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Modern challenges of geospatial data science: the Open-Earth-Monitor project

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Modern challenges of geospatial data science: the Open-Earth-Monitor project
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In this talk were addressed some of the main modern challenges of geospatial data science grouped around five main aspects: (i) training data issues — these include mismatches in standards when recording measurements, legal and technical issues that limit data use, high costs of producing new observational data; (ii) modeling issues — these include point clustering and extrapolation problems, model overfitting, artifacts in input data, lack of historical data, lack of consistent global monitoring stations (Kulmala, 2018), limited availability and/or quality of global covariate layers; (iii) data distribution issues — these include unusable file formats, high data volumes, incomplete or inaccurate metadata; (iv) usability issues — these include incompleteness of data, unawareness of user communities and/or data limitations, data being irrelevant for decision making; and (v) governance issues — these include closed data policies from (non-)governmental organizations, datasets not used by organizations, lack of baseline estimates, absence of strategies for updates of data products. OpenGeoHub, together with 21 partners have launched an ambitious new European Commission-funded Horizon Europe project called “Open-Earth-Monitor” which aims at tackling some of the bottlenecks in the uptake and effective usage of environmental data, both ground observations and measurements and EO data. They plan to build upon existing Open Source and Open Data projects and build a number of tools, good practice guidelines and datasets that can help cope with some of the modern challenges.
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