uk: Комп'ютерні науки

description: There has been an explosion of research into computer vision focused on deep learning. These significant advances in image classification, object detection and image segmentation have profound implications for foundational mapping applications. Recent open source initiatives such as SpaceNet have strived to direct more research and development towards remote sensing applications. GIS practitioners need to understand and engage the research community to help structure the application of these new techniques against geospatial problems. tt is difficult translate mission requirements to machine learning evaluation metrics, and vice versa. For example, in the computer vision community, most results are described by certain image specific metrics such as mAP, F1Score, Precision and Recall. Alternatively, a GIS practitioner may want to incorporate machine learning capabilities into their workflow, but not know what level of performance is necessary for the specific mission. We will discuss a framework for defining levels of practitioners augmentation that will allow end-user groups and machine learning researchers to better understand each other and help direct the application of these advanced algorithms against geospatial problems.

uk: вхід без авторизації

name: Accelerating Open Source Geospatial Machine Learning


Matthew Hanson

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: The SpatioTemporal Asset Catalog specification is an emerging standard for to cataloging geospatial data from different sources, and a specification for serving that data in an API. This talk will be a detailed overview of STAC illustrating it's usefullness in integration with cloud-based processing workflows. It will cover the core set of metadata fields for STAC Catalogs, Collections, and Items, along with available extensions for describing different types of data (EO, SAR, Point Cloud, etc.). With the basics of STAC in hand, we will then go over the available Open Source tools that are available for working with STAC metadata: validators, compliant APIs, client command line tools and libraries for search, access, and exploitation. Finally we will give an overview of available STAC catalogs for searching and accessing publicly available datasets (e.g., Landsat-8, Sentinel-1/2, NAIP) using these Open Source tools. After this talk you should have a good understanding of the metadata used to describe satellite imagery and be able to use existing open-source tools to immediately search and access this data.

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: STAC and OS Ecosystem: Spatio Temporal Asset Catalog specification and software ecosystem

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: In a disaster or humanitarian relief context, time obviously matters. This talk will show how, without concern for the details of servers and storage, you can use small amounts of code to quickly build powerful solutions, using a prototype disaster response pipeline as an example.

uk: вхід без авторизації

name: Simple is Better: An Intro to Event-Driven Serverless Architectures for Faster Disaster Response


uk: Комп'ютерні науки

description: A recent fun blog post turned into an idea for synthesizing imagery training data for ML applications. In the post we presented a method for identifying sasquatch using cloud native geospatial methods and tools. This talk will describe the cloud native approach we took and the opensource tools that were used. We will then describe and demonstrate an idea to create synthetic satellite imagery training data using opensource libraries and tools.

uk: вхід без авторизації

name: Finding Sasquatch or how to fake a moon landing


uk: Комп'ютерні науки

description: 2018 saw the release of [Julia](https://julialang.org/) 1.0, a high-level, high-productivity programming language, with the performance of a low-level language like C. That means looping over all features or cells and applying your own functions is encouraged. The [JuliaGeo](http://juliageo.org/) organization was first started in 2015 to provide support for working with geospatial data in the Julia programming language. JuliaGeo currently provides high-level APIs with comprehensive support for OSGeo libraries like GDAL, GEOS and PROJ. In this talk, we introduce Julia and the JuliaGeo packages, showcase interactive workflows, and talk about next steps.

uk: вхід без авторизації

name: JuliaGeo: A Fresh Approach to Geospatial Computing


uk: Комп'ютерні науки

description: Having been around for two decades, QGIS clearly is an organically grown project. It has primarily been fulfilling the various special needs of its developers. From an outsider's perspective, it is an amazingly rich patchwork of features. However, some are deeply hidden in numerous layers of user interface elements, requiring intense training for getting used to. Others are only accessibly through APIs, requiring not only training but also programming skills. Being confronted with QGIS as professional users on a regular basis, we thought about what would make working with QGIS more attractive. What if QGIS has a pleasant, coherent theme, including not only colors but also icons? What if QGIS had the ability to store workbench configurations? What if QGIS had dedicated interface configurations for specific workflows? What if much more of the API's functionality was accessible through the GUI in a well-organized way? How could QGIS work in a useful manner with ribbons? How could the incredible amount of dialogs be tamed into tabs? We demonstrate (live) a series of user interface experiments - all of which are or will be [available online](https://github.com/qgist) as plugins or patch sets. We seek a conversation with the audience.

uk: вхід без авторизації

name: Enhancing & re-designing the QGIS user interface - a deep dive


CubeSats, FOSS4G, and cubesatdata.com

uk: Комп'ютерні науки

description: Over the last several years, Element 84 has been centrally involved in NASA’s transition to the cloud, supporting their Earth Observing System (EOS) and Earthdata programs representing over 20PBs of remote sensing data and preparing for an order of magnitude increase with upcoming missions. Based on this experience, and backed by a variety of great open-source software, we have created a self-service remote sensing data management platform for smaller projects and teams. Cubesatdata.com is designed to support data management following downlink of L0 data and includes end-to-end system architecture, cloud archive optimization, data pipeline processing and archives of convenience, as well as a robust user-interface for search, discovery, and visualizations. This managed service provides a lower cost of entry for academic institutions, nonprofits, and other small businesses who lack the domain expertise or the desire to support an end-to-end data management system. This talk will focus on how the Cubesatdata.com service works and what open-source software made it possible.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: SAGA (System for Automated Geoscientific Analyses) is an open source geographic information system (GIS) used for editing and analysing spatial data. It includes a large number of modules for the analysis of vector (point, line and polygon), table, grid and image data. Among others the package includes modules for geostatistics, image classification, projections, simulation of dynamic processes (hydrology, landscape development) and terrain analysis. The functionality can be accessed through a GUI, the command line or by using the C++ API. SAGA has been in development since 2001, and the centre of SAGA development is located in the Institute of Geography at the University of Hamburg, with contributions from the growing world wide community. This talk will focus on the new features that have been added since the previous LTR version (2.3.2) which is the version used in QGis processing.

uk: вхід без авторизації

name:
SAGA - System for Automated Geoscientific Analysis: Version 7.3.0
LTR


uk: Комп'ютерні науки

description: The INSPIRE Reference Validator is the tool adopted by EU Member States to validate the resources of their Spatial Data Infrastructures. It is an implementation of the ETF, an open source testing framework based on ISO and OGC standards, which performs tests organized into Executable Test Suites (ETS) using SoapUI, BaseX and TEAM Engine. The ETF can be used via either a web application or a REST API; a Docker container is also available for quick deployment. The INSPIRE Reference Validator, recently deployed on the cloud, offers many open source ETS to test data sets, metadata, View Services (WMS, WMTS), Download Services (Atom, WFS, WCS, SOS) and Discovery Services (CSW) against the interoperability requirements set by the INSPIRE Technical Guidance documents. Starting from the context of INSPIRE Action 2017.4 on Validation and conformity testing, the talk will present the latest developments of the ETS and ETF (including the governance of the software project) and describe the future plans.

uk: вхід без авторизації

name: INSPIRE Reference Validator: status and next steps


uk: Комп'ютерні науки

description: Indexed 3d Scene Layers (I3S), is an Open Geospatial Consortium (OGC) standard for streaming massive amounts of heterogeneously distributed geospatial data for an interactive experience for web, desktop, mobile and embedded clients. I3S supports storage and transmission of very large data consisting of millions of discrete 3D objects with attributes, integrated surface meshes and point cloud data covering vast geographic areas. Ability to stream millions of triangles and billions of point cloud, regardless of platform constraints, has opened a new 3D graphics and visual computing front in the geospatial world, where there is an increasing demand for high quality 3D application. In this talk, we will describe principles and concepts for organizing geospatial data based on bounding volume hierarchy (BVH), various spatial subdivision algorithms, efficient mesh representation, as well as exploring point cloud, mesh and texture compression/decompression techniques, while keeping the content friendly to GPUs. We will also demonstrate various examples of the different layer types and profiles that are supported in I3S.

uk: вхід без авторизації

name: I3S – an open standard to bring 3D to Web, Desktop and Mobile platforms


uk: Комп'ютерні науки

description: In order to increase interoperability and facilitate the reusing of geospatial data, it is proposed a methodology of publishing INSPIRE-compliant datasets as Linked Data, using the RDF format and various ontologies such as the ones derived from the ARE3NA for the Annex I themes, or GeoSPARQL from the OGC. This methodology would cover the whole process of generating the RDF triples from GML sources, setting up a triple-store to persist the information, and issuing SPARQL queries to the exposed endpoint. A working example would be presented using the Spanish CNIG endpoint, where several datasets from the Annex I are hosted. Then a series of queries joining external information from other endpoint, like DBPedia or GeoNames, would be used as a mean to demonstrate the interoperable capabilities and the potential applications to enrich spatial data, extract meaningful insights from it and use it to support information systems.

uk: вхід без авторизації

name: Publication of Inspire Datasets as Linked Data


Getting INSPIRE'd with Hale Studio

uk: Комп'ютерні науки

description: In this talk, we explain how open source platforms will enable data users to truly utilize geospatial data in Europe. Open platforms based on standards, as INSPIRE, will enable new business models, applications and markets. However, there are still challenges in building them effectively. A key component of effective INSPIRE implementation is hale studio, wetransform's open source tool for geodata harmonization. With its declarative and interactive workflow, it provides users with the ability to easily transform complex data. It has been designed from the ground-up to support specifications such as OGC GML, ALKIS, INSPIRE, and others. It has been applied to thousands of harmonisation projects. In the talk, we will highlight recent INSPIRE data harmonisation projects, such as: 1) Reference transformation project creation for 3A to INSPIRE Data 2) INSPIRE compliant data generation (Human Health and Safety, Hydrography, Transport Networks and Elevation) from WFS It will specify the general and case-specific challenges faced and how they were overcome. We will then delve into the future of hale studio, and which features will be included later based on our observations from the harmonization projects we have undertaken.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The new Forest Inventory ESTimation and Analysis system (nFIESTA) is an open-source PostgreSQL extension capable to produce estimates of target parameters describing the condition of forests and its development. The specificity of the nFIESTA estimation system is that it allows for an analysis of large datasets sourced by National Forest Inventories (NFIs) of many (not only European) countries. Such an integrated database contains sample plot data that use to be collected following a number of different sampling and survey designs, with spatial distribution and timing that vary from country to country. Using such a system the estimates of forest and landscape parameters can be obtained at a level of detail starting from a relatively small areas - as small as several hundreds of sq. kilometers. From the temporal point of view, the current implementation supports estimations for periods of one calendar year or longer. The system was designed and developed so it can use various sources of auxiliary information (typically GIS maps produced by remote sensing methods). The SW has been developed as part of the Diabolo project (http://diabolo-project.eu/) funded by the European Union’s Horizon 2020 research and innovation programme. Here is the link to the git repository: https://gitlab.com/nfiesta and presentation slides: [odp](https://gitlab.com/nfiesta/nfiesta_pg/wikis/myuploads/FOSS4G_Bucharest/nFIESTA__FOSS4G_2019.odp), [pdf](https://gitlab.com/nfiesta/nfiesta_pg/wikis/myuploads/FOSS4G_Bucharest/nFIESTA__FOSS4G_2019.pdf).

uk: вхід без авторизації

name: The new Forest Inventory Estimation and Analysis system


Demystifying AI in Geo

uk: Комп'ютерні науки

description: You are probably familiar with the terms artificial intelligence (AI), machine learning (ML) and deep learning (DL). However, do you really know how they work with GIS? In this session, we will use Python and various libraries to illustrate how artificial intelligence is used to detect deep and complex spatiotemporal patterns in data, and how to predict geospatial events of interest. This talk will cover several scenarios of applying the latest machine learning and deep learning techniques to geospatial data, including applying object detention using satellite imagery, detecting objects in videos and other workflows to incorporate these data sciences.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The talk presents the Planet overview, with a focus on Planet’s mission and vision and how satellite data users leverage our products and services. We will emphasis on Planet’s products - PlanetScope and SkaySat imagery Planet Analytics. Key verticals and uses cases.

uk: вхід без авторизації

name: Planet - how GIS/RS users can leverage the product and services


uk: Комп'ютерні науки

description: The talk aims to share with other participants how Map Kibera in partnership with World Bank are helping Counties in Kenya to map their projects. Producing maps to be used during participatory Budgeting forums with the public. The maps help inform what other projects citizens want implemented for them in their respective areas after knowing what’s already in place. Kindly see below http://www.mapkibera.org/blog/2018/07/17/mapping-counties-with-participatory-budgeting/ http://www.mapkibera.org/blog/2018/05/30/citizens-and-government-map-makueni-county/

uk: вхід без авторизації

name: Open County Mapping for Accountability and Service Delivery


#(G)EOHACK 19

uk: Комп'ютерні науки

description: (G)EO Hack 19 is an innovative hackathon at the interface of traditional and scientific knowledge that will take place during the GEO Ministerial Summit.The EO-based challenges will be co-designed by indigenous youth communities throughout the world to encourage the co-development of innovative EO-based applications that are locally relevant and enhance the communities way of learning. The primary goals of the activity are to promote the use of open EO data among indigenous communities and ultimately to co-design locally relevant free and open source software that promote new means for aligning local/ traditional knowledge and science co-production across cultural and generational lines.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The Copernicus data provided on a free, full and open access basis are an invaluable asset for both established and new businesses. EU funded projects such as e-shape and PARSEC aim to support developers and entrepreneurs through solid access to knowledge, technology, capital and markets. e-shape endeavours to build capacity across the whole value chain for the exploitation of EO data and services as well as to boost application sustainability. PARSEC, a holistic acceleration programme, aspires to provide start-ups and SMEs with the necessary resources to develop and launch their own EO based ideas into the market.

uk: вхід без авторизації

name: Copernicus-enabled business opportunities: e-shape & PARSEC, key projects at your service


Remote Sensing Deltas

uk: Комп'ютерні науки

description: Deltas are the most productive and economically important global ecosystems associated with some of the largest coastal marine fisheries and the majority of global wetlands. They also the most extensive coastal lowlands threatened by climate change and human activities such as agriculture, navigation, fisheries, forestry, fossil energy production and industrial urban development. Under climate- and human-induced sea level rise, sediment trapping behind dams and destruction of natural protective ecosystems, deltas are currently sinking at accelerating rates. Deltas maintenance and reconstruction depends on effective monitoring of vast and intricate areas of channels, lakes, wetlands, beaches, and islands that cannot be effectively accomplished on the ground without prohibitive expense. If ignored, disappearance of deltas will soon have devastating consequences for the livelihood of the half billion people who live in these coastal regions and lead to mass migration. I’ll present ideas & initiatives that seek to monitor deltas remotely and plug spatially-distributed data into models of hydrology, morphology, and ecosystem dynamics using remotely-sensed data from satellite missions that are complemented by ground sensor networks.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: As intention to facilitate faster establishment of cadastral databases, different projects were initiated to support rapid automated approach for boundary extraction from remotely sensed imagery. Such project is the EU funded “its4land”, developed as a joint venture between several organizations including University of Twente. Despite the current advancement of the modern segmentation algorithms, there are imperfections in the output that have to be further manually filtered out. Therefore, a QGIS plugin called BoundaryDelineation was designed and developed to support an interactive delineation of visible (cadastral) boundaries to speed-up the process. The plugin supports the full pipeline of loading, picking and drawing segments, and saving to a remote server the final validated output, which allows rapid reduction of the mouse clicks compared to manual delineation, which affects the overall speed of creation of cadastral entities. The presentation will consist of a general overview of the its4land project, and main focus on the usage of the BoundaryDelineation QGIS plugin as a more general-purpose assistant in boundary delineation.

uk: вхід без авторизації

name: Automating Image-Based Boundary Delineation: The BoundaryDelineation QGIS plugin


EO Services: From Research to Business

uk: Комп'ютерні науки

description: Content of the European Association of Remote Sensing Companies: 1. About EARSC 2. The Value in Earth Observations 3. Supporting Businesses - The “Research to Business” Solution 4. Open Source Initiative 5. EARSC in the Region

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Copernicus offers, besides the well-known Sentinel satellite data, a wealth of domain-specific open environmental data sets, e.g. data on climate, wildfires, air quality, floods. One of the most popular data set useful for many environmental applications is the climate reanalysis ERA5 produced from the European Centre for Medium Range Weather Forecasts (ECMWF). Improvements in the spatial and temporal resolutions lead to an increase of the entire data volume up to 5 PBs. Additionally to the sheer amount of data, meteorological and climate data have a certain complexity, especially for “non-expert” users, as data can have up to five dimensions and two time dimensions. The current situation shows that a full, free and open data policy is one important prerequisite, but the key to fully unleash the potential is making the data ‘accessible’. If open data is not accessible, it becomes open data that is locked away in large data silos. However, making meteorological and climate data “accessible” means more than just improving data access. It requires improvements and developments along the entire data processing chain, including the development of example workflows and reproducible training materials as well as developing / enhancing mainstream open-source software tools. In this context, the FOSS4G spirit is vital. This talk puts the spotlight on open meteorological and climate data. Current ‘accessibility’ challenges and future needs will be discussed in order to make open meteorological and climate data better accessible to everyone.

uk: вхід без авторизації

name: Open Meteorological and Climate Data: Building Bridges between user communities!


The FOSS4G Journey: GeoCat loves FOSS4G

uk: Комп'ютерні науки

description: Open geospatial is an amazing journey. Join GeoCat in a look at what makes this community great, and the new opportunities for open source to thrive. We also have an important project announcement to share.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The FOSS4G community is much more than OS Software. The community, while small globally, has had, and continues to have an outsized impact on science using geospatial data. This impact starts with Open Ideas: the community fosters the free-flow exchange of ideas that lead to Open Standards for interoperability, Open Data for democratizing data access, and Open Source Software for the use and analysis of data. Science fields wishing to leverage remote sensing data has historically suffered from several challenges. Archives of remote sensing data can be large, and finding just the desired pieces of data can be time consuming, as every dataset is accessed in different ways. The data then often requires pre-processing and reformatting: reprojection, clipping, assembling time series, or even some more complex operations. Lastly, processing and analyzing these large datasets can take massive computing resources, making large scale studies difficult, if not impossible. The impact of all this on Open Science (the movement to make science more accessible on all levels) is clear - complex custom-made tools required for each dataset does not support making science more accessible. Now, the culmination of several advances in Open Standards, Open Data, and Open Source, along with cloud computing, are helping realize Open Science. And FOSS4G has been here all along, where many of these advances started as Open Ideas.

uk: вхід без авторизації

name: How Open Communities are Revolutionizing Science


EU's Copernicus@FOSS4G

uk: Комп'ютерні науки

description: The talk will introduce Copernicus - the European flagship Earth Observation programme - its support for European policy, the Copernicus startup and research programmes, and its contribution to the European Data Economy. The talk will also discuss the challenges and opportunities related to the large volumes of data being generated.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: This is the welcome speech of Mr. Dumitru Prunariu.

uk: вхід без авторизації

name: Welcome speech from Mr. Dumitru Prunariu, Romanian Space Agency


OSGeo: Your Open Source Compass

uk: Комп'ютерні науки

description: Very brief introduction to the huge geospatial universe. On this talk, we will cover most of OSGeo software and sibling initiatives to prove that Free and Open Source Solutions is not only a complete stack but the canonical solution when we want to have the best option possible.

uk: вхід без авторизації

name: Open Source Geospatial Foundation (OSGeo)


OSGeo Annual General Meeting

uk: Комп'ютерні науки

description: This is the AGM of OSGeo.

uk: вхід без авторизації


Awards ceremony

uk: Комп'ютерні науки

description: This is the FOSS4G 2019 awards ceremony: Eo Data Challenge award, Sol Katz award, developer award

uk: вхід без авторизації


Four-letter word

uk: Комп'ютерні науки

description: You keep using that word. I don't think it means what you think it means.

uk: вхід без авторизації


FOSS4G 2019 Closing Ceremony

uk: Комп'ютерні науки

description: This is the closing ceremony of FOSS4G2019 Bucharest!

uk: вхід без авторизації


EO Data Challenge proposal

uk: Комп'ютерні науки

description: During this 90 minutes slot, the results obtained by the teams at EO Data Challenge will shortly present their results. The following talks will be presented: Visualization and Analysis of Big Multidimensional Geospatial Data on the Web (Candan Eylül Kilsedar), STAC for the decentralized Web (Volker Mische), WebGL for in-browser GeoTIFF processing (Iván Sánchez Ortega), Citizen science in support of landslide detection and monitoring (Vasil Yordanov), EO Data Challenge results (Bang Pham Huu) EO Data Challenge results (Ivian Adrian Albu), LeafS - LEveraging Artificial Intelligence for Forest Sustainability (Teodora Selea).

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Many of you have asked about the news of fires in the amazon forest and may have a lot of other questions to ask. There are many questions and many different analyses to be made. For the purposes of this presentation, I will propose the following question: “Is the amazon forest being burned in large rates?” I will demonstrate a geoprocessing task using unwieldy data from the NASA FIRMS system (MODIS and VIIRS) and FOSS4G tools to try to answer the proposed question. What I will NOT do is discuss politics, ecology, or causes and effects. This is a complex subject and I believe one should ask questions focused on the decision one has to make. What are you trying to decide? What questions should you ask to help you in your decision? Maybe this presentation will provide you with a workflow and a few tools to do your own research.

uk: вхід без авторизації

name: The return of Crazy Data: Amazon forest fires


QGIS on the road

uk: Комп'ютерні науки

description: Telling the story of Ms Maya Mielina, a retired GIS analyst and passionate beekeeper, we will show you features that you might not even have imagined existed in QGIS and that will allow you to dramatically increase your efficiency.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The role of urban designers is to shape the physical features of a city with the goal of making the city functional and pleasant to live in. For this, the urban designer has to gather information about the current situation, design improvements, and communicate these to stakeholders. The use of space and the spatial relationships between physical features play a significant role in urban design, therefore much of the information that is collected and manipulated is georeferenced. In this paper we review and evaluate open source geospatial technologies that can be used for the collection, storage, manipulation and visualization of geospatial data in urban design projects. Based on this, an open geospatial toolbox for urban design projects is presented. We followed a scenario-based approach for collecting the requirements. Three researchers were asked to explain how they collect and use data for their urban design projects. Their backgrounds were in spatial planning and architecture. The first scenario involves an urban designer who is requested to guide and advise the local municipality on improvements in a neighborhood that has become dilapidated over time, and therefore unsafe. In the second scenario, the aim was to identify crime hotspots in a neighborhood and to propose preventative crime measures through environmental design. By analyzing the scenarios, we determined both functional and non-functional requirements, and categorized them into requirements related to data collection, data storage and management, and data visualisation respectively. A set of open source geospatial technologies were evaluated against these requirements. Tools were evaluated against requirements relevant to a category, e.g. for data storage and management, the user should be able to upload geospatial data, upload newer versions of the data, create and edit metadata about the data, and share the data in various formats using web services. Furthermore, the evaluation results show how tools meet individual requirements, i.e. tools that meet only one of several requirements were not excluded. The resulting open geospatial toolbox is modular, allowing urban designers to swap out a tool in a category for another one in that category, or swap out a tool that meets one requirement for another tool that meets that requirement. Each of the evaluated tools fulfilled the functional requirements to some degree; the real difference emerged from the non-functional requirements, such as perceived usability for novice users and documentation or support available. The results in this paper are based on requirements of urban designers, but are equally applicable for others who collect data at the neighbourhood level. Future work will focus on aspects of provenance for preserving and making data collected for urban design studies available for longitudinal studies.

uk: вхід без авторизації

name: Supporting Urban Design with Open Source Geospatial Technologies


uk: Комп'ютерні науки

description: Big Geo Data (BGD) constitute a challenge for monitoring and assessing the status of and changes in the natural and in the built environment where most of the people live. Nevertheless, to convert BGD into value, we need to fill the gap existing between the current form in which BGD are represented, which conveys information understandable to scientists and experts, and the needs of not experts, decision and policy makers who could exploit information derived of BGD if adequately summarised and explicitly visualised. To this end, new methods are needed for the discovery of the relevant geodata among huge repositories, the assessment of the geodata quality, and, finally, the synthesis of BGD to provide decision makers with consistent and comprehensible information to possibly discover hidden knowledge. Within the project “URBAN GEOmatics for Bulk data Generation, Data Assessment and Technology Awareness (URBAN GEO BIG DATA)” we are experimenting the definition and application of novel technological solutions for fostering the fruiting and synthesis of BGD by public administrators and the citizens of urban areas. Specifically, the project aims to improve the knowledge of urban areas by exploiting the fruition of the vast availability of EO data sources for soil consumption and long-term monitoring, and IoT data on mobility. A key aspect concerns the definition and implementation of novel methods for geo data dissemination through the application and extension of standard interoperable sharing protocols. In this paper, we focus on the experiments aimed at fostering the fruition of ground deformation time series derived through the Differential SAR Interferometry (DInSAR) measurements, in urban areas (i.e., Naples and Milan city areas). In particular, the Small BAseline Subset (SBAS) technique has been applied to generate DInSAR BGD displacement time series which can be served directly by applying OGC WMS and WFS requests, but the results achieved can be hardly interpretable by non-expert decision makers. To empower their potential fruition, we defined and implemented an automatic mechanism aimed at generating a qualitative visual temporal animation of the BGD time series of deformation synthetized by snapshot maps, generated with a reduced spatial and temporal resolution. They can be helpful for a non-expert to visually identifying at a glance the areas subject to deformations, without spending much of time analysing the single deformation time series. Useful knowledge is the mean deformation velocity map of the analysed areas. However, to follow the time evolution of the deformation, we have selected merely one single measurement per year. This is only a qualitative method for helping non-experts in identifying areas with large deformations. The paper will focus on this aspect describing its implementation details and characteristics.

uk: вхід без авторизації

name: Visualization of Big GeoData: An experiment with DINSAR deformation time series


uk: Комп'ютерні науки

description: Accessibility to primary health care (PHC) in developing countries is crucial and remains a challenge with conflicting statistics in Malawi. For instance, the Health Sector Strategic Plan II, 2017-2022 reports accessibility at 90 % while the Demographic Health Survey puts it at 56 %. The discrepancies emanate from multiple factors among which is failure to incorporate critical geographic cost factors like elevation, road networks, road conditions, etc. in the estimation models. This study, therefore, seeks to develop a PHC accessibility estimation model that incorporates cost spatial factors of elevation and road network distances using open source software and geospatial routing techniques.The accessibility analysis was evaluated using 2 step floating catchment area (2SFCA) model implemented using PostgreSQL/PostGIS and based on the pgr_dijkstraCost algorithm. The model score was expressed in terms of time of travel assuming walking as the mode of travel with a 1-hour threshold indicating acceptable accessibility. To improve accuracy, the road network data was exploded to 20 m node distances. 2SFCA creates two catchment areas called floats in each step.The first step determines the population falling within a specified cost threshold and the facility population ratio. In the second, for each household, the model determines services available within the specified cost threshold at facilities and adds it to the facility population ratio to derive an accessibility score. The 2SFCA score starts from 0 growing boundlessly with 0 indicating households not within the 1-hour threshold. Higher scores indicate access within 1-hour and to multiple facilities or multiple services within an hour or facility respectively.The 2SFCA model result scores ranged from 0 to 0.19, with 100 and 58 % of urban and rural households within 1-hour of a facility (2SFCA > 0) respectively and a district average of 62 %. 70 % of the urban households have access to multiple health facilities (2SFCA > 0.01) as opposed to only 16 % of the rural households. As such the findings provide, arguably, spatially objective PHC accessibility data to inform policy direction and also reveals accessibility to PHC in Malawi to be lower than reported. Besides the evaluation of PHC accessibility, the application of FOSS tools in this study, strengthens the case of their relevance in low resource contexts where computation power and electricity can be intermittent, making it difficult to run models that span multiple days. Using PostgreSQL/PostGIS for relational spatial analysis modeling made it possible to resume modelling after power outages. Thus, the study has successfully demonstrated utility of relational spatial analysis using open source technologies in low resource settings of the developing world. With improved computational capabilities such models can be used for national benchmarking of accessibility and hence provide concrete data on the provision of PHC and other applications

uk: вхід без авторизації

name: FOSS Technologies in Modelling Spatial Accessibility of Primary Health Care in Malawi


uk: Комп'ютерні науки

description: On a judicial basis of § 196 Baugesetzbuch (BauGB, 2018) every municipality in the Republic of Germany must publish standard land values in €/m² for the whole district area in a biennial cycle. The standard land values have to be derived comprehensively for different land use within a district. These are mainly residential areas, mixed-use zones (residential and commercial areas), industrial areas, cropland, grassland and forestry. The standard land values serve the taxation authorities to rate the hereditary real estate and also will play a major role for the future property tax (Löhr, 2018). With the help of Geographic Information Systems (GIS) all the necessary data for the derivation of the standard land values could be analyzed. This data consists of cadastral information (ALKIS) (AdV, 2005) for each municipality district like streets, buildings, land parcels, land development plans as well as geocoded data (Bill, 2016) about real estate transactions. According to the INSPIRE (Infrastructure for Spatial Information in Europe) directive (European Parliament, 2007) which aims to create a European spatial data infrastructure for a transparent common environmental policy the geodata representing the standard land values will be provided in the Web with services to query, visualize and download the datasets. The following work contributes to both requirements, the statutory determination of the standard land values answering the lawful necessity and the setting up of the generated geodata in the Web according to the demanded transparency of the INSPIRE directive. This thesis describes the development of automatizing the process of implementing, selecting, aggregating and layouting the relevant objects of the ALKIS data in an Open Source GIS (QGIS) via Python language. The standard land values will be visualized and presented in Web GIS (Seip et al, 2017). Therefore three different Web Clients will be compared according to performance and editing capabilities: QGIS Web Client (Open Source), Lizmap (Open Source) and ArcGIS Online (commercial). Additionally the two different Web GIS server solutions, QGIS Server and ArcGIS Online, will be described and evaluated.

uk: вхід без авторизації

name: Database Transformation, Cadastre Automatic Data Processing in QGIS and Implementation in Web GIS


uk: Комп'ютерні науки

description: Geomatics is the key resource in analyzing the deployment of publicly accessible Automated External Defibrillators (AED). Since AEDs are only effective if used within 6 minutes from the onset of an Out-of-Hospital Cardiac Arrest (OHCA), they have a limited area of effectiveness (i.e. ‘catchment area’, CA), that is traditionally computed as a circular surface with radius = 100m. The availability of open geospatial data related to roads network and edification on the territory allows to compute realistic catchment areas based on the effective distance along streets, which is a novel approach, never compared with the traditional method. Aim of this study was to compare the two approaches, and to evaluate if the territory analysis could support decision making about the mapping technique better suiting each device. The study was performed and validated on the territory of Lombardy (Italy, total surface 23’863.65 km2), and CAs were computed for 7458 known AEDs on the territory (at 28/02/2018). The analysis was performed exploiting open source software, specifically QGIS and PostGIS with pgRouting extension. Setting a limit of 200m for the realistic CAs, their mean surface for the considered dataset resulted close to that of the traditional circular area: 33’665 m2 against 31’416 m2. However, the spatial coverage of OHCAs (events occurring inside a CA, on the base of a georeferenced database of 45039 OHCAs occurred in Lombardy within 1/1/2015 and 31/12/2018) estimated considering circular areas (9.43%) is very different from that obtained considering realistic areas (15.35%). The distribution of the mapping error (surface of realistic CA – surface of circular CA) was studied, and its correlation with the characteristics of the surrounding territory was inspected. The considered attributes were: I) distance from the device to the nearest road; II) total length of the roads in the surrounding area; III) number of roads network nodes in the surrounding area; IV) percentage of edified surface in the surrounding area; surrounding area for II) to IV) was a circular area of 50, 100, 150, 200 and 250 m radius. The most correlated attributes were: I) R = -0.58 (p<0.05), and II) R = 0.65 (p<0.05) in 50m-radius area. Results suggest that circular CAs underestimate the spatial coverage of AEDs located nearby streets in a densely networked area, and in these cases realistic CAs, better suiting real-world scenario, are preferable. However, when AEDs are far from the streets, realistic mapping is not reliable, and the use of circular areas is preferable. This second situation is typical of large and isolated facilities (e.g. airports, sport facilities, warehouses), and the circular area better estimates the coverage of the facility itself. With known AEDs location, open data and open source software are reliable enough to decide which mapping technique will result in a better estimation of the CA.

uk: вхід без авторизації

name: Open data in health-geomatics: mapping and evaluating publicly accessible defibrillators


uk: Комп'ютерні науки

description: Social media have shown significant contribution in disaster reliefs. It could be very valuable source of the on-site information shared by the affected citizens. Particularly, Twitter is currently one of the most popular social media used for the exchange of information connected to the disasters. If this type of source is considered as a real-time crowdsourcing of crisis information, the spatial distribution of geolocated tweets related to an event can represent an early indicator of the severity of impact. This raises a question if rapid mapping teams could use additional information from Twitter before mapping. Would it be possible to estimate the outcome, to understand the affected zones and approximate level of impact? The aim of this paper is to explore the spatial distribution of the Twitter posts related to a disaster and to analyse their potential in providing fast insight regarding the impact. The focus of the analysis was on the tweets related to the hurricane Michael that happened in Florida, in the United States on October 2018. The crisis maps produced by Copernicus Emergency Management service were used as reference data and obtained results were compared with them. Copernicus EMS have produced twenty-five delineation maps over the coast of Florida. Six maps were delivered on the 11th of October and the rest of crisis maps were published on the 12th of October. The focus of this study is to explore the potential of Twitter’s crisis posts in providing information before the delivery of maps. The available message dataset consisted 8169 tweets posted from 10th until 15th October. The tweets published before the delivery of crisis maps that are inside of the crisis maps’ area, in total 30% of the available dataset, were analysed. Weights have been assigned to each tweet, on a base of the date of posting; i.e. newer posts were considered as more relevant. Spatial statistics have been performed with QGIS and GeoDa. For example, the QGIS plugin Hotspot was used to identify where statistically significant spatial clusters were present, more precisely, the zones with significant concentration of relevant posts were corresponding to areas with high impact of the hurricane. Comparisons of the results with the reference data have been performed and discussed, showing the potential value of these data for crisis mapping.

uk: вхід без авторизації

name: Fast insight about the severity of hurricane impact with spatial analysis of Twitter posts


uk: Комп'ютерні науки

description: During the last decades, production of Land Cover maps (LC) at a continental and global scale has increased thanks to the progress in Earth Observation capacities, as well as due to high demand for these maps for many applications (e.g. climate change monitoring). However, the usefulness of these maps strongly depends on their accuracy. Therefore, for a fruitful LC maps exploitation, accuracy assessments (i.e. validation and inter-comparison) must antedate. Spatial analysis of the errors should then complement the accuracy assessment to provide insights into the local errors patterns which may not be outlined by traditional accuracy assessment techniques. According to this, we propose here a comprehensive analysis to target accuracy of LCs by focusing on the African continent. Two datasets, GlobeLand30 (GLC30) at and CCI Land Cover - S2 Prototype Land Cover 20m Map Of Africa (CCI Prototype Africa), at 30m and 20m resolution respectively, were considered. Inter-comparison was performed by means of traditional accuracy indexes computed from the error matrix (i.e. Overall Accuracy, Producer’s and User’s accuracy etc). Harmonization of the two maps in terms of resolution and classification nomenclature is prerequisite for inter-comparison. This was achieved by taking advantage of QGIS functionalities (e.g. resampling). Results of the accuracy assessment provide overall quality metrics for the map as well as quality indicators for each LC class. Additionally, spatial association statistics were adopted to investigate local patterns of the errors. The analysis was performed by means of GRASS and custom developed Python scripts exploiting cutting-edge data analysis libraries such as Pandas, Dask, and PySAL. By “virtual” overlaying CCI with GLC30, we computed which classes of CCI are under each pixel of GLC30, and what is the pixel fraction of a CCI class at each GLC30 pixel. Results of the overlay were stored in a vector point file whose coordinates represent centers of pixels of GLC30. If the classes of GLC30 and CCI for a point are not the same this results in an error with magnitude represented by the pixel fraction itself. Error fractions at each GLC30 pixel were analysed by means of Local Indicators of Spatial Association (LISA) to map non-random pattern in the spatial distribution of the errors as well as to assess their intensity and spatial association typology. By considering the results of accuracy assessment and LISA outputs, a comprehensive comparison of the GLC30 or CCI Prototype Africa is achieved. The results provide a guideline for detecting source of the error, which is potentially useful for future LC production (i.e. sampling design of training data). Lastly, it has been demonstrated that processing of massive datasets for accuracy assessment can be accomplished with Free and Open Source Software (FOSS).

uk: вхід без авторизації

name: Inter-comparison of the Global Land Cover Maps in Africa Suplemented by Spatial Association of Errors


uk: Комп'ютерні науки

description: Narok Water and Sewerage Services Company (hereinafter, called NARWASSCO) supplies water at Narok town and Ololulung'a town in Kenya. As of February 2019,we have 4,689 water connections and 74,314m3 of water consumption in Narok, also have 580 water connections and 5,736m3 of water consumption in Ololulung'a. Total length of pipeline is 144.2km in Narok and 71.7km in Ololulung'a. NARWASSCO, currently uses FOSS4G to do data collection and data utilization for water supply services. For example, mapping of all water facilities in the company, and the collected data have been used to improve operations (application of new connection, leakage management, meter reading, customer care, etc.). We can say Narok water is the first water company which started to use FOSS4G in Kenya. <br> Our interesting is how water company use GIS inventory data to reduce Non-Revenue Water (NRW). NRW means physical losses(leakage) and commercial losses(meter reading error, illegal connection, etc.). We think GIS technology can contribute a lot of things for water supply services, so we would like to share our experience and get some idea from participants of FOSS4G conference.

uk: вхід без авторизації

name: Case Study of Non-Revenue Water Management of Narok water, Kenya


uk: Комп'ютерні науки

description:
Curricula in geography and GIS can be transformed by integrating open source GIS with critical human geography. This integration requires students to develop strong skills in assessing error and uncertainty and in questioning the powerful social implications of spatial information technologies, and requires faculty and students to develop new open curricula, features and algorithms to facilitate teaching introductory spatial analysis. Building on three semesters of experimentation with an advanced-level integrated open and critical GIS course, I have transformed a large introductory proprietary GIS course into a critical human geography course with open-source QGIS.
 Throughout the curricula, open GIS techniques are mapped to critical human geography concepts. Novice GIS students learn fundamental techniques while also learning to question the political economics, social and cultural forces, and instrumental logics that shape GIS data, software algorithms, visualizations, and social impacts. For example, students' first exercise is to practice radical cartography of disabled mobilities. On one hand, they learn fundamental techniques of the vector data model, planning a data collection schema, using a Leaflet application exposing the global positioning system location services on their phones, querying OpenStreetMap data, and creating a QGIS map visualization and print layout of wheelchair users' accessibility on campus. On the other hand, they confront and appreciate social power in construction of the built environment and campus maps, socially differentiated mobility in physical and cognitive space, and potential for GIS to challenge the status quo.
 What are the substantive differences between teaching GIS and teaching human geography with GIS, or between teaching open and proprietary GIS? Teaching human geography places critical questions about the society and society's interaction with spatial technology first, while the spatial technology itself is not black-boxed, infallible, or determinant. Taken together, students first ask how GIS can be used for critical inquiry and when GIS fails or delivers unsatisfactory results, they ask how open GIS can be altered to produce better answers. The fallibility of open GIS requires a pedagogical focus on assessing error and uncertainty: students must learn to confidently assess the integrity of each algorithms' results. The accessibility and malleability of open GIS enables students and faculty to change GIS as we use it, and open GIS can benefit from cohorts of novice students critically engaging with the technology. New forms of GIS users and applications emerge as students diffuse open GIS technology through other university courses and internships with grassroots and non-governmental organizations. New forms of open GIS software emerge as students help create more user-friendly open GIS for novices and repurpose open GIS for critical inquiry.

uk: вхід без авторизації

name: Human Geography with Open GIS: Transformative Introductory Higher Education Course


uk: Комп'ютерні науки

description: With the exponential growth of the variety, heterogeneity and volumes of geospatial data, a wide range of actors have increased their need to combine information from multiple sources such as private, crowdsourced and public sector repositories. The purpose of this study is to compare two sources currently relevant for Europe: INSPIRE and OpenStreetMap (OSM). In doing so, we start with a brief overview of the two data sources, outlining similarities and differences as well as pros and cons for data users. In force since 2007, INSPIRE is the Directive aiming to create a European (EU) Spatial Data Infrastructure (SDI) to be used for environmental policies. The Directive requires EU Member States (MS) to publish geospatial content falling under 34 cross-sectoral categories (themes) according to a Service-Oriented Architecture (SOA) approach based on ISO and OGC standards. On the other hand, OSM is the leading geospatial crowdsourcing project. Born in 2004 and counting more than 1 million active contributors, the project has produced a worldwide, large-scale geospatial database. In addition to their different approach (legislative, top-down vs. community-based, bottom-up), INSPIRE and OSM feature a number of technical differences. While OSM data is structured around a flat data model with attributes encoded as simple key/value pairs, defined and maintained by the OSM community in a flexible wiki environment, INSPIRE features complex data models for each of the 34 themes which have been rigorously defined and are maintained by the European Commission through a constant dialogue with INSPIRE stakeholders. Consequently, while INSPIRE proposes specific data formats for increased interoperability, OSM data can be retrieved into a variety of GIS-friendly encodings as well as through dedicated Application Programming Interfaces (APIs) which increase their reuse and the development of third-party applications. From a legal point of view, the open access license of OSM (available under the Open Database License) further facilitates the re-use of the data as well as the production and distribution of derived products at any spatial scale. Instead, being built on top of individual national infrastructures, INSPIRE data sets are available under a variety of different licenses, which overall may hinder the full usability of the infrastructure. Finally, whilst INSPIRE is by definition an authoritative source of quality-certified data, OSM quality can only be ensured by the very nature of its crowdsourced approach; nevertheless it has been proven in some cases to be comparable, if not even better, than authoritative sources. The paper will further develop this comparison by detailing the aforementioned elements on concrete use cases addressing specific EU MS and thematic data sets and discussing how to make the most out of the two sources. An analysis of available FOSS4G solutions to access, visualize, analyse and process INSPIRE and OSM data will be also provided.

uk: вхід без авторизації

name: Comparing INSPIRE and OpenStreetMap data: how to make the most out of the two worlds


uk: Комп'ютерні науки

description: SMODERP2D is a runoff-soil erosion physically-based distributed episodic model used for calculation and prediction processes at agricultural areas and small watersheds. The core of the model is a raster based cell-by-cell mass balance calculation which includes the key hydrological processes, such as effective precipitation, surface runoff and stream network routing. Effective precipitation, the forcing of the runoff and erosion processes, is reduced by a surface retention and an infiltration. Surface runoff consists of two components: slower sheet and concentrated rapid rill flow. Stream network routing is performed line-by-line in user predefined polyline layer. SMODERP is a long-term running project driven by the Department of Landscape Water Conservation at the Czech Technical University in Prague. At the beginning SMODERP has been developed as a surface runoff simulated by profile model (1D). Later the model has been redesigned using spatially distributed method. This version is named SMODERP2D. Ongoing development (https://github.com/storm-fsv-cvut/smoderp2d) is focused on obtaining parameters of the hydrological models, incorporating new infiltration and flow routing routines, and conceptualization of a rill flow and rill development. The model belongs to a family of so called GIS-based hydrological models utilizing capabilities of GIS software for geodata processing. Importantly, the SMODERP2D project is currently entering the open source world. Originally the model could be run only in proprietary Esri ArcGIS platform. A new version of the model presented by this contribution adds support for two key open source GIS platforms, GRASS GIS and QGIS. A newly developed GRASS module and QGIS plugin significantly increases accessibility of the SMODERP2D model for research purposes and also for engineering practice. Middle scale distributed hydrological models often encounter with a high computation costs and long model runtime. Long runtime is caused by high resolution input data which is easily available nowadays. The project also includes an experimental version of the SMODERP2D model enabling the parallelization of computations. This parallelization is done using TensorFlow, and its goal is to decrease the time needed for its run. It is supported by both CPU and GPU. Parallelization of computations is an important step towards providing SMODERP2D web processing services in order to allow quick and easy integration to highly specialized platforms such as Atlas Ltd.

uk: вхід без авторизації

name: SMODERP2D Soil Erosion Model Entering Open Source Era with GPU-based Parallelization


uk: Комп'ютерні науки

description: How can interactive maps help people plan great travel experiences? Destination travel is a popular way to experience the world for millions of people. Until now, little research has been conducted to establish what this type of user might actually need in a map-centric application. Most current approaches do not emphasize the role of space and place in travel preparation to help users understand the spatial dimensions of their travel plans. In addition, most of the available trip planning systems are proprietary in nature. Our work seeks to develop an application that goes beyond providing support for simple itinerary creation. We present results from a user survey to assess key spatially-supported travel task needs and design preferences. This data helps characterize the core functional needs for a FOSS web-GIS application and accompanying user interface designed specifically for destination travelers.

uk: вхід без авторизації

name: Destination Unknown: Design Dimensions of Open Source Travel Mapping Tools


uk: Комп'ютерні науки

description: Developing meaningful and interactive materials for the GIS classroom is a major challenge for educators. In this talk, I present a framework for developing GIS educational resources - including interactive in-class activities and out-of-class exercises - through an open and collaborative approach.

uk: вхід без авторизації

name: Casting a vision for LibreGeo: A framework for collaborative, open-access, and interactive GIS educational resources


uk: Комп'ютерні науки

description: A call center powered by an open GIS platform helps livestock herders in Northern Mali find pasture and water through the "Sustainable Technology Adaptation for Malian Pastoralists" (STAMP) programme. Herders can now access life-saving information by phoning call center agents, who in turn provide the outlook from Earth Observation and real-time field survey data to herders. This talk will show how the system was built, what we learned works (and doesn’t!), demonstrate the dashboard and show how to download and play with the datasets.

uk: вхід без авторизації

name: Show me that good grass: a call center for pastoralists in Northern Mali


uk: Комп'ютерні науки

description: The defining characteristic of point cloud data is that they are large, and tools such as [Entwine](https://entwine.io) and the Entwine Point Tile specification can help you overcome their bigness. We will discuss how we used Entwine and EPT to construct point cloud web services for the [USGS 3DEP LiDAR data](https://usgs.entwine.io) of the United States as an Amazon Public Dataset. We will also demonstrate how to leverage EPT web services with open source software such as [PDAL](https://pdal.io) to extract information, enhance data utility, and reduce data volume for tasks such as filtering, object identification, and visualization. You will learn about how these tools work together with others such as [GDAL](https://www.gdal.org/) and [PROJ](https://proj4.org/) to provide data management and processing pipelines for expansive data holdings.

uk: вхід без авторизації

name: Continental Scale Point Cloud Data Management with Entwine


uk: Комп'ютерні науки

description: After initial deployment of Croatian SGA Geoportal, it made a great impact on the usage of GIS viewer and OGC web services in the country. After a few thoushands registered users, it's time to analyze who is using it and how much. Also, there was a need for the administrators to be able to have reported on usage, and to deal with users and groups authorization roles. We achieved this with the combination of proven solutions such as GeoServer, Geofence and custom code.

uk: вхід без авторизації

name: Croation SGA Geoportal-users management and usage analysis

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: Comet Time Series (CometTS) is an open-source tool that facilitates analysis and visualization of satellite imagery time series. Such analysis can enable population estimation research, change detection methods, or natural disaster monitoring. Historically, analyzing large time series of satellite imagery was achieved using proprietary GIS tools or by time-intensive methods requiring substantial geospatial expertise. CometTS requires only a web browser, Python, and dependent packages to function, obviating the GIS requirement for time series analysis and visualization. CometTS provides a partially automated approach for analyzing a time series of satellite imagery in any user defined area of interest, then calculating relevant statistical quantities (e.g., measures of central tendency and variation), and visualizing their changes over time, all in a matter of seconds. The overall focus of this talk will be on the development and application of CometTS for two analyses: 1) analyzing dynamic population changes over time in Africa and the Middle East and 2) ccreating the first independent estimate of the number of persons without power over time in Puerto Rico following Hurricane Maria.

uk: вхід без авторизації

name: Comet Time Series (CometTS): Investigating Temporal Trends in a Time Series of Imagery with an Open Source Tool


uk: Комп'ютерні науки

description: The impact of land use and land use change and forestry (LULUCF) on soil organic carbon (SOC) stocks and greenhouse gas (GHG) emissions is important for both national GHG inventory reporting and worldwide strategy to offset GHG emissions. Within the Irish Soil Organic carbon and Land Use Mapping (SOLUM) project, Eurostat’s Land Use/Cover Area frame Survey (LUCAS) of 2015, LUCAS soil survey of 2009, and ancillary national open data were employed in an analytical GIS framework to develop spatially integrated soils and land use dataset specific for Ireland. In order to capture dominant Irish land uses that are not included in the EU wide LUCAS survey, the LUCAS dataset was reclassified to grassland intensification and management for IPCC reporting purposes using a formal, semi-automated, interpretation key approach. All types of land use were ascribed to a soil label using the open source Soil Information System (SIS) for Ireland and other ancillary geospatial data, thus generating LUSII, Land Use and Soil Inventory for Ireland. Thus LUSII builds on an existing EU wide Open Data set with local knowledge and GIS analysis to create a new more applicable national dataset.

uk: вхід без авторизації

name: Processing and refining European Land use Inventory LUCAS for National Needs: A Case study  – Land Use and Soil Inventory for Ireland, LUSII


uk: Комп'ютерні науки

description: Training spatio-temporal OSM-indicators based on the resilience core from Cutter (2016) and exploring the implications for urban planning in the light of revealed thematic tags in the region of Stuttgart. “Nobody on this planet is going to be untouched by the impacts of climate change” Rayendra Pachauri (2014) The overarching nature of building resilience across disciplines and its inherent positive mutual understanding due to the association with the immune system, also amongst the non-scientific community, makes it an attractive and increasing popular concept which everybody seems able to grasp its necessity. Hence there is an exponential increase, even limited down to the key words “urban resilience”, in scientific literature over the last decade. Moreover the concept is also taken up by the New Urban Agenda – Habitat III, the SDG goals and also the IPCC. Hand in hand with this development the definitions and operationalizations are innumerable and starting to lay a smoke screen above it. Conjoined, there is a clear lack of validation of resilience measures, including spatio-temporal aspects but also of the single component of it (Bakkensen 2017). Moreover, traditional data sources like census or governmental data miss out on certain important facets making empirical validation impossible and lack the spatio-temporal resolution necessary to cover the characteristics of resilience (Burton 2014). Hence, this experimental study explores and develops new spatial indicators through machine learning methods derived from OpenStreetMap data to replicate conventional core indicators. In order to cover all spatial attributes indicators for points, lines and areas will be deduced and separately as well as in a combined analysis investigated by means of supervised and unsupervised algorithms. The outcome is expected to uncover hidden spatial relations and patterns of urban resilience. Moreover, Burton (2014) stresses the need for new data sources to better understand the multifaceted phenomena of urban resilience. Therefore this study is contributing in developing robust and reliable socio-economic indicators contributing to this challenge to clear up the smoke.

uk: вхід без авторизації

name: Exploratory study of urban resilience in the region of Stuttgart based on OpenStreetMap and literature resilience indicators


uk: Комп'ютерні науки

description: Developing learning crowed based spatio-temporal indicators to model the components of the WorldRiskIndex based on OSM tags and machine learning Climate change is already reality in many parts of the world and even more threatening our future well-being. The SDG 1.5 explicitly aims to reduce by 2030 the vulnerability and exposure to climate related hazards. The World Risk Index (WRI) is one well-respected approach in profiling countries risk to natural hazard. To effectively monitor development and detect decision knots on the climate resilience pathway (IPCC 2014) data of high resolution in space and time about the worlds countries is of urgent importance. Hence, the core of this work is the development of learning indicators. Learning in the sense of a methodological approach combining PostGIS for data management, R for statistical learning and QGIS for spatial analysis on crowd based information assessing the OSM-database and addressing the need of societal learning in the face of severe climate change. The World Risk Index (Birkmann et al. 2015) will guide the supervised learning part resulting in an indicator set derived from OSM tags, establishing on one hand an open risk index and adding deep explanatory power to its components by a qualitative discussion of the OSM themes. The second part explores with unsupervised algorithms the inherent characteristic of country groups classified by the open risk index and deduces common patterns of socio-economic vulnerability but also societal resilience. Hence, the inherent challenge of this work is to substitute existing static indicators with new dynamic indicators, but not only substituting them but also painting a more detailed picture. Moreover, new data sources still questioned often by their reliability compared to World Bank or census data, and therefore its opportunities are neglected instead of critically exploring the potential. Therefore, this thorough statistical approach in quantifying uncertainty contributes to the acceptance and hence use of crowd based information adding necessary reliability for policy and planning. This unique combination is not yet done and bares huge potential moreover united with the open source geo community to contribute a little piece of the puzzle for achieving the SDG 1.5.

uk: вхід без авторизації

name: An open risk index with learning indicators from OSM-tags, developed by machine learning and trained with the WorldRiskIndex


uk: Комп'ютерні науки

description: At Swiftera we've built a Spatio Temporal Asset Catalog (STAC) service using the gRPC framework and protobuf messages (instead of the OpenAPI framework and JSON messages) . The Remote Procedure Call framework, gRPC, and the protobuf message format are what Google uses internally for it's micro-services (10s of billions of messages a second). Since Google open sourced gRPC 4 years ago, it has been widely adopted by companies moving massive amounts of data (Netflix, Salesforce, Spotify and others). But it isn't only about performance, it's also an suprisingly easy framework to get up and running. At FOSS4GNA we open sourced our NAIP metadata service and the IDL defining the services and messages. By Bucharest we plan to have added Landsat and Sentinel to our public gRPC service. We want to share more about what it's like to work with gRPC and the ease of development for hosting your own gRPC services.

uk: вхід без авторизації

name: Implementing a STAC Service with gRPC and Protocol Buffers


uk: Комп'ютерні науки

description: It is widely known that China will soon be the leading player in world economy overtaking the traditional hubs of North America, Europe and South-East Asia. Its economic activities increasingly influence countries beyond its own borders and dominate global economic growth. The analysis of the shifting axis uses global trade data that countries report through the Harmonised Commodity Description and Coding System (HS-Codes). The shift of power towards China is evident when the spatial mean of some 220 globally traded commodities is calculated for which data is available. Other geo-(statistical) indicators further quantify and visualise China’s growing economic power while other economic centres cannot keep up with this pace or even decline in importance.

uk: вхід без авторизації

name: The shift of trade powers: Understanding China’s growing importance in global economic activity with FOSS technologies


uk: Комп'ютерні науки

description: Natural hazards such as floods are receiving a lot of attention around the world and the vulnerability assessment is a strategy to develop prevention and mitigation plans. But it is important to work under a conceptual framework that considers communities as socio-ecosystems, especially with climate change. In Colombia, floods have always been a serious threat for its population, and many coastal communities could be in risk. To face these hazards, mangrove forests are fundamental elements for the resilience of coastal livelihoods and the entire coastal zones. Then the COASTMAP URABÁ project that is being carried out since 2017 in the Urabá gulf in Colombia and that so far has created free access maps of two coastal communities using the mapping methodology created by the HOT team, has allowed the development of a Flood Vulnerability Index for coastal social-ecosystems (FVIc) that could be used in all the coastal communities of the country.

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name: Flood Vulnerability Index for coastal communities linked to mangrove forests based on the COASTMAP URABÁ project


uk: Комп'ютерні науки

description: For almost 5 decades, ECMWF, the European Centre for Medium-range Weather Forecast, has been producing numerical weather forecasts and maintained one of the largest archives of meteorological data. Recently the European Commission has entrusted ECMWF with the implementation of the Copernicus Climate Change Service (C3S), and Atmosphere Monitoring Service (CAMS), opening up the access to a huge amount of environmental data. ECMWF has a long experience to decode, manipulate and visualise GRIB and NetCDF data. This talk will present how with the help of community open source tools users can more easily explore these large datasets. But even if users have the right tools and knowledge to manipulate the data, the amount of data to transfer is still a bottleneck. It is why ECMWF embarked in various projects to build and use cloud environments. One of these is the EU-funded Horizon 2020 HiDALGO project, which explores the building of workflows using these tools over various HPC and cloud environments. Open source plays again a vital role to make this happen. First findings of this exciting new work will be presented in this talk.

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name: Building cloud environments with open source software to offer processing of large environmental data sets


uk: Комп'ютерні науки

description: EnviDat is the institutional data portal and publication data repository of the Swiss Federal Research Institute WSL. EnviDat actively implements the FAIR (Findability, Accessibility, Interoperability and Reusability) principles and provides a range of services in the area of research data management that were extensively described in [Iosifescu et al. (2018a)](https://doi.org/10.5334/dsj-2018-028). We continuously improve various aspects of open science support in EnviDat, including implementation of Jupyter Notebooks as documented in [Iosifescu et al. (2018b)](https://doi.org/10.7287/peerj.preprints.27211), thus improving the current situation defined by a “replication crisis”. In [Iosifescu et al. (2015)](http://hdl.handle.net/2263/49954) we have presented several reasons for the increasing adoption of FOSS4G (free and open source software for geoinformatics) in academic research: not only the total cost of ownership, but also the growing stability and maturity of the recent open source software packages, the faster bug-fixing turnover, the increasing availability of professional support, and the flexibility to change and repurpose the open software to tackle new research challenges, among others. These reasons are still valid today, and consequently EnviDat trusts PostgreSQL/PostGIS and Apache Solr with the management of its spatial meta(data). In this contribution, we discuss two novel drivers for the adoption of FOSS(4G) in environmental research: open science and reproducibility. Independent research replication at peer-review is facilitated by the immediate availability of the free and open source software, the absence of software licensing issues and the openness of the code even for older versions of a software. Moreover, researchers producing their own FOSS code can expect a wider distribution of the produced software. In EnviDat, open science support is supported by the combined publication of bundles of datasets and software as for example [Fraefel (2018)](https://doi.org/10.16904/envidat.49) or purely FOSS4G software as for example [Bont (2018)]( https://doi.org/10.16904/envidat.software.1). While Fraefel shows how scientists can complement data publication with additional analysis workflows, the work of Bont demonstrates the opening of a methodology for optimizing the geometric layout cable roads and makes it available for everyone as a plugin for QGIS. In conclusion, supporting reproducibility of research in a portal such as EnviDat is a complex issue that can be simplified by the adoption of FOSS(4G). We would like to stress that reproducibility in science also consists of the transparency of methods and the precise documentation of all steps needed to achieve the published results. In these processes, open source software can play a key role.

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name: Open Science, Knowledge Sharing and Reproducibility as Drivers for the Adoption of FOSS4G in Environmental Research


uk: Комп'ютерні науки

description: Land cover (LC) (and land use (LU)) maps are an essential components for regional decision-making.They inform policy-makers about the structure of their territory and frame policies including spatial and urban planning, environmental management, transport optimization, risk assessment, etc. The LC data currently available in the Walloon region in Belgium date back over a decade and an update was thus needed. The regional administration decided to launch a research project to develop a robust, automatized, scalable and reproducible method for creating these data, principally based on the available VISNIR orthoimagery at 0.25 m resolution, as well as height information derived through photogrammetry.The ultimate aim of the project is not only to provide recent (2018) maps, but also to elaborate a method that would make it easier for the region to reproduce such data at higher temporal frequency than in the past. The size of the data set (several TB) also provoked a specific focus on scalability while ease of application for a regional administration was another priority.Whereas in urban areas an object-based (OBIA) approach has been the privileged path in the last years as it allows taking into account shape information relevant for the characterization of man-made constructions, such an approach has its limits in the rural and more natural areas the structure of which does not fit as well into the OBIA paradigm, thus calling for a pixel-based approach. In addition, many of the more natural land cover classes have temporal profiles which cannot be detected in a one-date orthoimage. We therefore decided to also analyze Sentinel 1 and 2 data in order to profit from their higher spectral and temporal resolution.All methods were trained using existing regional databases. In a second step, we combined the different LC classification results by fusioning them into one high-accuracy (over 90% OA) product, using a series of different approaches ranging from rule-based to machine learning, passing by more statistical techniques such as Bayesian fusion. The research teams involved have a long tradition of working with FOSS in image analysis and the choice for a purely FOSS approach was quite obvious and clearly encouraged by the regional administration. Complementary experiences working, for one, with Orfeo Toolbox, and for the other with GRASS GIS, allowed the combination of these different software in the overall framework. This paper will present the details of the respective LC classification chains, including some improvements to the software that happened during the process. Individual LC results as well as results of the different approaches tested for fusioning the different LC products will allow to highlight the advances made, but also some difficulties encountered during the work. In a final section we will present future steps of the work, such as the passage from LC to LU based on alphanumeric databases and the use of LC landscape metrics.

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name: Creating Wallonia's new very high resolution land cover maps: combining GRASS GIS OBIA and OTB pixel-based results


uk: Комп'ютерні науки

description: The OSGeo United Nations (UN) Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between the OSGeo Board of Directors and the UN GIS team at the FOSS4G conference in Seoul, Korea, in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project "... to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector". In 2018, the OSGeo UN Committee called for proposals for developing open geospatial educational materials as a part of its activities. There were three challenges: the first two (one of them sponsored by Boundless) are related to the UN Open GIS Initiative. The first challenge, related to UN Open GIS - Spiral 1, aims at the development of education material that teaches users how to apply the GeoSHAPE platform. GeoSHAPE is a free and open source geospatial collaborative platform created from various open source projects. The developed material provides a guide on how to create, edit and share critical data on an integrated dynamic map in near real time, view map updates by users from anywhere in the world and use GeoSHAPE exchange in connected and disconnected environments. The course is structured with content to suit novice, intermediate and advanced users. The second challenge supports UN Open GIS - Spiral 3, which provides geo-analytical solutions for the UN. The feasibility of the analytical functions developed as part of Spiral 3 were tested against an Ebola Epidemic use case. Requirements for developing suitable applications and methodologies based on actual UN operational cases were defined in 2017. Members of the UN Open GIS - Spiral 3 developed a geo-analytical library, called "Processing Toolbox", which is a plug-in for uDig, an open source desktop GIS. The training material developed in the frame of the OSGeo UN Challenge provides an introduction to the use of the algorithms for environmental analysis in the uDig Processing Toolbox, specifically those related to ecology and ecosystems identification. The training material for Spiral 3 is designed as a step-by-step tutorial, using algorithms in the uDig Processing Toolbox. While working through the tutorial, the user is familiarized with the tools covering all the available macro sections. After completing the tutorial, a user will be able to find the needed algorithms to solve a specific use case. The presentation deals with the description of the UN Open GIS Challenge and the open training materials developed under this initiative. The material is available under an open license and can therefore be reused by anybody.

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name: OSGeo UN Committee Educational Challenges: A use case of sharing software and experience from all over the world


uk: Комп'ютерні науки

description:
A number of climate change research projects discover dependencies between dynamics of vegetation indexes and dynamics of meteorological parameters, which make possible estimation and monitoring of growing season parameters using remote sensing data. In our study, we use Normalized Difference Water Index (NDWI) that can be derived automatically from the daily satellite imagery collected by MODIS sensor. The NDWI indicates amount of liquid water in plant tissue, and then reflects change of vegetation growing conditions and particularly growing season change.

To ensure monitoring of growing season parameters we elaborated an automated software complex that incorporates desktop Geographic Information System (GIS) software (QGIS was used), geospatial database and complex of computational tools. The GIS is used as an infrastructure element for operating and visualization purposes, while the database together with computational tools enable storage and multipurpose processing of meteorological and remote sensing data. The meteorological data is collected for the past period of 130 years and NDWI data for the 20 years. Developed complex is tested on the example of Republic of Komi (Northern part of European Russia) that is covered by Taiga and Tundra natural zones and impacted by different climate forming factors.

Currently we describe architecture of the elaborated complex and design of data processing chains. Elaborated complex ensure automation of downloading raw remote sensing data and reprocessing it into gridded NDWI maps. In this context, it can be underlined that daily collected MODIS imagery can be discovered as big geospatial data, due to this we were needed to resolve a number of optimization tasks to implement its processing. Subsequently, NDWI data is used to produce gridded map series that reflects time and spatial dynamics of growing season characteristics. Produced data have a special significance for areas with sparse meteorological network.

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name: An automated GIS-based technique for evaluation of indirect growing season estimations


uk: Комп'ютерні науки

description: Dar es Salaam, the primary city of Tanzania is highly vulnerable to flooding even from minor Storms, floods in 2009, 2011, 2014 and 2015, caused loss of life,injury, and severely impacted diverse sectors. Dar es Salaam’s flooding problems are largely a function of inadequate storm drainage and poor waste disposal practices rather than being driven exclusively by only extreme rainfall. To reduce flood risk through improved management of drain infrastructure The World Bank Tanzania funded the development of a flood risk monitoring system(Twaa Mtaro) to engage communities in drain clean ups, to facilitate community reporting on blockages affecting the flood risk of local drainage systems and provide municipalities with relevant data related to drain cleaning activities. The development of Twaa Mtato as a web application started May 2017 however the initial co-debase was forked from Chicago-based website for collecting and displaying resident submissions around snow emergencies called adopt-sidewalk. Twaa Mtaro core is based on ruby on rails, uses postgres/postgis for data storage and leaflet for map visualization, all geospatial data(drains data) was prepared using QGIS.

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name: Development of a flood risk monitoring system to support flood risk reduction through community-driven drainage cleaning and drain adoption(Twaa Mtaro) in Dar es salaam city.


uk: Комп'ютерні науки

description: Parliamentary elections were held in Finland in April 2019 and to better visualize the results, I went on a quest to generate polygons for each of the 1937 voting districts. Voting district polygons are not open data except for few major cities, but address points for buildings are open data in Finland and they also have information about which voting district each address belongs to. The talk aims to give examples and tips of how to work with bigger datasets with OSGeo tools and how to deal with errors and uncertainties in your data analysis.

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name: 3.6 million points to polygons: lessons learned while generating voting districts with QGIS, PostGIS and OpenJUMP?


uk: Комп'ютерні науки

description: An overview of GNOSIS CMSS, a styling language for both classic and 3D cartography. Ecere developed the GNOSIS Cascading Map Style Sheets language in conjunction with the OGC Innovation Program's Tetstbed 13 and 14, and the open specifications for it are available in a public Engineering Report: http://docs.opengeospatial.org/per/18-025.html#StylingModel Key features of GNOSIS CMSS include cascading of styling rules and sheets, any symbolizer value can be a complex expression, and a concise and clear syntax.

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name: GNOSIS Cartographic Map Style Sheets (CMSS): an elegant and powerful styling language for both classic and 3D cartography


uk: Комп'ютерні науки

description: Vector tiles are a challenge for the creative mind. In this talk we will take you along the path of making artistic styles for your vector tiles like this [Crafty map](https://apps.webmapper.nl/crafty_map/) and the [Paradise in the Polder map](https://nieneb.github.io/mycelium/). Starting from the importance of having a good and clear tile set to making your own sprites and glyphs with command line tools and software like Inkscape and Gimp. After that we show some trick to add animation with Turf.js and D3.js. Like placing random hot air balloons all over your map! Vector tiles are on the cutting edge of technology and creativity, we combine both to show you the endless possibilities that vector tiles offer!

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name: How to make a crafty Vector Tile map: Custom tiles, the perfect sprite, animating stuff and random hot air balloons!


uk: Комп'ютерні науки

description: Using Open Street Mapping to map Incidence of Malaria among Vulnerable People of Luano District, central Zambia This is a Research project for the YouthMappers. This study investigates the incidence of malaria among the vulnerable people living in a remote area of Zambia. Since the area is prone to flooding, the incidence of malaria is very high. The study will use ODK a mobile based data application to collect data and QGIS to analyze the data. The study is important because the data that will be collected will be useful to the Ministry of Health and other organizations that have interest in community health and human security. The all research project is based on the open street map. This Research has 3 focusing objectives as follows’ (a) Map the incidence of malaria in Luano district using Open Street Mapping techniques. (b) Determining the burden of malaria epidemics in the area. (c) Determine the impact of the incidence of malaria on the socio-economic wellbeing of the people in the area.

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name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: During the last decades, many climatic parameters are more and more deviating from the average according to the mean values registered since consistent weather observations are available. The World Meteorological Organization (WMO) stated that the 2015, 2016 and 2017 years were the warmest since 1850 [1]. This trend is going to be confirmed in 2018 according to the preliminary data analysis of the last year. Drought events will likely occur more frequently or with an higher intensity either in Europe and in Asia [2,3]. Sri Lanka is not an exception, the norther-east area is already facing long period with very few precipitation events. Drought has multiple impacts on environmental and socio-economic aspects such as water resources management, human lives, energy consumption and many others. This climatic scenario highlights the importance of the development of monitoring systems to support the management of the drought risk. The 4onse project (analysis of Open, Non-conventional, Sustainable and Effective monitoring systems), funded by the Swiss National Science Foundation (SNSF), aims to evaluate “non-conventional” Environmental Monitoring System (EMS) based on open technologies both hardware and software. At this state of the project, after developing and validating the prototype [4], 30 weather stations have been deployed in the Deduru Oya Sri Lankan basin and collecting the basic weather parameters (air temperature, humidity, pressure, accumulated rain, wind speed and wind direction). The system can help developing and low-income countries in coping the lack in the monitoring and management of natural hazards. In fact, thanks to the collected data, it is possible to elaborate some drought indexes which help in evaluating the intensity of the dry periods. The Standard Precipitation Index (SPI) has been selected as principal indicator to evaluate droughts. The SPI has been calculated integrating the data collected by the 4onse stations together with the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset. In this paper, the authors present the results of the methodology used and the proposed system to share the information that are useful to better take mitigation actions in time. [1] WMO WMO statement on the state of the global climate in 2017; 2018; ISBN 978-92-63-11212-5. [2] Spinoni, J.; Vogt, J.V.; Naumann, G.; Barbosa, P.; Dosio, A. Will drought events become more frequent and severe in Europe? International Journal of Climatology 2018, 38, 1718–1736. [3] Guo, H.; Bao, A.; Liu, T.; Jiapaer, G.; Ndayisaba, F.; Jiang, L.; Kurban, A.; De Maeyer, P. Spatial and temporal characteristics of droughts in Central Asia during 1966–2015. Science of The Total Environment 2018, 624, 1523–1538. [4] Strigaro, D.; Cannata, M.; Antonovic, M. Boosting a Weather Monitoring System in Low Income Economies using Open and Non-Conventional Systems: Data Quality Analysis. Sensors 2019, (accepted).

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name: An open drought monitoring system for the Deduru Oya basin in Sri Lanka in the context of the 4onse project.


uk: Комп'ютерні науки

description: Imagine having a leading-edge application that manages Transportation Networks. Every aspect is user configurable and it can deal with any type of network. You can define multiple linear referencing methods (LRM) that can be network-type specific or across all your network types. You can also define any type of asset or event and the users can locate or retrieve the location of these features. Although the server-side "LRS engine" is going strong and getting more intelligent, the same cannot be said for the UI. Which it's a thick desktop client, on underlying technology you cannot control and looks dated. This was the situation Bentley found itself in, a while back. The way we solved it, which is the subject of this presentation, was using a mixture of open and closed source components. The UI was moved to the web and the communication mechanism was re-written. Using Oracle Mapbuilder, map definition files were created and dynamically fed to MapServer to render the maps which were then displayed through an OpenLayers interface. The end result, Assetwise ALIM LRS, is a living proof of the advantages of using this "best of breed" approach which benefits the end user from both a commercial and technical standpoint.

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name: The best of both worlds: Using open and closed source s/w to manage Transportation Networks and associated LRS


Designing Fair Ranking Schemes

uk: Комп'ютерні науки

description: Items from a database are often ranked based on a combination of criteria. The weight given to each criterion in the combination can greatly affect the fairness of the produced ranking, for example, preferring men over women. A user may have the flexibility to choose combinations that weigh these criteria differently, within limits. In this paper, we develop a system that helps users choose criterion weights that lead to greater fairness. We consider ranking functions that compute the score of each item as a weighted sum of (numeric) attribute values, and then sort items on their score. Each ranking function can be expressed as a point in a multi-dimensional space. For a broad range of fairness criteria, including proportionality, we show how to efficiently identify regions in this space that satisfy these criteria. Using this identification method, our system is able to tell users whether their proposed ranking function satisfies the desired fairness criteria and, if it does not, to suggest the smallest modification that does. Our extensive experiments on real datasets demonstrate that our methods are able to find solutions that satisfy fairness criteria effectively (usually with only small changes to proposed weight vectors) and efficiently (in interactive time, after some initial pre-processing).

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Data Literacy - Lehrende

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description: Data Literacy ist die Fähigkeit, Daten auf kritische Art und Weise zu sammeln, zu managen, zu bewerten und anzuwenden. Zu Data Literacy gehören eine ganze Reihe von Einzelkompetenzen – vom Schaffen des grundlegenden Bewusstseins bis hin zu ethischen und rechtlichen Fragestellungen. Data Literacy ist eine zentrale Kompetenz für die Digitalisierung und die globale Wissensgesellschaft in allen Sektoren und Disziplinen. Angesichts der zunehmenden Menge und der Verfügbarkeit von Daten stellt sich die Herausforderung, mit den Daten Wissen zu generieren und fundiert Entscheidungen treffen zu können. Hierfür sind einerseits spezialisierte Fachkräfte von Nöten, die so genannten Data Scientists, welche sich auf den Umgang mit Big Data konzentrieren. Andererseits wird heutzutage in allen Sektoren und Fächern bis hin zum gebildeten Bürger Grundwissen im Umgang mit Daten und entsprechenden Werkzeugen zur Datenverarbeitung gefordert. Data Literacy wird somit zu einer zentralen Kompetenz für das 21. Jahrhundert, die es systematisch im Rahmen der (Hochschul-)Bildung zu integrieren und nachhaltig zu vermitteln gilt.

@language: de

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Technische Informationsbibliothek (TIB)

addressCountry: DE

addressLocality: Hanover

addressRegion: Lower Saxony


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name: Data Literacy an der Universität Göttingen


PANGAEA

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name: Datenkompetenzen aus Sicht der Forschung


Künstliche Intelligenz & Data Literacy

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name: Data Literacy - Open Educational Resources