used in the UN SDI context. A catalogue portal is one of the independent components of GeoHosting complex system for raster and vector spatial data sharing. The catalogue portal provides data source searching on the basis of their metadata records through structure queries. The portal also contains edit functionality for new metadata records creating or editing. The metadata catalogue system corresponds to ISO 19115/19119/19139 standards [1], [2], [3], [4] and provides for cascade searching on the other standardized catalogue systems. The difference is, there exist different other initiatives offering publishing of own content like Google technology or OpenStreet Map, that GeoHosting is based fully on INSPIRE European standards and support establishing of network of distributed servers.
ESRI's ArcGIS software allows CAD data to be directly imported and used within the GIS platform without conversion. CAD data is represented as feature classes within ArcGIS and maintains geometry and attributes. Tools exist for exporting GIS data back to CAD formats while maintaining relationships. The Mapping Specification for DWG standard developed by ESRI helps improve interoperability between CAD and GIS data.
This document describes the DA_MAP project, which aims to create a desktop application for METOC (meteorology and oceanography) data analysis and modeling. The application will integrate data access, visualization, and analysis tools to allow users to more easily find, access, and analyze diverse METOC data. Key aspects of the project include using Java and XML technologies, providing search and query of metadata stored in XML format, and including interactive visualization and analysis modules. Screenshots show examples of the data registration, search and query, and analysis modules with features like model output overlays, time series plots, and difference maps.
Spark SQL allows users to perform relational operations on Spark's RDDs using a DataFrame API. It addresses challenges in existing systems like limited optimization and data sources by providing a DataFrame API that can query both external data and RDDs. Spark SQL leverages a highly extensible optimizer called Catalyst to optimize logical query plans into efficient physical query plans using features of Scala. It has been part of the Spark core distribution since version 1.0 in 2014.
The document provides an introduction to the ArcGIS Pipeline Data Model (APDM), which is a standardized data model for storing pipeline geospatial data. It describes the core components of a geographic information system (GIS) and how the APDM implements these components using ESRI's geodatabase tools. This includes discussions of feature classes, object classes, attributes, relationships, and how the pipeline data is structured and related within the APDM schema.
Generating Pipeline Alignment Sheets Using FMESafe Software
Presented by Jerrod Stutzman & Kyle Brock of Devon Energy
Abstract: The standard workflow for converting pipeline survey data into alignment sheets is a tedious and repetitive process. Using Data Interoperability (FME) via ArcGIS Server geoprocessing, we can automate the entire process, saving many man hours while also retiring a 3rd party application.
This presentation will dive into a development team’s use case for choosing MongoDB as their spatially enabled NoSQL solution. The talk will also cover how the integration of GeoServer can expand the accessibility of your data. GeoServer is the open source implementation of Open Geospatial Consortium (OGC) standards and a core component of the Geospatial Web.
Graph Databases, The Web of Data Storage EnginesPere Urbón-Bayes
Graph databases are a type of database that uses graph structures with nodes, edges and properties to represent and store information. They are distinct from specialized graph databases like triple stores and network databases. Some key graph database vendors include Neo4j, InfiniteGraph and OrientDB. Graph databases are well suited for applications that involve relationships, like recommendations, social networks, knowledge graphs and location-based services.
The document discusses the new features and improvements in QGIS 2.0, including enhanced atlas/mapbook generation, composer improvements, new symbology options, an improved attribute table, integration of SEXTANTE processing capabilities, and a redesigned user interface. It also provides an overview of adoption of QGIS, the current release plan, and a call for help finding and fixing bugs prior to the June public release.
Taming the Survey Data "Tower of Babel"mercatorlem
The document discusses managing diverse survey data from multiple sources in AutoCAD. It recommends using field codes and layers to organize data by type and source. Direct survey measurements are given prominent styles, while indirect data like scans use subdued styles. The goal is to make the nature and quality of data self-evident in CAD files to avoid mixing hazards and ensure clarity for clients.
How The Weather Company Uses Apache Spark to Serve Weather Data Fast at Low CostDatabricks
The Weather Company (TWC) collects weather data across the globe at the rate of 34 million records per hour, and the TWC History on Demand application serves that historical weather data to users via an API, averaging 600,000 requests per day. Users are increasingly consuming large quantities of historical data to train analytics models, and require efficient asynchronous APIs in addition to existing synchronous ones which use ElasticSearch. We present our architecture for asynchronous data retrieval and explain how we use Spark together with leading edge technologies to achieve an order of magnitude cost reduction while at the same time boosting performance by several orders of magnitude and tripling weather data coverage from land only to global.
This document provides an overview of graph databases, including their basic components and structure. It discusses graph database vendors like Neo4j and OrientDB and how they are implemented. Examples of use cases for graph databases include social network analysis, recommendations, knowledge graphs, and routing. The document also mentions graph processing frameworks and APIs that can interact with graph databases.
The document discusses various topics related to mapping, GIS and geolocating data in Java using open source software. It covers GIS basics like layers, tiles, features and geometries. It also discusses data formats, database options, Java libraries for GIS like JTS and GeoTools, and Java servers and frameworks like GeoServer and Geomajas.
OpenLayers (OL) is an open-source JavaScript library for displaying map data in web applications. It can display data from various sources like GeoJSON, WMS, WFS and supports interactions like querying, filtering and overlaying layers. OL has evolved over the years with new versions introducing features like improved projections support, 3D rendering and compatibility with modern standards. While Leaflet is better for simpler uses due to its large plugin ecosystem, OL is more powerful and flexible for complex GIS applications and supports advanced OGC protocols out of the box.
The document provides an overview of open source GIS software and formats. It discusses what open source software is, common open source licenses, where to find open source GIS software, how to evaluate software quality, and examples of popular open source desktop and web-based GIS programs, databases, data formats, and programming languages. Key open source GIS software mentioned includes QGIS, GRASS, PostGIS, MapServer, and OpenLayers. Common data formats discussed are shapefiles, GeoJSON, KML and GPS eXchange format.
MapStore Create, save and share maps and mashups @ GRASS-GFOSS 2013GeoSolutions
MapStore is an open source application created by GeoSolutions to allow users to create, save, and share maps and mashups. It provides tools for map creation, browsing existing maps, and sharing maps. MapStore has a modular architecture built on open source standards and libraries. It includes components for map management, composition, viewing, and interacting with metadata catalogs. GeoSolutions provides commercial support and consulting for MapStore and other open source geospatial projects like GeoServer and GeoNetwork.
Leo Hsu and Regina Obe
We'll demonstrate integrating PostGIS in both PHP and ASP.NET applications.
We'll demonstrate using the new PostGIS 1.5 geography offering to extend existing web applications with proximity analysis.
More advanced use to display maps and stats using OpenLayers, WMS/WFS services and roll your own WFS like service using the PostGIS KML/GML/and or GeoJSON output functions.
LocationTech is an Eclipse Foundation industry working group for location aware technologies. This presentation introduces LocationTech, looks at what it means for our industry and the participating projects.
Libraries: JTS Topology Suite is the rocket science of GIS providing an implementation of Geometry. Mobile Map Tools provides a C++ foundation that is translated into Java and Javascript for maps on iOS, Andriod and WebGL. GeoMesa is a distributed key/value store based on Accumulo. Spatial4j integrates with JTS to provide Geometry on curved surface.
Process: GeoTrellis real-time distributed processing used scala, akka and spark. GeoJinni mixes spatial data/indexing with Hadoop.
Applications: GEOFF offers OpenLayers 3 as a SWT component. GeoGit distributed revision control for feature data. GeoScipt brings spatial data to Groovy, JavaScript, Python and Scala. uDig offers an eclipse based desktop GIS solution.
Attend this presentation if want to know what LocationTech is about, are interested in these projects or curious about what projects will be next.
GeoServer is open-source software that allows users to share and edit geospatial data by publishing it using open standards. It can access data from various sources like shapefiles, databases, and web feature services. GeoServer implements OGC standards like WFS and WCS and is used as a core component of geospatial web systems. Data from GeoServer can be added to the Open Development Cambodia website and accessed through their NewGenLib online library system, providing over 1,000 searchable and downloadable documents to users.
Open source based software ‘gxt’ mangosystemHaNJiN Lee
This document discusses GeoTools and GeoXTreme (GXT), open source geospatial toolkits. It provides information on:
- GeoTools, an open source GIS toolkit for developing standards compliant solutions. It supports various data formats and can compose maps.
- GXT, a commercial geoprocessing engine based on GeoTools that supports over 200 algorithms. GXT can be used for desktop or server applications.
- Examples of GXT applications including the KOPSS GIS engine, KOPSS data mart tools, and education/personal uses of GXT and uDig.
The User-participated Geospatial Web as Open PlatformChanny Yun
It's presentation of speaking in GIS International Seminar in Korea. You can refer to my full document in http://channy.creation.net/blog/data/channy/gis-seminar-2007.pdf
The document discusses Geomajas, an open source spatial application framework, and describes its core components including faces, plugins, and independent projects that provide functionality like caching, editing, geocoding, and layers for formats like WMS, KML, and OSM. It also explains Geomajas plug-ins that add capabilities for GWT, REST, printing, profiling, and more.
Spatiotemporal Raster Improvements in GeoServerGeoSolutions
GeoServer can now better support Earth observation and meteorological data through improvements to its WCS, WMS, and raster management capabilities. Key developments include implementing WCS 2.0 with extensions, adding support for NetCDF formats and custom dimensions, and extending the layer group concept in WMS to support requirements for Earth observation data like specifying default styles and layers for datasets. These changes improve GeoServer's ability to serve multidimensional geospatial raster data.
A talk about the OSGeo Live project; covering 43 projects that are available in a live DVD format (for you to run without installing). The project is much improved with OGC documentation and a description of many of the projects. New this year (thanks to some sponsorship) is quickstarts for several of the projects.
This document provides a proposed two month plan for transitioning from a GIS user to a web-GIS developer. The plan involves four main steps: 1) learning basic GIS concepts, 2) developing frontend web applications using HTML, CSS, JavaScript and the Leaflet mapping library, 3) implementing a map server using GeoServer to serve web map services, and 4) developing the backend using Python/Django and PostGIS. Common problems beginners face are outlined, such as trying to learn too many technologies at once. Resources are recommended for each step to help with the learning process.
Open source geospatial software provides code that is freely available to the public. It has several advantages, including keeping code in the public domain, high software quality through peer review, improved security, and interoperability. There are many open source projects for desktop GIS, web mapping servers, web mapping clients, spatial databases, and full open source geospatial web platforms. However, open source geospatial software still faces challenges of lack of commercial support, skilled personnel, and visibility compared to proprietary alternatives.
This document discusses large scale geo processing on Hadoop. It begins with an introduction to geo processing and spatial data. It then covers pre-processing spatial data, loading it into HDFS, and performing analysis using tools like Hive, ESRI, and Hadoop. Finally, it provides examples of use cases like network analysis at T-Mobile Austria and traffic prediction using GPS data.
This document discusses using NoSQL databases for geographic search and location-based services. It explains that geographic data is complex to store in SQL databases due to its multiple dimensions and large size. NoSQL databases provide alternatives like quadtrees and R-trees to index and search geographic data more efficiently. The document provides examples of geographic implementations in databases like MongoDB, Lucene, ElasticSearch, and Neo4j. It also gives examples of building point of interest search using technologies like SQL, Lucene, and Hibernate Search.
This document discusses the GeoServer ecosystem and integrations. GeoServer is an open source geospatial data server that can publish data using open standards. It is used by many organizations to serve maps and geospatial data on the web. The document highlights several integrations and uses of GeoServer including by government agencies to serve satellite imagery, cadastral data, and more. It also discusses commercial support from Boundless and how GeoServer can be deployed in cloud environments and integrated with other open source geospatial tools like GeoNetwork, GeoNode, and World Wind Server.
1) WebGIS architecture separates the geographic data storage and map generation on a remote server from the map interaction which occurs in the user's browser.
2) Setting up a WebGIS involves configuring the WebGIS architecture, producing and managing geographic data in a PostGIS database, configuring MapServer maps, and enabling map-user interaction through JavaScript libraries.
3) Key components for developing a WebGIS are PostGIS for geographic data storage, MapServer for generating maps from the database, and JavaScript libraries like OpenLayers and GeoExt for basic and complex user interaction with the maps in a web browser.
Introduction to the Application Security Verification Standard with attention to the requirements which caught my attention. Presentation from the JavaZone 2015 conference.
This document discusses converting between transfer objects and domain objects in Java applications. It recommends using a library like jTransfo to automate the conversion process. jTransfo uses annotations to map fields between transfer and domain objects, eliminating boilerplate conversion code. It supports features like type conversion, inheritance mapping, security authorization, and integration with frameworks like Spring and Hibernate. The document provides an example of how to easily convert between objects using jTransfo.
The document discusses simple runtime profiling techniques that provide limited overhead and feedback without additional resources. It describes profiling REST calls and JDBC calls using containers and aggregating data. Alternatives like XRebel and Metrics are also mentioned.
The document discusses the evolution of GIS data and potential solutions for managing changes and versions over time. It explores options like workflow solutions, long transactions, editing layers, timestamp-based versions, and revision-based versions. It also discusses using versioning standards from relational databases or implementing custom versioning approaches like timestamping or Revision Control System-style branches and tags. Integrating these solutions with tools like Hibernate and business process management is suggested.
Build with AI events are communityled, handson activities hosted by Google Developer Groups and Google Developer Groups on Campus across the world from February 1 to July 31 2025. These events aim to help developers acquire and apply Generative AI skills to build and integrate applications using the latest Google AI technologies, including AI Studio, the Gemini and Gemma family of models, and Vertex AI. This particular event series includes Thematic Hands on Workshop: Guided learning on specific AI tools or topics as well as a prequel to the Hackathon to foster innovation using Google AI tools.
The FS Technology Summit
Technology increasingly permeates every facet of the financial services sector, from personal banking to institutional investment to payments.
The conference will explore the transformative impact of technology on the modern FS enterprise, examining how it can be applied to drive practical business improvement and frontline customer impact.
The programme will contextualise the most prominent trends that are shaping the industry, from technical advancements in Cloud, AI, Blockchain and Payments, to the regulatory impact of Consumer Duty, SDR, DORA & NIS2.
The Summit will bring together senior leaders from across the sector, and is geared for shared learning, collaboration and high-level networking. The FS Technology Summit will be held as a sister event to our 12th annual Fintech Summit.
AI 3-in-1: Agents, RAG, and Local Models - Brent LasterAll Things Open
Presented at All Things Open RTP Meetup
Presented by Brent Laster - President & Lead Trainer, Tech Skills Transformations LLC
Talk Title: AI 3-in-1: Agents, RAG, and Local Models
Abstract:
Learning and understanding AI concepts is satisfying and rewarding, but the fun part is learning how to work with AI yourself. In this presentation, author, trainer, and experienced technologist Brent Laster will help you do both! We’ll explain why and how to run AI models locally, the basic ideas of agents and RAG, and show how to assemble a simple AI agent in Python that leverages RAG and uses a local model through Ollama.
No experience is needed on these technologies, although we do assume you do have a basic understanding of LLMs.
This will be a fast-paced, engaging mixture of presentations interspersed with code explanations and demos building up to the finished product – something you’ll be able to replicate yourself after the session!
Smart Investments Leveraging Agentic AI for Real Estate Success.pptxSeasia Infotech
Unlock real estate success with smart investments leveraging agentic AI. This presentation explores how Agentic AI drives smarter decisions, automates tasks, increases lead conversion, and enhances client retention empowering success in a fast-evolving market.
Web & Graphics Designing Training at Erginous Technologies in Rajpura offers practical, hands-on learning for students, graduates, and professionals aiming for a creative career. The 6-week and 6-month industrial training programs blend creativity with technical skills to prepare you for real-world opportunities in design.
The course covers Graphic Designing tools like Photoshop, Illustrator, and CorelDRAW, along with logo, banner, and branding design. In Web Designing, you’ll learn HTML5, CSS3, JavaScript basics, responsive design, Bootstrap, Figma, and Adobe XD.
Erginous emphasizes 100% practical training, live projects, portfolio building, expert guidance, certification, and placement support. Graduates can explore roles like Web Designer, Graphic Designer, UI/UX Designer, or Freelancer.
For more info, visit erginous.co.in , message us on Instagram at erginoustechnologies, or call directly at +91-89684-38190 . Start your journey toward a creative and successful design career today!
Autonomous Resource Optimization: How AI is Solving the Overprovisioning Problem
In this session, Suresh Mathew will explore how autonomous AI is revolutionizing cloud resource management for DevOps, SRE, and Platform Engineering teams.
Traditional cloud infrastructure typically suffers from significant overprovisioning—a "better safe than sorry" approach that leads to wasted resources and inflated costs. This presentation will demonstrate how AI-powered autonomous systems are eliminating this problem through continuous, real-time optimization.
Key topics include:
Why manual and rule-based optimization approaches fall short in dynamic cloud environments
How machine learning predicts workload patterns to right-size resources before they're needed
Real-world implementation strategies that don't compromise reliability or performance
Featured case study: Learn how Palo Alto Networks implemented autonomous resource optimization to save $3.5M in cloud costs while maintaining strict performance SLAs across their global security infrastructure.
Bio:
Suresh Mathew is the CEO and Founder of Sedai, an autonomous cloud management platform. Previously, as Sr. MTS Architect at PayPal, he built an AI/ML platform that autonomously resolved performance and availability issues—executing over 2 million remediations annually and becoming the only system trusted to operate independently during peak holiday traffic.
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...Safe Software
FME is renowned for its no-code data integration capabilities, but that doesn’t mean you have to abandon coding entirely. In fact, Python’s versatility can enhance FME workflows, enabling users to migrate data, automate tasks, and build custom solutions. Whether you’re looking to incorporate Python scripts or use ArcPy within FME, this webinar is for you!
Join us as we dive into the integration of Python with FME, exploring practical tips, demos, and the flexibility of Python across different FME versions. You’ll also learn how to manage SSL integration and tackle Python package installations using the command line.
During the hour, we’ll discuss:
-Top reasons for using Python within FME workflows
-Demos on integrating Python scripts and handling attributes
-Best practices for startup and shutdown scripts
-Using FME’s AI Assist to optimize your workflows
-Setting up FME Objects for external IDEs
Because when you need to code, the focus should be on results—not compatibility issues. Join us to master the art of combining Python and FME for powerful automation and data migration.
Viam product demo_ Deploying and scaling AI with hardware.pdfcamilalamoratta
Building AI-powered products that interact with the physical world often means navigating complex integration challenges, especially on resource-constrained devices.
You'll learn:
- How Viam's platform bridges the gap between AI, data, and physical devices
- A step-by-step walkthrough of computer vision running at the edge
- Practical approaches to common integration hurdles
- How teams are scaling hardware + software solutions together
Whether you're a developer, engineering manager, or product builder, this demo will show you a faster path to creating intelligent machines and systems.
Resources:
- Documentation: https://on.viam.com/docs
- Community: https://discord.com/invite/viam
- Hands-on: https://on.viam.com/codelabs
- Future Events: https://on.viam.com/updates-upcoming-events
- Request personalized demo: https://on.viam.com/request-demo
Challenges in Migrating Imperative Deep Learning Programs to Graph Execution:...Raffi Khatchadourian
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges---and resultant bugs---involved in writing reliable yet performant imperative DL code by studying 250 open-source projects, consisting of 19.7 MLOC, along with 470 and 446 manually examined code patches and bug reports, respectively. The results indicate that hybridization: (i) is prone to API misuse, (ii) can result in performance degradation---the opposite of its intention, and (iii) has limited application due to execution mode incompatibility. We put forth several recommendations, best practices, and anti-patterns for effectively hybridizing imperative DL code, potentially benefiting DL practitioners, API designers, tool developers, and educators.
Does Pornify Allow NSFW? Everything You Should KnowPornify CC
This document answers the question, "Does Pornify Allow NSFW?" by providing a detailed overview of the platform’s adult content policies, AI features, and comparison with other tools. It explains how Pornify supports NSFW image generation, highlights its role in the AI content space, and discusses responsible use.
fennec fox optimization algorithm for optimal solutionshallal2
Imagine you have a group of fennec foxes searching for the best spot to find food (the optimal solution to a problem). Each fox represents a possible solution and carries a unique "strategy" (set of parameters) to find food. These strategies are organized in a table (matrix X), where each row is a fox, and each column is a parameter they adjust, like digging depth or speed.
UiPath Agentic Automation: Community Developer OpportunitiesDianaGray10
Please join our UiPath Agentic: Community Developer session where we will review some of the opportunities that will be available this year for developers wanting to learn more about Agentic Automation.
Hybridize Functions: A Tool for Automatically Refactoring Imperative Deep Lea...Raffi Khatchadourian
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a refactoring tool that automatically determines when it is safe and potentially advantageous to migrate imperative DL code to graph execution and vice-versa.
GyrusAI - Broadcasting & Streaming Applications Driven by AI and MLGyrus AI
Gyrus AI: AI/ML for Broadcasting & Streaming
Gyrus is a Vision Al company developing Neural Network Accelerators and ready to deploy AI/ML Models for Video Processing and Video Analytics.
Our Solutions:
Intelligent Media Search
Semantic & contextual search for faster, smarter content discovery.
In-Scene Ad Placement
AI-powered ad insertion to maximize monetization and user experience.
Video Anonymization
Automatically masks sensitive content to ensure privacy compliance.
Vision Analytics
Real-time object detection and engagement tracking.
Why Gyrus AI?
We help media companies streamline operations, enhance media discovery, and stay competitive in the rapidly evolving broadcasting & streaming landscape.
🚀 Ready to Transform Your Media Workflow?
🔗 Visit Us: https://gyrus.ai/
📅 Book a Demo: https://gyrus.ai/contact
📝 Read More: https://gyrus.ai/blog/
🔗 Follow Us:
LinkedIn - https://www.linkedin.com/company/gyrusai/
Twitter/X - https://twitter.com/GyrusAI
YouTube - https://www.youtube.com/channel/UCk2GzLj6xp0A6Wqix1GWSkw
Facebook - https://www.facebook.com/GyrusAI
Mastering Testing in the Modern F&B Landscapemarketing943205
Dive into our presentation to explore the unique software testing challenges the Food and Beverage sector faces today. We’ll walk you through essential best practices for quality assurance and show you exactly how Qyrus, with our intelligent testing platform and innovative AlVerse, provides tailored solutions to help your F&B business master these challenges. Discover how you can ensure quality and innovate with confidence in this exciting digital era.
Transcript: Canadian book publishing: Insights from the latest salary survey ...BookNet Canada
Join us for a presentation in partnership with the Association of Canadian Publishers (ACP) as they share results from the recently conducted Canadian Book Publishing Industry Salary Survey. This comprehensive survey provides key insights into average salaries across departments, roles, and demographic metrics. Members of ACP’s Diversity and Inclusion Committee will join us to unpack what the findings mean in the context of justice, equity, diversity, and inclusion in the industry.
Results of the 2024 Canadian Book Publishing Industry Salary Survey: https://publishers.ca/wp-content/uploads/2025/04/ACP_Salary_Survey_FINAL-2.pdf
Link to presentation slides and transcript: https://bnctechforum.ca/sessions/canadian-book-publishing-insights-from-the-latest-salary-survey/
Presented by BookNet Canada and the Association of Canadian Publishers on May 1, 2025 with support from the Department of Canadian Heritage.
65. Location Where am I? In browser, HTML5, based on IP, GPS, GSM signal Where is …? Mostly through geocoder web-services Geonames (http://www.geonames.org/) Nominatim (http://nominatim.openstreetmap.org/) Google API, Mappy, Yahoo! PlaceFinder
98. Open / free data OpenStreetMap, community built map http://www.openstreetmap.org/ Natural Earth http://www.naturalearthdata.com/ Local data
111. In-memory DB ideal for junit testing Does not support all methods, but can easily be extended project GeoDB version 0.4 site https://github.com/jdeolive/geodb/wiki license BSD-like
140. Register your data provider hibernate.dialect=org.hibernatespatial.postgis.PostgisDialect Special type for storing a Geometry @Column(name = "geom")
147. Analytics Originally a fork of (part of) GeoTools but with cleanup and refactoring, and Java6 only project GeoToolkit version 3.19 site http://www.geotoolkit.org/ license LGPL
177. Integrate with ArcGIS, Google Maps/Earth; Yahoo! Maps, MS Virtual Earth project GeoServer version 2.1.2 site http://geoserver.org/ license GPL
190. Can be extended/customized using plug-ins Jgrass, Eurobios, DEWS project uDig version 1.2.2 site http://udig.refractions.net/ license LGPL
226. Graphical components to run and use those algorithms Including graphical modeler Integrates with many GIS tools gvSig, OpenJUMP, uDIG Split of from gvSig project SEXTANTE version 0.6 site http://sextante.forge.osor.eu/ license MIT
232. Faces for front-end/clients GWT, SmartGWT, GeoJSON Generic layers for data access WMS, WFS, GeoTools data source, Hibernate Spatial Plug-ins for extension Caching and rasterization, printing/PDF, security services, geocoder project Geomajas version 1.9.0 site http://www.geomajas.org/ license AGPL
239. Q & A Joachim Van der Auwera http://blog.progs.be/ Geosparc [email_address] @joachimvda http://geosparc.com/