uk: Комп'ютерні науки

description: A knowledge graph is a network that interconnects concepts, objects, or events according to domain specific relationships and terminology. Spatial knowledge graphs model locations and how they are spatially related to each other according to semantic properties and are useful for helping to automate the integration of geographic data across silos. Information systems used to make decisions often have different pictures of the geographies (i.e. people, places, and infrastructures) they respectively cover. Within a single area, different programs collect and store different geographic data in siloed systems at different times, leading to discrepancies and duplication of effort. This also results in decisions based on incomplete and out-of-date geographic data (e.g., spatial distribution of population and resources). GeoPrism Registry is an open-source Common Geo-Registry (CGR) implementation that utilizes spatial knowledge graphs to provide a single source of truth for managing geographic data over time across multiple information systems and data sources. It is used to publish, access, and manage changes over time to hierarchies and geospatial data for geographic objects such as administrative divisions, infrastructure and other relevant physical features. GeoPrism Registry uses geo-ontologies to define semantic properties and relationships that implement spatial knowledge graphs using a graph database. Changes to attribute values, relationships, and geographies are managed for different time periods. Historical views of data can be generated for any time period. The application has been released under the Lesser General Public License (LGPL) and was developed using only open-source components including OpenJDK, MapboxGL, PostgreSQL, OrientDB, Solr, GDAL, and GeoServer. This talk will demonstrate how spatial knowledge graphs defined in GeoPrism Registry using FOSS4G tools can: 1. contextualize data from different sources in both time and space, 2. use geographic objects as the common link between data sources, 3. facilitate trend analysis, and 4. aggregate data according to different hierarchies Support for the development of GeoPrism Registry was provided by the Bill and Melinda Gates Foundation via the Digital Solutions for Malaria Elimination (DSME) Project and the DSME Community. The DSME project uses geo-enabled information systems to improve the efficiency and effectiveness of malaria surveillance, program planning, and intervention.

uk: вхід без авторизації

name: GeoPrism Registry - Using Spatial Knowledge Graphs for Managing and Integrating Geographic Data Over Time Across Multiple Information Systems


Jorge Martinez Gomez

type: Person

cs: Informatika

de: Informatik

fi: tietojenkäsittelytiede

uk: Комп'ютерні науки

en: Computer Science

fr: Informatique

da: Datalogi

es: Ciencias de la Computación

nl: Informatica

cs: Technické vědy

de: Ingenieurwissenschaften

fi: tekniikka

uk: Інженерія

en: Engineering Sciences

fr: Ingénierie

da: Ingeniørvidenskab

es: Ingeniería

nl: Engineering

description: Climate and vegetation indicators created from Earth observation data provide timely information to analysts and decision makers implementing disaster risk reduction and climate risk mitigation programs. The United Nations World Food Programme’s (WFP) Climate and Earth Observation unit (ClEO) works with a number of Earth observation datasets to measure and monitor climate risks across all of the regions where we work, including 90+ countries globally. The end users of this information include government institutions such as the meteorological and disaster management agencies, implementers of humanitarian assistance programs, as well as WFP field staff working on programs which build climate resilience through the development of community assets and livelihood support. To enable the creation and dissemination of monitoring indicators, WFP is in the process of deploying an instance of Open Data Cube with nearly global coverage. Leveraging the power of data cubes to measure key climate and vegetation indicators over space and time, WFP’s Open Data Cube instance will provide free and open access to a wide range of analysis-ready data products. Utilization of this data requires user-facing applications with easy to use and intuitive interfaces. One of the tools developed by WFP to provide more direct access to climate and Earth observation data is PRISM – an open-source software solution which greatly simplifies the integration of geospatial data from various systems. PRISM has been developed to easily integrate data from Open Data Cube deployments using OGC standards – providing a quick tool to display time-series raster data in an interactive dashboard. During this talk, WFP will present a brief overview of the use cases we address with Earth observation data, the role of our Open Data Cube instance in the organization, and the development of tools and processes to disseminate data for visualization using OGC standards – including the PRISM platform.

TIB AV-Portal

type: Service

type: WebContent

type: MediaObject

@language: en

cs: přihlášení není vyžadováno

de: keine Anmeldung erforderlich

uk: вхід без авторизації

en: no login required

nl: geen login vereist

name: Visualizing climate risks for disaster reduction and climate resilience programs – Interactive open-source tools for analysts and decision makers to utilize Earth observation data

type: Organization

name: Open Source Geospatial Foundation (OSGeo)

cs: Video

de: Video

fi: Video

uk: Відео

en: Video

fr: Vidéo

da: Video

nl: Video

es: Video


uk: Комп'ютерні науки

description: MAps for Planning, Monitoring and Evaluation (MAPME) is an initiative founded by Geo-geeks and FOSS enthusiasts from KfW Development Bank (KfW), French Development Agency (AFD) and MapTailor Geospatial Consultants. Aid agencies such as KfW and AFD financially assist developing countries in fighting hunger, poverty, disease, illiteracy and environmental degradation around the world. Together with our partner countries we are key decision makers in the allocation of the so-called Official Development Assistance (ODA). KfW, for example, allocated 12.4 bn. EUR to assist developing countries achieving the Sustainable Development Goals (SDGs) in 2020. Geodata and geospatial technologies help us to take informed decisions to allocate funds responsibly and maximize public goods and benefits. Nevertheless, the uptake of open data and geospatial technologies within our institutions and decision-making processes is still relatively low. We think that one of the main reasons for this is missing openness in the way that we deal with data-analytic questions in our institutions. In response we founded MAPME, an open community and open-source initiative to upscale and democratize the usage of geodata and geo-spatial technologies within our own institutions as well as our partners. With this initiative we promote cultural change in our institutions by prototyping small FOSS and open-data pilot projects that illustrate the power and usefulness of these technologies to improve development aid projects. One of our outputs is the mapme.biodiversity package, which offers R-users the possibility to automatically download and process several important open-data sources for conservation science using a parallelization approach to deal with large AOIs or global conservation portfolios (github.com/mapme-initiative/mapme.biodiversity). We will offer a talk where we share our approach to FOSS application and development, what we see as barriers in our institutional and IT contexts and first successes stories that leveraged the power of geospatial data for learning about our projects and taking more informed decisions.

uk: вхід без авторизації

name: The MAPME Initiative: Leveraging the power of open data and FOSS GIS to improve public expenditure in the development aid sector.


keywords: foss4g2022 generaltrack Stateofsoftware

uk: Комп'ютерні науки

description: In 2012, FAIMS project developed FAIMS Mobile, an open-source platform for minting Android applications for offline human-mediated data collection on multiple tablets. Originally intended for archaeology, this platform saw cross-disciplinary adoption including disciplines such as oral tradition, linguistics, ecology and geochemistry. Mobile GIS (provided by Nutiteq, Estonia) was built into the core software from the start providing the most essential geospatial functionality from management and rendering user-owned raster and vector data, to manual data creation, editing, retrieval, and rendering. Automated data collection via onboard and bluetooth sensors was also implemented to support unique identifier generation and printing, and other key tasks for field sample tracking. Navigation and spatial query facility existed. The simplified interface isolated end-users from administrators, with only the latter needing geospatial skills and domain knowledge, a division that facilitated data entry by unskilled volunteers. Many of the geospatial functions, however, required programming to customize. Given this barrier to entry, only clients with access to a programmer could create customisations for geospatially-tailored field data entry. Others had to run existing customisations, published on Github. Despite this bottleneck, FAIMS 2.6 clients created a variety of spatial data collection workflows, from simple offline shape mapping to manual map data digitisation. In 2022, FAIMS project is rebuilding the FAIMS Mobile platform to equip it with a graphic user interface for customisation, to allow cross-platform deployment, and to implement ‘round trip’ data transfer to and from existing desktop tools. We hope to retain a robust geospatial data creation capability but aim to strip away functionality that saw little use over the 10 previous years, taking a 'just-enough-GIS' approach. As the architecture of FAIMS Mobile is changing from sqlite with spatialite extension to CouchDB/ PouchDB supporting geojson, technical elaboration pointed to OpenLayers as the most appropriate and complete library for geospatial data collection and management. This paper will examine the challenges and considerations of ‘just enough GIS’ implemented with OpenLayers in a comprehensive mobile data capture application.

uk: вхід без авторизації

name: Just Enough GIS: Plugging Lightweight Mobile GIS into an Offline Field Data Collection Platform


uk: Комп'ютерні науки

description: QFieldCloud's unique technology allows your team to focus on what's important, making sure you efficiently get the best field data possible. Thanks to the tight integration with the leading GIS fieldwork app QField, your team will be able to start surveying and digitising data in no time. Discover what QFieldCloud has to offer and how, thanks to seamless integration with your SDI, it can help make your teams' fieldwork sessions pleasant and efficient. And if you want to roll out your own customized version, nothing will stop you, QFieldCloud is open source! QFieldCloud is a SaaS (software as a service) solution built by OPENGIS.ch that allows your team to seamlessly integrate field data to your SDI. QFieldCloud is written in python using the Django Web framework that encourages rapid development and clean, pragmatic designs. QField is the mobile data collection app for QGIS with more than 120K active monthly users and 500K downloads. Discover how the seamless synchronisation with QFieldCloud can help make your teams' fieldwork sessions pleasant and efficient.

uk: вхід без авторизації

name: Seamless fieldwork thanks to QFieldCloud


uk: Комп'ютерні науки

description: PostGIS represents the de-facto standard for managing your spatial data, while QField is the state-of-the-art application for their management in the field. Since QField 2.0 release in spring 22, the seamless data synchronisation experience is complete. QFieldCloud closes the loop between your company's fieldworkers and the GIS analysts. In this talk, we'll share _features_, _best practices_ and _pro-tips_ for managing your projects, remote teams, and permissions in a professional setting. ## About QField QField is an open-source app developed for efficient fieldwork in real-time in urban areas, with a 5G connection or with offline data. The mobile GIS app combines a minimal design with sophisticated technology to conveniently bring data from the field to the office. Seamless QGIS integration, GPS-centred, offline functionality, synchronisation capabilities, desktop configurable: “QField” is designed for fieldwork – simple but uncompromising. Link: qfield.org ## About QFieldCloud QFieldCloud is a spatial cloud service integrated into “QField” that allows remote provisioning and synchronisation of geodata and projects. Although “QFieldCloud” is still in an advanced beta stage, it is already being used by many groups to improve their workflows significantly. Link: qfield.cloud

uk: вхід без авторизації

name: Professional field data management with QField


Openness - a Strategic Choice

uk: Комп'ютерні науки

description: The National Land Survey of Finland has made a strategic decision to pursue increased use of open source solutions in its activities. We’ve been an active user of FOSS4G solutions for more than a decade. Further, we created an open source mapping framework Oskari, which has an active user and developer community. In autumn 2020, the National Land Survey of Finland made a major decision to build our new topographic data production system on open source components, such as QGIS and PostgreSQL/PostGIS. The decision has raised a few eyebrows and a lot of interest among other national mapping agencies as well as other institutions using geospatial software. This talk will discuss - on what grounds we made such a decision - how we are progressing with the implementation - how we are looking at engaging in collaboration with open source communities - and most importantly, why every public sector organization should consider the benefits that can be gained by using and investing in open solutions.

uk: вхід без авторизації


Google Summer of Code with OSGeo

uk: Комп'ютерні науки

description: OSGeo's *Google Summer of Code * Initiative has been an inspiring and motivating platform for new contributors to join the OSGeo projects, community projects, guest projects, and incubating projects. In 2022, OSGeo is participating for the *_16th year_* in the Google Summer of Code, and it itself is a great achievement. With this talk, the OSGeo GSoC Administrators shall try to put forth the importance of GSoC with respect to the students and participating projects. The admins would focus on the development of projects with GSoC and encourage projects to be a part of the upcoming GSoC. Over the years, OSGeo's Google Summer of Code initiative has transformed into an initiative full of contributions towards geospatial software development. In the last 16 years, many OSGeo projects comprising incubating projects, community projects, and guest projects have progressed attributed to the contributions of student developers. Some of these contributors continue to participate as contributors for the projects and went on to take mentoring and organizing responsibilities. This is a true sense of FOSS4G in terms of the individual and collective growth of the developers and the OSGeo community. *In this talk, the OSGeo GSoC Admins team would try to appreciate the efforts of all the mentors and students involved till now and present the state of the GSoC 2022. The Admins would also present possibilities for new projects to be part of the GSoC with OSGeo as an umbrella organization.*

uk: вхід без авторизації


UN Open GIS Initiative

uk: Комп'ютерні науки

description: UN Open GIS Initiative, established in March 2016, is to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of contributing partners (Member States, international organizations, academia, NGO’s and private sector). Geospatial Information Systems (GIS) has been played a substantial role in providing timely and effective geospatial information products (maps and dynamic tools) to ensure the United Nations operations are equipped with suitable information to support the UN mandates through informed planning and decision-making processes. The UN has been using proprietary GIS software for the past two decades. The rapid growth and development of open-source GIS solutions present the technological potential, operational flexibility and financial benefits as well as easy to access for UN operational partners and host nations. In view of complexity and variety of UN operational demands and the outcome and lessons learned from the UN Open GIS Initiative, it is identified to develop a hybrid GIS platform that the users should be able to access the most suitable solutions to fulfil the operational demands in flexible and cost effective manner whether the solutions are open source or proprietary, combination of both and/or complement each other. The hybrid model lets coexist two software stacks, one open source based, the other proprietary, which renders different services to end users and applications. Significant progress has been made so far in developing open source-based GIS solutions such as Hybrid Geospatial Database, GeoPortal, Analytical models/ applications, Data collection and Optimized/innovated applications for harmonizing open source technology with proprietary as well as open GIS trainings to the UN staff for smooth transition from proprietary to hybrid GIS platform technology. In particular, it will provide an overall update on what has been achieved by the UN Open GIS Initiative during the past year, such as hybrid GIS architecture, mobile GIS solution, story map project, field application of OpenDroneMap and UN Vector Tile toolkit as well as the capacity building activities.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The message is not surprising: You should quality check your code, too, even if you are writing a small script for your own needs! However, maybe you wondered if all the warning messages are relevant to you or got discouraged after getting a flood of messages from tools like Pylint. Perhaps you were even annoyed by it. This talk will help you get motivated and get started and how to automate that with continuous integration tools such as GitHub Actions. In this talk, I will share my experience with adding various code and non-code checks to GRASS GIS which is primarily written in C, C++, and Python. Checking a mixed code base with over 30 years of development is not easy, but not impossible. The talk will cover code quality measures in GRASS GIS such as tests, Pylint, Black, GCC, CodeQL, and Super-Linter and how this compares to my experience with new and small organizational repositories.

uk: вхід без авторизації

name: Take-Home Messages from Adding Code Quality Measures to GRASS GIS


uk: Комп'ютерні науки

description: SMASH, the smart mobile app for surveyor’s happiness, is a slick app dedicated to digital field mapping. The open source flutter app for Android, IOS (and upon request Linux, Macos and Windows) is packed with features, as for example: Geopackage and PostGIS editing support, Kalman filter on gps logs, geo-fences, native geotiff and shapefile visualization support, SLD styling for vector datasets. SMASH’s web counterpart is the Survey Server, a web application that allows groups of surveyors to centralize data collection. Users can synchronize the data from the app, but also download dedicated forms and projects, as well as basemaps and datasets. The server is built upon the same technology as the mobile app and visualizes the data with the same look and feel. Notes serverside-versioning has been introduced to enhance synchronization of data by teams. A redmine plugin is being developed by community members to create a geo-ticketing system. This presentations gives an insight about the state of the art of the SMASH ecosystem and its current roadmap.

uk: вхід без авторизації

name: SMASH, state of the art of the digital field mapping project.


OSGeo community interactions

uk: Комп'ютерні науки

description: OSGeo is an international organization, and the members are people from everywhere in the world . OSGeo is cares and loves the community. When you move from "other" G software to FOSS4G you become part of the community. This community has a range of roles like users of the geo-spacial software, conference organizers, geo-spacial software developers, committee members, and some many more. We are a complex organization. As the second objective of this talk I would like to explain our organization. The preface of the main objective: These last two years have been hard times for everyone, we have been locked down, working remotely and unable to interact in person with our colleagues, and probably on this FOSS4G some members will not be able to be face to face during this FOSS4G 2022 in Florence, Italy. The main objective: I would like to share the "autographs & good wishes" from the OSGeo community members that I've meet along these 7 years that I've been participating on the organization.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The Copernicus Climate Change Service (C3S) Climate Data Store (CDS) is a single point of access to a wide range of free, quality-assured climate data, along with a suite of tools for performing cloud-based analysis and visualisation of very large datasets. Launched in 2018, the CDS provides over 100 datasets and 30 interactive applications for a global, interdisciplinary and intersectoral audience of over 100,000 users. The Copernicus Data Store (CopDS) project aims to reimagine the CDS, making use of modern technologies and knowledge gained during the development of the existing system to expand and streamline its functionalities and improve its performance and scalability. We present a high-level blueprint of the in-development CopDS, with an emphasis on how we plan to overcome the limitations of the original CDS. We explore our plans for the development of a new suite of open-source Python tools for performing retrieval, analysis and visualisation of climate and atmospheric data under the CopDS project, along with our plans for offering free cloud-based infrastructure for processing and visualising very large datasets through an easy-to-use Python web interface. We also discuss the development of tools for transforming simple Python code into high-quality web applications for exploring CopDS climate and atmospheric datasets, providing tools for interactive mapping, graphical user interfaces and a results cache for responsiveness.

uk: вхід без авторизації

name: The Copernicus Data Store (CopDS) - a reimagining of the Copernicus Climate Change Service (C3S) Climate Data Store (CDS)


FAIR-ization of INSPIRE datasets

uk: Комп'ютерні науки

description: Belgian federal authorities are working on PSI/INSPIRE conversion tool. We have produced an enhanced DCAT AP 2.0 profile. We have proposed to use ATOMFeed to instantiate dcat:Distribution classes because of their semantic completeness. We have tried to keep most of the INSPIRE metadata elements in order to keep the work that has been done for some years.. Now we are working on its implementation through GeoNetwork 4.x microservices that would provide a consistent DCAT AP RDF/XML with many languages. By doing this we consider that our datasets will be more accessible through many platforms and open data portals and will become real FAIR data. This work is the result of the strong collaboration between federal belgian authorities (e.g. Cadaster, National Mapping Agency, Office of federal statistics, ...).Moreover we are involving regional authorities in order to reach a certain harmonization. Now we would like to share these developments with the opensource community.

uk: вхід без авторизації


How to join OSGeo (for projects)

uk: Комп'ютерні науки

description: Welcome to the Open Source Geospatial Foundation, proud hosts of FOSS4G, and advocate for free and open source geospatial software everywhere. This is a call out to open source software developers; please join OSGeo and help us help you! Join OSGeo today: - Even just listing your project on the osgeo.org website is a great first step. Help us promote your technology so users can discover and enjoy your software. - The OSGeo “community program” gives project teams a chance to join the foundation with an emphasis on supporting innovation and new projects. The foundation provides some direct support, assistance along with endorsement and recognition from our board. - For established projects please join our “incubation program” to be recognized for excellence and as a full OSGeo committee. Unlike other foundations, OSGeo does not require that you give up or transfer any Intellectual Property; we simply ask that you be spatial, open-source, and open to participation. This presentation gives clear instructions on how to join OSGeo, and representatives from recent successful projects will be on hand to answer your questions.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: To enable sustainable and impactful Open Science in the long-term, ESA Earth Observation looks to design and implement a comprehensive Open Science framework, which includes a dedicated set of integrated tools and common practices for effective scientific data management, seeking to support Open Innovation, advance Science and increase community participation. The framework will build on and advance existing Open Science elements and will develop new capabilities to achieve the ambitions and vision set forth in the 2025 Agenda, supporting the European Green Deal. The four main pillars of the initiative are: i) EO Digital Platforms, interoperability and standardisation, ii) Accessible and Reproducible EO Science, iii) Inclusive and collaborative research and iv) Strategic Partnerships. Contributing to the second pillar, ESA is developing an EO Open Science Catalogue tool to enhance the discoverability and use of products, data and knowledge resulting from Scientific Earth Observation exploitation studies. Adhering by design to the "FAIR" (findable, accessible, interoperable, reproducible/reusable) principles, the Open Science Catalogue aims to support better knowledge discovery and innovation, and facilitate data and knowledge integration and reuse by the scientific community. The Open Science Catalogue is based upon the EO Exploitation Platform Common Architecture (https://eo4society.esa.int/2022/01/26/interoperability-sharing-your-application-where-the-data-sit/) (EOEPCA) and shares its basic Open Source components, but extends it with additional functionalities: - The Static Catalogue is a hosted STAC Catalogue, comprised of static Catalogue, Collection, and Items that represent the Themes, Variables, Projects, and Products - The Open Science Catalogue Frontend is a Vue.js based client application, that allows the efficient browsing of the Open Science Catalogue - The Backend API allows users to make submissions to create, update, and delete Themes, Variables, Projects, and Products. These submissions are then handled as GitHub Pull Requests, where they can be further reviewed, discussed, and finally accepted or denied. The Open Science Catalog makes use of various geospatial Open Source technologies such as pycsw, PySTAC, and OpenLayers. In this presentation we will review the EO Open Science Catalogue architecture, technology stack, and how this tool can be used to discover and publish Earth System Science products from ESA activities. We'll also look at future evolutions of the product and how it contributes to the overall ESA EO Open Science Framework.

uk: вхід без авторизації

name: EO Open Science Catalogue initiative by ESA


uk: Комп'ютерні науки

description: In force since 2007, the INSPIRE Directive has established a European Spatial Data Infrastructure to support European Union (EU) policies relevant to the environment. The INSPIRE Geoportal (inspire-geoportal.ec.europa.eu) constitutes its main component, being the central point of access to all datasets published by EU Member States falling under the scope of the Directive. Using the INSPIRE Geoportal, users can search for, access, visualize and download datasets published by more than 7000 data providers from across Europe. In line with the open source strategy of the European Commission and the ambition towards a sustainable evolution of the INSPIRE infrastructure based on open source components, since 2021 the INSPIRE Geoportal is has been revamped by using cutting-edge, open source applications and open standards, while redesigning the way in which information and services are offered to users. The process comprises deep changes in the Geoportal backend, totally renovating the underlying catalogue application: management interface, powerful harvesting engine, set of metadata, data and service linking tests, search engine, automatic metadata translation capabilities, containerization and deployment in a cloud environment. In addition, a new frontend (user interface) is integrated with the mentioned backend using APIs, making both layers more independent in terms of technological stack and update cycles. The application selected for achieving these goals is GeoNetwork opensource, currently constituting the catalogue choice of around 80% of Member States national geospatial data portals in the EU. Since its inception in 2001, it has been developed with a strong focus on international standards and many new features have been added over the years. During the last year, the GeoCat staff and the INSPIRE team at the European Commission’s Joint Research Centre have closely collaborated in the development of a new powerful and versatile system for delivering the revamped INSPIRE Geoportal, contributing the improvements – to the maximum possible extent – to the core of GeoNetwork to maximize their exploitation by the geospatial community. More in detail, the system encompasses a high-performance harvesting system based on a microservices, including link validation and reporting functionality. All these pieces have been developed as separate components, which can be scaled independently from other components within a GeoNetwork-based infrastructure. Performance and compliance to the INSPIRE Technical Guidelines formed part of the key requirements of the work. As a result, GeoNetwork capabilities for supporting the INSPIRE Directive will be substantially improved and completed in the toolkit. This, in turn, will also improve the transparency and collaboration between the national authorities and the European level. At the end of this transitional phase for the INSPIRE Geoportal, foreseen by mid-2022, the project will deliver tangible benefits. Firstly, by providing EU Member States with an up-to-date and transparent toolkit for managing their geospatial metadata, data and services in compliance to the INSPIRE Directive monitoring and reporting obligations. Secondly, by making a direct valuable contribution to the core of GeoNetwork and to the whole open source geospatial community.

uk: вхід без авторизації

name: Revamped INSPIRE Geoportal - Cooking the next generation of spatial data catalogues


uk: Комп'ютерні науки

description: This talk by Thomas Gageik, Director Digital Business Solutions (DIGIT.B) at the European Commission will get you up to speed on the most recent actions to encourage free and open source in and around the Commission. This is an introduction to the session organised by the EC, and we will show you what has changed since the adoption of the reinvigorated open source strategy in October 2020. Our topics include: what have we done to make it easier for the Commission to share software as open source, and how can we contribute to existing free/open source software tools. We will show you how the Commission is helping to strengthen the security of open source software, and how we are networking with other organisations to help open source to progress in public services across the EU. The talk will also introduce you to the open source programme office. The EC OSPO, created in 2020, is here to help Commission projects with free/open source.

uk: вхід без авторизації

name: Open source at the European Commission 2022


uk: Комп'ютерні науки

description: The European Centre for Medium-Range Weather Forecasts (ECMWF) is an intergovernmental organisation that produces global numerical weather predictions and other data for its Member and Cooperating States and the broader community. It hosts one of the largest meteorological data archives in the world. ECMWF supports the open data community by providing data through its Public Datasets program and Open Charts. Additionally, the Centre has a long history of and extensive expertise in developing and providing software to process and visualize meteorological data. In concert with these efforts, we developed SkinnyWMS – a lightweight Web Map Service for meteorological data. SkinnyWMS is currently used in the Copernicus Climate Data Store (CDS) and Germany’s Meteorological Service (DWD) Geoportal. It provides out-of-the-box interactive visualisation for a large set of meteorological parameters. It offers built-in support for data stored in GRIB (WMO standard) and NetCDF (OGC standard) formats, which are commonly used in meteorology, climatology, and oceanography. SkinnyWMS is written in Python and is based on ECMWF’s existing free and open source software ecCodes and Magics. It is free and open source software available under the Apache License 2.0. SkinnyWMS’ code is hosted on GitHub and it's available as an Anaconda package, from PyPi and as a Docker image from Docker Hub.

uk: вхід без авторизації

name: SkinnyWMS Meteorological Web Map Service


uk: Комп'ютерні науки

description: *MapStore* is an open source product developed for creating, saving and sharing in a simple and intuitive way maps, dashboards, charts and geostories directly online in your browser. MapStore is cross-browser and mobile ready, it allows users to: - _Search_ and load geospatial content served using widely used protocols (WMS, WFS, WMTS, TMS, CSW) and formats (GML, Shapefile, GeoJSON, KML/KMZ etc..) - _Manage maps_ (create, modify, share, delete, search), charts, dashboard and stories directly online - _Manage users_, groups and their permissions over the various resources MapStore can manage - _Edit data online_ via WFS-T with advanced filtering capabilities - _Deeply customize the look&feel_ to follow strict corporate guidelines - _Manage different application contexts_ through an advanced wizard to have customized WebGIS MapStore viewers for different use cases (custom plugins set, map and theme) You can use *MapStore* as a product to deploy simple geoportals by using the standard functionalities it provides but you can also use MapStore as a framework to develop sophisticated WebGIS portals by reusing and extending its core building blocks. *MapStore* is built on top of React and Redux and its core does not explicitly depend on any mapping engine but it can support both OpenLayers, Leaflet and Cesium; additional mapping engines could be also supported (MapBox GL is in the working) to avoid any tight dependency on a single engine. The presentation will give the audience an extensive overview of the MapStore functionalities for the creation of mapping portals, covering both previous work as well work for the future releases. Eventually, a range of MapStore case studies will be presented to demonstrate what our clients (like City of Genova, City of Florence, Halliburton, Austrocontrol and more) and partners are achieving with it.

uk: вхід без авторизації

name: FOSS4G Firenze 2022 - MapStore, a year in review


STAC Best Practices and Tools

uk: Комп'ютерні науки

description: The SpatioTemporal Asset Catalog (STAC) specification is a common language for describing geospatial information that is flexible enough to extend across domains and use cases. In this talk, we walk through best practices for building STAC catalogs and using STAC extensions, using real world examples. These best practices are informed by documentation, conversations with STAC contributors, and discussions within the wider community. We survey the ecosystem of open-source STAC software, which includes libraries and tools written in Python, Node.js, and more. We show examples of reading, modifying, and writing STAC catalogs with a selection of software, including PySTAC and stactools, and we show which metadata to include in your STAC objects to ensure interoperability with powerful tools like xarray and pandas. Whether you are new to the STAC ecosystem or an experienced contributor, this talk will provide you with the context and tools you need to build your best STAC!

uk: вхід без авторизації


uk: Комп'ютерні науки

description: When using QGIS as a user interface for a PostgreSQL- & PostGIS-based registry database, user experience plays a high role. The data schemas of a registry database can hold a complex set of relations and database objects which can be hard to set up within QGIS. This was the case with a waste soil transportation registry that we developed for the City of Tampere, Finland. The main goal of the registry is to optimize soil transportation from construction sites by communicating and making it visible what soil categories are available and needed where and when. The registry enables significant savings in transportation costs as well as substantial reductions in climate emissions. When the relational data model gets complex, you can deploy different strategies for setting up the workflows within QGIS. One possible solution is to use editable views and triggers for enabling user-friendly workflows in QGIS. This was the case in our soil registry project. The data model, as it was, would have forced the user to create multiple new features to the database tables when he/she just wanted to add a single soil transfer from one construction site to another. This was seen as too tedious when repeated constantly. The solution was to make a database view that the user could edit in QGIS, in addition to deploying database triggers for creating the right database features, with the proper data into the correct database tables. This presentation seeks to show how the strategy was deployed and what challenges we met during the development.

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name: Streamlining QGIS workflows with PostgreSQL editable views and triggers


News from actinia - let's STAC!

uk: Комп'ютерні науки

description: „Hello again, my name is actinia. Still new to OSGeo and a Community Project since 2019, you might have heard about me already. In short I am a REST API on top of GRASS GIS to allow location, mapset and geodata management and visualization as well as execution of the many GRASS GIS modules and addons. Processing with other tools like GDAL and snappy is supported as well. I can be installed in a cloud environment, helping to prepare, analyse and provide a large amount of geoinformation. Besides these facts about me there is also a lot to tell about what happened last year! Besides vector upload, citable DOI, QGIS and python client implementations and more, I can be a Spatio Temporal Asset Catalog myself with the actinia-stac-plugin, am able to use data registered in a STAC for processing and after processing register the resulting data. With the ongoing development of the openeo-grassgis-driver, you can use this new functionality either in my native language or via openEO API. To learn about the details, come on over!“

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State of TerriaJS

uk: Комп'ютерні науки

description: TerriaJS is an open-source framework for web-based geospatial catalogue explorers. It uses Cesium and Leaflet to visualise 2D and 3D geospatial data, and it supports over 50 different Web APIs, file formats and open data portals. It is almost entirely JavaScript in the browser, meaning it can even be deployed as a static website, making it simple and cheap to host. TerriaJS is used across the globe to create next-generation Digital Twin Platforms for open geospatial data discovery, visualisation and sharing - it is used to drive - National Map (nationalmap.gov.au/) (Australian Gov) - Digital Earth Australia Map (maps.dea.ga.gov.au/) - Digital Earth Africa Map (maps.digitalearth.africa/) - Pacific Map (map.pacificdata.org/) - NSW Spatial Digital Twin (nsw.digitaltwin.terria.io/) (Australian State Gov) - and many others In this talk, I will give: - Background information about TerriaJS and how it is used by the community - Current state of the project for users, developers and wider community - New features - Future plans!

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The State of Cloud-Native Geospatial

uk: Комп'ютерні науки

description: The vision of “Cloud-Native Geospatial” is a new paradigm of performing efficient computing and data access in the cloud in an interoperable way in order to achieve scalable and repeatable analysis of geospatial data. The last few years have seen major developments in open standards and open software that are helping make this vision possible, supporting full end to end interoperable workflows on remote sensing data, from data discovery to publishing of interoperable derived products. This talk will present the current state of the Spatio Temporal Asset Catalog (STAC) specifications (stac-spec and stac-api-spec), updates in the published STAC extensions, and the latest community developments around Analysis Ready Data (ARD). We will cover the landscape of current recommended cloud-optimized file formats, for raster, vector, and point-cloud data formats (COG, Zarr, GeoParquet, COPC). Finally, we will provide recommendations for open-source client software to use to take advantage of the emerging geospatial clouds.

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State of GeoNetwork 2022

uk: Комп'ютерні науки

description: The GeoNetwork-opensource project is a catalog application facilitating the discovery of resources within any local, regional, national or global "Spatial Data Infrastructure" (SDI). GeoNetwork is an established technology - recognized as an OSGeo Project and a member of the foss4g community for over a decade. The GeoNetwork team would love to share what we have been up to in 2022! The GeoNetwork team is excited to talk about the different projects that have contributed with the new features added to the software during the last twelve months. Our rich ecosystem of schema plugins continues to improve; with national teams pouring fixes, improvements and new features into the core application. We will also talk a bit about the health and happiness of the GeoNetwork opensource team. Progress of our main branches (3.12.x and 4.0.x), and release schedule. Attend this presentation for the latest from the GeoNetwork community and this vibrant technology platform.

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keywords: foss4g2022 generaltrack Education

uk: Комп'ютерні науки

description: Increasingly ubiquitous open spatial technologies offer the opportunity for new actors to participate in creating knowledge about the places where they live and work, and where they navigate the shocks and stresses of an uncertain world. This presentation offers insights about university student engagement in open mapping through the experiences of YouthMappers around the world. This inclusive international network of youth-led, faculty-mentored, and technology-enabled chapters on more than 300 campuses in 65+ countries work together to organize, collaborate, and implement mapping action that respond to needs around the globe. Specific examples will illuminate how students are creating and using spatial information that is collected using open software tools and made publicly available through open platforms, and in turn inform us about both the power and the limits of open spatial technologies in the hands of students working to build a more resilient, equitable and sustainable future.

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name: YouthMappers: a global youth movement on open mapping for humanitarian and development action


State of GeoPandas and friends

uk: Комп'ютерні науки

description: GeoPandas is one of the core packages in the Python ecosystem to work with geospatial vector data. By combining the power of several open source geo tools (GEOS/Shapely, GDAL/fiona, PROJ/pyproj) and extending the pandas data analysis library to work with geographic objects, it is designed to make working with geospatial data in Python easier. GeoPandas enables you to easily do operations in Python that would otherwise require desktop applications like QGIS or a spatial database such as PostGIS. This talk will give an overview of recent developments in the GeoPandas community, both in the project itself as in the broader ecosystem of packages on which GeoPandas depends or that extend GeoPandas. We will highlight some changes and new features in recent GeoPandas versions, such as the new interactive explore() visualisation method, improvements in joining based on proximity, better IO options for PostGIS and Apache Parquet and Feather files, and others. But some of the important improvements coming to GeoPandas are happening in other packages. The Shapely 2.0 release is nearing completion, and will provide fast vectorized versions of all its geospatial functionalities. This will help to substantially improve the performance of GeoPandas. In the area of reading and writing traditional GIS files using GDAL, the pyogrio package is being developed to provide a speed-up on that front. Another new project is dask-geopandas, which is merging the geospatial capabilities of GeoPandas with the scalability of Dask. This way, we can achieve parallel and distributed geospatial operations.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: In this talk we are going to present how the Danish Agency for Data Supply and Efficiency (SDFE) transitioned from a purely proprietary system to an open source system based on SpatioTemporal Asset Catalog (STAC) API and Cloud Optimized GeoTiffs (COGs) for servingservicing its open data collection of 5 million oblique aerial images. The new system is built partly using existing open source components and partly on newly built open source components. It uses significantly less resources and lets third party users access the data in a standardized way. An important part of the process has been to develop and propose a community STAC extension for perspective imagery. This extends the STAC base metadata with parameters which are needed to do photogrammetric calculations and measurements using the images. The potential of this extension is that it enables the community to build generic perspective imagery clients in which the user can do advanced photogrammetric measurements. To ensure support for existing clients and to lower the barrier to entry the system also supports clients without COG reading abilities. Using open source components we have built "CogTiler" a high performance tile server which serves jpeg tiles directly from the COGs. Most of the time this is accomplished without decompressing the jpeg data. SDFE required that all code written for this project be open source and easily available to anyone. Therefore, all the code is available on GitHub.

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name: Serving oblique aerial imagery using STAC and Cloud Optimized Geotiffs


uk: Комп'ютерні науки

description: Although in use for about 10 years in various Esri products and services, the LERC (Limited Error Raster Compression) raster compression algorithm has only just recently made its way into the free and open-source GIS scene by its inclusion in GDAL (3.3). LERC can perform both lossless and lossy raster data compression. To achieve its impressive compression ratios and speed LERC employs two major basic tricks: - The raster is processed and compressed in small two-dimensional blocks, taking advantage of spatial autocorrelation (neighboring values usually being more alike than others). - The raster values are quantized (absolute values are replaced by differences between neighbors) and bitstuffed to minimize the number of bits required to store them, this is especially useful for high bit depth data. For lossy compression LERC will follow a user-configurable maximum error threshold (the "limited error" in its name). Want to compress your DEM and allow up to one centimeter of error? No problemo! LERC is patented by Esri but thanks to the choice of the permissive Apache License it is freely usable by anyone. The talk will try explain the algorithm on a basic level, understandable by non-experts, and show its performance with some examples.

uk: вхід без авторизації

name: LERC, an innovative compression algorithm for raster data


State of Oskari (for developers)

uk: Комп'ютерні науки

description: Oskari is used world wide to provide web based map applications that are built on top of existing spatial data infrastructures. Oskari offers building blocks for creating and customizing your own geoportals and allows embedding maps to other sites that can be controlled with a simple API. In addition to showing data from spatial services, Oskari offers hooks for things like using your own search backend and fetching/presenting statistical data. This presentation will go through the improvements to existing functionalities and new features introduced in Oskari during the last year. The focus will be on functionalities from developer perspective like: - Improvements for working with vector features - API-improvements for embedded maps. - Rewrite of service capabilities parsing and handling - Planned developments for better theming support and mobile-device friendliness for the geoportal You can try some of the functionalities Oskari offers out-of-the-box on our sample application: demo.oskari.org.

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name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: To make the Platform possible and meet the objectives set, it was necessary to work with different areas of the government involved in urban planning and systems, promoting the opening of data to generate a sustainable process over time for the automatic and dynamic system of interpretation of the Urban Code that governs the constructive and urban behavior of the city of Buenos Aires, which is the basis of this technological solution. The platform is based on the “Digital Twin” concept, that is, a virtual and digital replica of a city's urban plan. The objective is to test any initiative on this virtual model before its real implementation, in order to reduce costs and risks. The tool was developed entirely with open source resources and technologies so that other organizations can study, modify and improve its design through the availability of its source code. Regarding its architecture, the platform works from the information extracted from the datasets of the areas referred to the urban fabric and parcels. Then, from a set of processing algorithms that works with systematized rules generated from the text of the urban code regulations, this information is processed, allowing the generation of 3D graphics of each of the city parcels. The volumetry of each parcel allows to know the buildability, the maximum allowed height and the allowed construction alternatives for each parcel, which integrate the platform's viewer.

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name: Generation of 3D geometries with Artificial Intelligence for the prediction of volumetry of the Urban Code of the City of Buenos Aires


uk: Комп'ютерні науки

description: High resolution aerial photos combined with accurate map data represents a perfect data set for training artificial intelligence models. The ‘KartAi’ project is an innovation project in public sector aimed at developing Ai-methods that detects buildings not in the cadastre or the building map dataset. Thereafter involving the property owner/citizen in a digital dialog and validate or crowdsource more detailed data. The foundation for this is high quality datasets for training and validating the different Ai-models. High resolution aerial photos are collected in large parts of Norway on a regular basis – often yearly – in a collaboration between federal and municipal. Thereby there exists a vast amount of extremely detailed image data combined with building map data and cadastre data. However, training the Ai-models have uncovered that minor errors and ‘skewed’ photos and/or vector data affects the results of the segmentation of roof tops/buildings. Therefore the KartAi projects has made fine tuned and accurate training data sets in several geographical areas optimized for training on detecting and segmenting buildings. In several large scale experiments, a multitude of existing models, newer models and own models have been training and validated. Additionally we have included LIDAR-height data to enhance the precision of segmenting between the likes of roofs and terraces. Training the models on the existing data yields good results. However, when finetuning with the high accurate data – the models show impressing results. Spatial Ai projects like KartAi are at the mercy of volumes of good training data. Our experience show that even more accurate data sets improve the models even further. Therefore, the project has made efforts that have resulted in the release of the training data sets publicly – as well as all of the results data for the different models and approaches that have been developed. This is an effort into developing a more open living lab for Spatial Ai in Norway. Our hope is that sharing the knowledge and data created can ensure that other Ai-models have easier access to high resolution and high accuracy data – to train models in the open living lab – and apply the models internationally where data is scarcer.

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name: KartAi – An open living lab for Ai in Norway


No-code geoAI

uk: Комп'ютерні науки

description: Artificial Intelligence (AI) has made an impact in almost every field and has become an incredibly powerful technology. However, while some players in big tech and academia have access to a highly skilful workforce that can create sophisticated AI solutions, many companies, governments, public organisations, and other societal stakeholders are lacking sufficient AI expertise and know-how. Many AI and Machine Learning (ML) frameworks aim to simplify and democratise AI development, even if typically focusing on those with software engineering skills. Some of these solutions, those that provide no-code tools, get the closest to the ideal of enabling "any person without prior training”. Collectively, these could represent a major breakthrough, as it has been proven time and time again that many businesses and organisations still struggle to implement AI to its full potential and scale. Visual, often drag-and-drop, no-code AI tools can make AI less intimidating and more comprehensible to non-technical profiles and those who lack the time and resources to build such systems from the ground up. No-code AI frameworks are expected to require minimum technical knowledge to develop practical AI solutions at scale. This is an emerging field, like was previously the case with no-code web development, starting with Dreamweaver and MS Frontpage, the first WYSIWYG (what you see is what you get) solutions, both launched in 1997. The European Commission is supporting the establishment of an AI-on-demand platform that will provide easy and simple access to AI tools that are made in Europe and are ‘trustworthy’. The platform will gather all the AI resources (algorithms and tools), and make them available to the potential users, businesses, and public administration, with the necessary services to facilitate their integration. Within the context of the EU’s commitment to trustworthy AI, we are exploring the landscape of AI solutions for non-experts, including no-code, low-code, AutoML and similar approaches, and evaluating them in an experimental setting via prototyping. Our findings are expected to inform the development of relevant European digital initiatives. For instance, we will consider how these emerging AI solutions for non-experts could be integrated and used in the context of digital infrastructures such as EuroGEOSS or the European Data Spaces. Further democratization of AI will happen when domain experts without prior AI expertise are enabled to tap into high-quality data to solve complex problems on their own, with technical details being abstracted away, such as algorithm selection, model training, software frameworks, hardware dependencies, and platform aspects. We expect that open-source AI technologies for non-experts represent a step towards such a future. During the conference, we will present the initial results of our geoAI activity, including a high-level architecture and a stack expected to be composed of various open-source software tools and open standards for digital infrastructures, data engineering and AI development. Our intention is to gather feedback from the audience and establish possible future collaborations in this space.

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keywords: foss4g2022 generaltrack OpenData

uk: Комп'ютерні науки

description: Is your government utilizing OpenStreetMap data in their workflows? How can crowdsourcing be leveraged to improve the completeness, freshness, and breadth of government geospatial data? As the world’s largest crowdsourced geospatial database, OpenStreetMap is poised to serve this need. Two years ago, OpenStreetMap US formed a Government Working Group to seek out mutually beneficial relationships between the public and open data communities. As part of this effort, OSM community members and representatives from federal agencies have been investigating solutions for feature collection. This collaboration has led to the development of Public Domain Map, which connects OpenStreetMap and government datasets. Through the Public Domain Map workflow, OpenStreetMap and government open geospatial data becomes more complete, current and readily usable by government agencies and the millions of users relying on both datasets. In this session, I will share the journey of Public Domain Map, how the project is bringing together US federal agencies and open source contributors to meet this goal, and how you can be part of it.

uk: вхід без авторизації

name: Crowdsourcing the Future of Government Data: OpenStreetMap in the Public Domain


The Open Source GIS Stack (OSGS)

uk: Комп'ютерні науки

description: In the last few years, open source GIS has been developing relatively rapidly with an increase in the number of open-source GIS software available for performing various specialty functions. With this increase came the problem of managing the dependencies of different software when installing them on the same machine or getting them to work together to accomplish a task. How was the setting up process the last time you needed to make a map, share it and write about how you made the map? This is where the docker-based Open Source GIS Stack (OSGS) comes in. OSGS is a rich, integrated, and opinionated GIS Stack with a focus on configurability and ease of use built from open source components. The primary objective of the OSGS stack is to provide simple and effective end-to-end solutions based on open source geospatial technologies. Some of the key services offered by the OSGS platform are Nginx and Hugo for web publishing using static web pages, File Browser for file management, QGIS-Server for publishing web maps, PostgreSQL and PostGIS for database management, and Metabase for visualizing your data. We’ll take a look at how easy and painless making, sharing and writing about maps can be. The Open Source GIS Stack by Kartoza is maintained in the Kartoza OSGS repository (github.com/kartoza/osgs).

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uk: Комп'ютерні науки

description: As a part of its AI4Earth initiative, Microsoft has created a Planetary Computer (PC) for hosting and processing open geospatial data. In addition to publishing a wide range of datasets, including Sentinel-2, MODIS, and more, the PC provides a powerful API and compute system based on open-source geospatial tools and using STAC metadata for data query, discovery, and access. In this talk, we present the latest in open geospatial data access, discovery, processing, and visualization using a variety of datasets from the Planetary Computer. We demonstrate use of the odc-stac package, which leverages the power of the OpenDataCube computing platform without the need for a database backend, and how odc-stac can load, mosaic, and transform geospatial assets into xarray datasets. We dive into other data interoperability tasks, including scaling processing with Dask and leveraging a variety of cloud-native formats. Along the way, we provide recommendations for data providers and curators on how to ensure their data can be used in a rich, interoperable way by the latest in geospatial processing tools.

uk: вхід без авторизації

name: Exploring Data Interoperability with STAC and the Microsoft Planetary Computer


uk: Комп'ютерні науки

description: In the words of Eric Elliot; All software development is composition: The act of breaking a complex problem down to smaller parts, and then composing those smaller solutions together to form your application. Inspired by Eric’s work we have begun to modularize all the things and combine your mapping libraries (Openlayers, Maplibre, et al.) with other open source libraries (Tabulator, ChartJS) for data visualizations. Having finally broken the shackles imposed on us by the restrictions of the Internet Explorer age we can finally facilitate Javascript (ES6+) to its functional best and deliver the applications we dream of. ESBuild has revolutionized the way we compile script, and dynamic imports which have long been touted as the future are finally available to us with a little help from Skypack. In addition to tried and tested server side rendering we now have powerful vanilla Web APIs to build application views on the fly and with little reflow, and repaint. This is a talk for the opinionated JS enthusiast.

uk: вхід без авторизації

name: Composing Software: Spatial for the JAMstack generation


uk: Комп'ютерні науки

description: Within large construction companies GIS is widely used to store, analyse and visualise spatial data. GIS is just one of the components of an information infrastructure and has to be an integral part that can provide data and information to other departments and subcontractors as well. Van Oord as a marine contractor deals with spatial data on a daily basis. Existing disciplines like the design team and Survey team already have their way of dealing with spatial data to fulfil their task. What is it that the organisation needs additionally to work with GIS? Van Oord has chosen to use FOSS4g software as a GIS backbone. This choice has its benefits but also poses challenges. Most competitors in the business use proprietary software. Clients do not necessarily follow standards and the IT department has to support our requirements. We are very proud of our GIS backbone and definitely see the benefits of using FOSS4G. Come and listen to the solution we have chosen; the changes we make in the business and challenges we face.

uk: вхід без авторизації

name: The challenges and benefits of implementing OS geo within a large contracting company


uk: Комп'ютерні науки

description: Acquiring and labeling geospatial data for training machine learning models is a time-consuming and expensive process. It is made even more difficult by the lack of specialized open-source tools for dealing with the idiosyncrasies of geospatial data. At Azavea, we have encountered both of these problems before. In this talk, we will present a solution that incorporates our geospatial annotation platform, GroundWork (groundwork.azavea.com), with our open-source deep learning framework, Raster Vision (rastervision.io), to provide a human-in-the-loop active learning workflow. This workflow allows labelers to immediately see the effect of their created labels on the model’s performance, thus speeding up the labeling-training-labeling cycle and making the connection between the AI and human GIS data labelers easy and seamless. This talk will extend the hands-on experience introduced in last year’s “Human-in-the-loop Machine Learning with GroundWork and STAC'' FOSS4G workshop. We will present an enhanced active-learning workflow that allows labelers to train a model and see predictions on-the-fly as they create labels in GroundWork. The model-training and predictions will be handled by Raster Vision. This workflow will give the labelers a clear view of the model’s current strength and weaknesses at all times, and thus allow them to direct their labeling efforts more efficiently. Newly created labels will propagate back to the AI model in real time, and an asynchronous job will continue to refine the model and predictions. This loop is backed by the open-source Raster Foundry (rasterfoundry.azavea.com) and Franklin (azavea.github.io/franklin) APIs, and is compliant with the STAC (stacspec.org) and OGC Features (ogc.org/standards/ogcapi-features) open standards.

uk: вхід без авторизації

name: Human-in-the-loop Machine Learning with Realtime Model Predictions using GroundWork and Raster Vision


State of Oskari (for end-users)

uk: Комп'ютерні науки

description: Oskari (www.oskari.org) is used around the world to provide map applications with integrations to spatial and statistical data and service APIs. Oskari can be utilized as a Web GIS with a regular browser or via embedded maps controllable with a simple API. The embedded maps are created in a easy-to-use WYSIWYG-tool enabling users to add a map component to their websites/services without any programming skills. The additional API can be used to integrate to existing APIs and services for richer functionality. This presentation will cover the basics of Oskari and new features introduced during 2021-2022. The focus will be on functionalities for end-users and administrators, such as: new styling tools, map layer analytics and diagnostics tool, metadata supported automation to statistical data visualisation, enhanced support for theming and mobile use. There will be a separate presentation about technical developments in Oskari focusing on developer experience. You can try the features of vanilla Oskari in our demo environment (demo.oskari.org), it has the newest stable version without any customisation.

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uk: Комп'ютерні науки

description: When websites and web tools are properly designed and coded, people with disabilities can use them. However, currently many sites and tools are developed with accessibility barriers that make them difficult or impossible for some people to use [W3C - Introduction to Web Accessibility]. The European accessibility requirements present a new and welcome challenge for OSGeo applications. Accessibility (a11y) goes far beyond ease-of-use, with strict guidance on making web applications easily accessible to screen readers and assistive technologies. This talk provides an overview of implementing the accessibility guidelines WCAG 2.1, WAI-ARIA, and EN 301 549 (Harmonised European Standard). GeoNetwork is used as a case study here, with “hands-on” illustrations of successful guideline implementations and their technical and organisational challenges. Making OSGeo Software accessible is a rewarding task that requires broad community engagement and support. Attend this talk to learn more about meeting the a11y requirements and the impact they will have on your organisation and your software solution.

uk: вхід без авторизації

name: GeoNetwork and a11y: Introducing accessibility in OSGeo applications


uk: Комп'ютерні науки

description: All of us involved in the creation and publication of large amounts of geodata are familiar with the complexities of data management. In the case of geodata created with GRASS GIS, we asked ourselves how they could be made accessible to GeoServer without duplication. To overcome the previous limitation of GRASS GIS having its own data format, we connected the tribes and let Java and C/Python communicate with each other. So the challenge was to be able to efficiently read the GRASS GIS database directly with GeoServer. And why is that? Because this directly links the analytical capabilities of GRASS GIS with the exceptional geo service & publishing capabilities of GeoServer. Our approach is to use the existing GDAL-GRASS bridge, and add this bridge as a new extension to GeoServer. To this we add two new GRASS GIS addons (r.geoserver.style + r.geoserver.publish) to easily publish the data from a GRASS GIS session as an OGC service. The new GeoServer GRASS raster datastore allows to use GRASS raster data directly in a GeoServer instance. In this way it is now very easy to publish GRASS data as a web service via GeoServer without having to export the data from GRASS GIS to GeoTIFF or COG files. This works for both classic raster data and also for timeseries which can e.g. be inspected as a WMS Time.

uk: вхід без авторизації

name: Connecting tribes: how we connected the GRASS GIS database natively to GeoServer


State of GeoWebCache

uk: Комп'ютерні науки

description: GeoWebCache is a popular open source tile cache server written in Java. GeoWebCache that can be used stand alone, working off a remote WMS or local tile layers, such as MBTiles. However, it's also integrated inside GeoServer, allowing simple and quick configuration, as well as transparent caching of WMS requests that happen to match a cached tile. This presentation will provide information on the latest development for the project, including: - Performance and scalability improvements - OGC TileMatrixSet built-in definitions - Storage of tiles in more blob stores (Swift) - MBTiles support - Integration of tile caching in OGC API - Tiles (with GeoServer integration) - Serving vector tiles and integration with the Mapbox ecosystem (e.g., style editing with Maputnik) - Continued codebase QA efforts (code clean up, dependency upgrades and the like) Attend this talk for a cheerful update on what is happening with this project, whether you are an expert user, a developer, or simply curious what it can do for you.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The talk will focus on how Map Kibera has empowered different Counties in Kenya to Map their projects using Open Street Map, Kobo collect and ODK. During the exercise Map Kibera collaborated with World Bank to produce large maps that are used during the participatory budgeting meetings for members of the community to decide the projects they want implemented. Map Kibera's approach is to empower the youth and some selected County officials with new mapping skills and methodologies. Members of the community are then able to make informed decisions by seeing what they already have and what might be missing. Map Kibera also helped the Four selected counties to develop a website that shows the status and the budget allocation for each and every project mapped. This helps promote transparency and accountability within the counties. Before the mapping happened, people would be asked to propose what project they wanted but it became hard without knowing what was already in existence. Now they can tell, We have a hospital we want a school for example.

uk: вхід без авторизації

name: Map Kibera Mapping Counties on OpenStreetMap


uk: Комп'ютерні науки

description: Several ambitious initiatives, such as Destination Earth of the European Union, are harnessing large amounts of Earth Observation and other data to develop so-called digital twins of the Earth. The combination of large and diverse data assets, cloud- & HPC-computing as well as sophisticates models and AI algorithms now permit to generate predictive EO scenarios. One key aspect of Digital Twins is the possibility to employ openness as one of the key principles for all its functions. Data policy, data access, software development, processing and information management are important considerations for engaging and integrating users of all kinds. Due to their high potential for science and society the European Space Agency, with its unique geospatial data holdings, is fully engaged in the development of Digital Twins of the Earth.

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name: Data Management in Earth Observation - The Potential of Open Digital Twins of the Earth


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description: Object detection, classification and semantic segmentation are ubiquitous and fundamental tasks in extracting, interpreting and understanding the information acquired by satellite imagery. Applications for locating and classifying man-made objects, such as buildings, roads, aeroplanes, and cars typically require Very High Resolution (VHR) imagery, with spatial resolution ranging approximately from 0.3 m to 5 m. However, such VHR imagery is generally proprietary and commercially available at a high cost. This prevents its uptake from the wider community, in particular when analysis at large scale is desired. HIECTOR (HIErarchical deteCTOR) tackles the problem of efficiently scaling object detection in satellite imagery to large areas by leveraging the sparsity of such objects over the considered area-of-interest (AOI). This talk presents a hierarchical method for detection of man-made objects, using multiple satellite image sources with different Ground Sample Distance (GSD). The detection is carried out in a hierarchical fashion, starting at the lowest resolution and proceeding to the highest. Detections at each stage of the pyramid are used to request imagery and apply the detection at the next higher resolution, therefore reducing the amount of data required and processed. We evaluate HIECTOR for the task of building detection for a middle-eastern country, estimating oriented bounding boxes around each object of interest. For the detection of buildings, HIECTOR is demonstrated using the following data sources: Sentinel-2 imagery with 10 m GSD, Airbus SPOT imagery pan-sharpened to 1.5 m pixel size and Airbus Pleiades imagery pan-sharpened to 0.5 m pixel size. Sentinel-2 imagery is openly available, making their use very cost efficient. The Single-Stage Rotation-Decoupled Detector (SSRDD) algorithm is used. Given that single buildings are not discernible at 10 m GSD, a bounding box does not describe a single building but rather a cluster of buildings. The estimated bounding boxes at 10 m are joined and the resulting polygon area is used to further request SPOT imagery at the pan-sharpened pixels size of 1.5 m. In the case of SPOT imagery, given the higher spatial resolution, one bounding box is estimated for each building. As a final step, predictions are improved in areas with low confidence by requesting Airbus Pleiades imagery at the pan-sharpened 0.5 m pixel size. Ablation studies show that HIECTOR achieves a mean Average Precision (mAP) score of 0.383 and 20-fold reduction in costs compared to using only VHR at the highest resolution, which achieves a mAP of 0.452. Code will be released under MIT license. We will also release the trained models on Sentinel, SPOT and Pleiades imagery. In addition, manually labelled building footprints over Dakar will be open-sourced to allow users evaluate the generalisation of the models over different geographical areas. The Sentinel Hub service is used by HIECTOR to request the commercial imagery sources on the specified polygons determined at each level of the pyramid, allowing to request, access and process specific sub-parts of the AOI.

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name: HIECTOR: Hierarchical object detector for cost-efficient detection at scale


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description: Keeping (OGC) Geospatial Web Services up-and-running is best accommodated by continuous monitoring: not only downtime needs to be guarded, but also whether the services are functioning correctly and do not suffer from performance and/or other Quality of Service (QoS) issues. GeoHealthCheck (GHC) is an Open Source Python application for monitoring uptime and availability of OGC Web Services. In this talk we will explain GHC basics, how it works, how you can use and even extend GHC (plugins). There is an abundance of standard (HTTP) monitoring tools that may guard for general status and uptime of web services. But OGC web services often have their own error, "Exception", reporting not caught by generic HTTP uptime checkers. For example, an OGC Web Mapping Service (WMS) may provide an Exception as a valid XML response or in a error message written "in-image", or an error may render a blank image. A generic uptime checker may assume the service is functioning as from those requests and an HTTP status "200" is returned. Other OGC services may have specific QoS issues that are not directly obvious. A successful and valid "OWS GetCapabilities" response may not guarantee that individual services are functioning correctly. For example an OGC Web Feature Service (WFS) based on a dynamic database may return zero Features on a GetFeature response caused by issues in an underlying database. Even standard HTTP checkers supporting "keywords" may not detect all failure cases in OGC web services. Many OGC services will have multiple "layers" or feature types, how to check them all? What is needed is a form of semantic checking and reporting specific to OGC services! GeoHealthCheck (GHC) is an Open Source (MIT) web-based framework through which OGC-based web services can be monitored. GHC is written in Python (with Flask) under the umbrella of the GeoPython GitHub Organization. It is currently an OSGeo Community Project. GHC consists of two parts: (1) a web-UI app (using Flask) through which OGC service endpoint URLs and their checks can be managed, plus for visualising monitoring-results and (2) a monitoring engine that executes scheduled "health-checks" on the OGC service endpoints. Both parts share a common database (via SQLAlchemy, usually SQLite or PostgreSQL). The database also stores all historic results, allowing for various forms of reporting. GHC is extensible: at this moment of writing a plugin-system is developed for "Probes" in order to support an expanding number of cases for OGC specific requests and -checks. Work is in progress to provide a GHC API for various integrations. Links: - Website: geohealthcheck.org - Sources: github.com/geopython/GeoHealthCheck - Demo: geohealthcheck.osgeo.org

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name: GeoHealthCheck - QoS Monitor for Geospatial Web Services


Cloud-Native Geospatial with JavaScript

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description: The amount of Earth Observation data we have available nowadays is exceeding the capabilities for data processing. Therefore, a lot of data is now made available in the cloud. To make digesting the data easier and more-lightweight, it is getting more and more popular to store the data in so-called “cloud-native” file formats while data processing is also moving towards the data, i.e., into the cloud. This way you only need to retrieve the actual subset of the data you are actually interested in instead of the full data set, which can be in the magnitude of gigabytes or even larger. This technology of cloud-native file formats is usually best used with Browsers, which is the users’ main interface to the internet and the cloud. There the main language is JavaScript. Therefore, this talk will give a high-level introduction about the relevant cloud-native file formats and show whether and how you can make use of these files in client-side JavaScript: - COG: Cloud-Optimized GeoTiff (cogeo.org) - COPC: Cloud-Optimized Point Clouds (copc.io) - Flatgeobuff (flatgeobuf.org) - GeoParquet (github.com/opengeospatial/geoparquet) - STAC: SpatioTemporal Asset Catalog (stacspec.org) - Zarr (zarr.readthedocs.io) This talk will dig into the available open-source libraries and, if JavaScript implementations are available, show their functionality based on examples. If multiple options are available, a high-level comparison will show the main differences in functionality. For COGs for example, we’ll compare the capabilities of the popular mapping libraries Leaflet, OpenLayers and MapLibre GL.

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description: Assigning semantic labels to points within a point cloud aids in both visual interpretation of the data and as a preprocessing step to other forms of analysis like building footprint extraction, hydrological modeling, and biomass estimation. Our talk will focus primarily on earth observation data and airborne lidar data sources in particular, where labels are commonly aligned with those classes specified in the ASPRS LAS specification (e.g., ground, vegetation, and building), but we are also beginning to explore the extension of these same methods to data generated by commodity, consumer-grade devices like iPhones. For many years, hand-tuned models have been developed for this segmentation task, building on reasonable assumptions about the data. For example, ground points should include those lowest elevation returns within a local window or building segments should typically be planar. Within the past decade, we have seen a surge in AI/ML powered models that are able in many cases of outperforming the prior methods, being able to learn novel features and adapt to the intrinsic variability of data. We will provide an overview of the open source ecosystem powering this trend, from benchmark datasets like US3D and DALES to machine learning frameworks (i.e., PyTorch and Tensorflow) and key libraries such as PDAL, Open3D, and PyG.

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name: Open Source Point Cloud Semantic Segmentation Using AI/ML


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description: What's new in MapLibre version 2? We'll explore all the latest features of the library, including its new 3D capabilities. We'll also show you get started with MapLibre in whichever frameworks you choose to work in. This talk will be useful for beginners through to experienced web mappers interested in MapLibre. Along with the 3D capabilities, there are new styling functions and also the move from JavaScript to Typescript to discuss. We'll show you some snippets of these new features and demonstrate the power of MapLibre. For those getting started with web mapping or learning new frameworks, we will show you how to use MapLibre in your own application. We will introduce practical code examples in React, Vue.js, Angular or Svelte, creating a simple map component. By the end of this talk, you should have all you need to get started building apps with MapLibre and the main JavaScript frameworks.

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name: MapLibre GL 2.x - JavaScript maps with React, Vue.js, Svelte or Angular


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description: This talk will describe some of the tools and tricks used by the team at Sparkgeo to gather, clean, and represent global resource data (minerals, wood, and water) for use in video game development. One of the resources collected by the team used the STAC package for the Joint Research Centre - Global Surface Water data product to deliver water occurrence as part of the end product. This talk will describe how to use a STAC package like JRC to access and transform cloud datasets before moving on to additional datasets such as limestone, gold, and forest cover. These other datasets required a different geospatial approach to ensure that the resources were appropriately represented in the video game. Nevertheless, each dataset required gathering from the internet and performing an Extract-Transform-Load (ETL) task. The use of open-source geoprocessing tools, data science methods, and data delivery formats helped ensure real-world data is used in video games. Community standards

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name: Cleaning and processing global resource data for game development


State of GeoNode 2022

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description: GeoNode is a Web Spatial Content Management System based entirely on Open Source tools whose purpose is to promote the sharing of data and their management in a simple environment where even non-expert users of GIS technologies can view, edit, manage, and share spatial data, maps, prints and documents attached. This presentation provides a summary of new features added to GeoNode in the year up to the latest releases of GeoNode together with a glimpse of what we have planned for next year and beyond, straight from the core developers. The purpose of this presentation is to introduce the attendees to those which are the GeoNode current capabilities and to some practical use cases of particular interest in order to also highlight the possibility of customization and integration. Finally, we will provide a summary of new features added to GeoNode in the last release up to the latest releases of GeoNode together with a glimpse of what we have planned for next year and beyond, straight from the core developers.

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name: Open Source Geospatial Foundation (OSGeo)


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description: Mining industry professionals are in a constant need of simple and efficient software solutions for drillhole visualization, management, and edition. Although several Open Source solutions are offered to partially fulfill the need, none has propagated into common professional use. In partnership with a team of mining industry leaders including Orano, Evolution Mining, Sandfire Resources, Kenex, the University of Western Australia, NordGold, GoldSpot and the CEA, Oslandia has formed a consortium in 2021 to answer the demand. Oslandia has since then been developing a high performance drillhole data visualization QGIS plugin that combines 3D, cross-section, map, and log views into a fully synchronous system. Moreover, users are able to connect OpenLog directly to their existing drillhole databases such as Acquire, Datashed or Geotic. This talk will succinctly present the functionalities of OpenLog as well as its primary use cases, contribution to QGIS 3D data visualization technology, development roadmap, and future prospects.

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name: OpenLog - Open Source drillhole data visualization in QGIS


Introduction to STAC API plugin in QGIS

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description: STAC or SpatialTemporal Asset Catalog is now a popular option for providers wishing to create accessible catalogs of spatiotemporal asset data for end users. STAC aims to create a standardized and performant way for providers to expose their spatiotemporal asset data, and for users to ingest that data. A 'spatiotemporal asset' is any file that represents information about the earth captured in a certain space and time. Since the development of STAC started in 2007, the STAC ecosystem was not able to use the STAC data in desktop softwares. Recently through collaboration between Kartoza and Microsoft, a QGIS (a desktop GIS application) plugin called “STAC API Browser” was developed to bridge the gap between QGIS users and STAC data. Now using “STAC API Browser” users can access, download, analyze and use a vast amount of imagery data offered by various STAC specification providers, such as Microsoft Planetary Computer. The aim of this talk is to introduce the “STAC API Browser” plugin, give a guide on how to use the plugin inside QGIS, showcase cool things that the plugin supports and how users/developers can collaborate on the plugin project. On top of all, we will also look at how to use the QGIS temporal controller feature with the added STAC data from the plugin.

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Realtime multi-user mapping with MUDraw

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description: Mapping is a private operations. It is done with several different local tools and usually by one person at a time. Yet we are used to have realtime multiuser editing of spreadsheets, documents and presentations. MUDraw tries to define a protocol to enable multiuser editing of features on a map and make it available as a library for both Leaflet as well as Maplibre (and enabling cross-library data editing) in order to make map editing a group activity. It relies on the client(s) and a server part written in Python/FastAPI that can be used independently from the infrastructure in which the communication is used and can set up a persistence layer taht is connected directly to github or other storage facilities.The idea of this tool is to be able to integrate it into UMap in order to make it a more fun to use tool, but also in a longer perspective, part of the Public History Toolkit OpenHistoryMap is developing.

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description: Point cloud data are an important component of geospatial data workflows, but software and formats to manage it often have compromises that work against efficient storage and processing of data. While commonly seen characterizing topographic information in LiDAR applications, point cloud data are an important driver of change detection applications in SAR workflows and provide important raw data to bring the physical world to the augmented one through handset capture on devices like the iPhone 12+. COPC.io is an open specification by Hobu, Inc. for organizing point cloud data in LAZ that allows it to be streamable over HTTP, selectable for resolution or spatial window, and adaptable to existing point cloud workflows in a backward compatible way. We will discuss the design choices and evolution of COPC, demonstrate its use in PDAL and QGIS scenarios, and show how COPC can be used in the cloud for management of massive point cloud collections.

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name: Cloud Optimized Point Cloud: Compressed, Geospatial, Lossless and Compatible Data Organization for Analysis Ready Point Cloud Data


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description: This talk will introduce a new Spatiotemporal Asset Catalog (STAC) extension for geospatial video assets. The extension is designed to standardize the metadata for all types of overhead geospatial video assets, including those collected by satellite, UAV, or airborne sensors, while accommodating situations in which the sensor moves throughout the video. The talk will include a brief overview of the STAC ecosystem (elements and extensions), and explain the Video extension’s schema. In addition, there will be a complete end-to-end demonstration including data preprocessing and STAC item creation (entirely using FOSS tools), and a FOSS method for displaying STAC Video extension-enabled items on an interactive map. The audience need not prepare in any way for this introductory presentation, although some background in STAC and geospatial video might be beneficial. Otherwise, this talk has a broad appeal for data professionals through to frontend developers who are keen to add some motion to their maps!

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name: Maps in Motion: Introduction to the STAC Video Extension


Serverless Geospatial

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description: More and more geospatial operations are happening in the cloud and often these processes are serverless. Whether your focus is on transportation logistics, agriculture, climate change analytics, or real estate; it is now possible to do geospatial computing in the cloud for both small and large projects. With serverless cloud compute options for data storage, compute, and desktop; we can now host our entire infrastructure completely serverless. Let's review the current state of geospatial serverless cloud infrastructure by exploring a stack consisting of OGC publishing, QGIS Desktop for cartography and client-side processing, TiTiler tile server, STAC data catalog, and a combination of data storage options. For OGC publishing, we'll review MapServer and Koop using Lambda plus API Gateway. Similarly TiTiler can also be built with Lambda and API Gateway. QGIS Desktop can now be run in the cloud through AWS Workspaces or AppStream. For our data storage, we can use a combination of S3, Aurora PostGIS, and Redshift.

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description: deck.gl is one of the most advanced open-source libraries for data visualization. In this session we will discuss how its WebGL-powered engine can be used to perform visual exploratory data analysis of large datasets. This library is quickly becoming one of the most used in the FOSS4G world due to its open governance model and compatibility with other mapping libraries like MapLibre GL JS. We will learn how a deck.gl visualization is structured and what the main concepts are: views, layers and accessors. We will discuss its reactive architecture and how it can be used to build simple scripting prototypes and complex applications with modern JavaScript frameworks like React, Angular or Vue.js. We will present different examples ranging from simple layer visualizations to thematic and choropleth maps to advanced interactive 3D visualizations including animations. Finally we will focus on specific use cases for large data visualization, from datasets with hundreds of thousands of features with data formats like GeoJSON to datasets with billions of features using advanced tiling schemes.

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name: An introduction to deck.gl for data visualization


uk: Комп'ютерні науки

description: This talk presents the current state of MovingPandas (movingpandas.org) and related movement data analysis tools. MovingPandas has been growing steadily since its first publication in 2018 (with more than 24 contributors to date). Building on GeoPandas and GeoViews, MovingPandas provides movement data analysis tools that support efficient exploratory data analysis through interactive (visual) analysis. Early functionality and demos were focused on dealing with GPS tracking data (including vehicle and animal tracks). This talk presents recent developments towards supporting other track data, including examples from sports tracking (movement in real space, extracted from video footage) and eye or mouse tracking (movement in virtual space). Among many other details, this includes support for local coordinate systems, integration of context beyond geographic base maps, as well as trajectory generalization, segmentation, and distance measures. Finally, we revisit the origins of MovingPandas: the QGIS plugin Trajectools; and review the steps necessary to bring MovingPandas' trajectory analysis tools to QGIS.

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name: State of MovingPandas: analyze all those tracks (not just GPS)


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description: EarthDaily Analytics is building a powerful new constellation that will collect scientific-grade, 5 meter resolution imagery of the planet in a unique combination of 22 spectral bands using 3 different camera types, covering a broad spectral range from visible to thermal wavelengths. The mission will be launched in 2023 and will allow us to see the Earth’s global land mass each day in a wholly new way with more spectral bands, higher revisit, and at a higher resolution than ever before. It will allow us to monitor, detect changes, alert, and predict what is happening anywhere on the planet to help with some of world’s most pressing challenges in agriculture, Environmental, Social and Governance (ESG), and disaster prevention and recovery. This mission has been made possible by a near-perfect convergence of three major technology breakthroughs in the last 10 years: 1) lower cost satellite launch and manufacturing, 2) advancements in computer vision and machine learning to support automation of petabyte scale processing, and 3) cloud compute power and storage necessary to drive the processing and calibration of trillions of pixels each day. Together these three emerging technologies are key to driving next generation geospatial insights, but to bring them together requires a software solution capable of handing the complexity of raw satellite with automation driven by machine learning, and cloud-based Big Geo Data pipelines for cost-effective scale and latency. At EarthDaily Analytics, our software solution has been made possible by leveraging many open source software packages to form the backbone for our satellite processing, calibration and quality services called the EarthPipeline. Together with open source packages and custom machine learning and computer vision approaches, we are working on delivering true scientific satellite image products that can be applied directly to algorithms without the need for very costly (and dreaded) end user data normalization and correction procedures. This talk will focus on how EarthDaily Analytics uses open source packages and machine learning to create normalized scientific quality data, and will also provide some example applications of how the data can be used.

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name: "Earth in Colour" with EarthDaily Analytics


State of deegree: What's new in 2022

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description: This presentation provides a summary of new features added to deegree in the latest releases of deegree webservices and deegree OGC API together with a glimpse of what we have planned for next year and beyond. Initiated in 2002 the OSGeo project deegree has developed over the last 20 years to an important building block for Spatial Data Infrastructures (SDI). As the implementation of the INSPIRE directive is fully underway it requires stable and mature software solutions based on OGC standards such as GML, WFS and WMS. One of the goals of the deegree project is to provide implementation of those standards. In this talk we will focus on the recent improvements available in deegree webservices and our updated roadmap for full Java 11 support comming with version 3.5. We will show how the support for OGC API - Features Core, part 1 and 2 has been implemented and can be used with existing configurations. Finally we will show the directions for the project and what future developments are currently planned.

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