VGIScience at SotM and FOSS4G 2022
We are happy to announce that this year two VGIScience projects will be actively contributing to the FOSS4G and the State of the Map (SotM) conferences in Florence. FOSS4G is a large community meeting of developers, users, companies and scientists that use and develop free and open source software (FOSS). It is hosted by the OSGeo foundation, a leading distributor of FOSS geo-software. SotM is the leading meeting for the OpenStreetMap community where data users, mappers, developers and scientists come together to discuss current trends and innovations. The schedule is extremely packed for both of them so we want to highlight some topics you should definitely add to your schedule. Online and offline registration is still open and we would be happy to meet you in Italy or online:
- Su, 21.08.2022, 10:00: In their talk Comparative Integration Potential Analyses of OSM and Wikidata – the Case Study of Railway Stations, Alishiba Dsouza (University Bonn, DSIS , WoldKG Project) and Moritz Schott (Heidelberg University, GIScience, IDEAL-VGI Project) calculated dataset and community metrics to compare these two great community projects
- Su, 21.08.2022, 10:50: In the five minute lightning talk Returning the favor - Leveraging quality insights of OpenStreetMap-based land-use/land-cover multi-label modeling to the community you will learn about how OSM was used in a deep learning based approach for remote sensing image classification and how this could (and in future ‘should’, by default) benefit the OSM community. The topic is a result of the IDEAL-VGI project and a collaboration between Moritz Schott, Sven Lautenbach and Alexander Zipf from GIScience/HeiGIT at Heidelberg University and Adina Zell and Begüm Demir from RSiM research group at TU Berlin.
- Th, 25.08.2022, 14:15: The new tool OSM Element Vectorisation that enables users to calculate a large set of quality indicators for single OSM elements is presented. The tool is an outcome of the IDEAL-VGI project. In an example study it was used to uncover some interesting tendencies in OSMs land-use data.