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Given the circumstance that the process for the revision of the international standard ISO 19157 is currently open, this article presents a critical reflection on its content, application and some challenges posed by the new types of data (e.g. big data, BIM data, etc.), that also have a geospatial component and to which, therefore, this international standard can be applied as well. Proposals are put forward going along three lines of improvement, on the one hand the consideration of new data quality elements and on the other, the reinforcement of the interoperability of this international standard with other standards related to data quality, and finally various improvements (e.g. standardization of evaluation methods, clearly introducing the life cycle, improvement of the definition of metaquality, etc.) of the standard, which come from experience.

This deliverable provides a General Framework for the BESTMAP Policy Impact Assessment Modelling (BESTMAP-PIAM) toolset.The BESTMAP-PIAM is based on the notion of defining (a) a typology of agricultural systems, with one (or more) representative case study (CS) in each major system; (b) mapping all individual farms within the case study to a Farm System Archetype (FSA) typology; (c) model the adoption of agri-environmental schemes (AES) within the spatially-mapped FSA population using Agent Based Models (ABM), based on literature and a survey with sufficient representative sample in each FSA of each CS, to elucidate the non-monetary drivers underpinning AES adoption and the relative importance of financial and non-financial/social/identity drivers; (d) linking AES adoption to a set of biophysical, ecological and socio-economic impact models; (e) upscaling the CS level results to EU scale; (f) linking the outputs of these models to indicators developed for the post-2020 CAP output, result and impact reports; (g) visualizing outputs and providing a dashboard for policy makers to explore a range of policy scenarios, focusing on cost-effectiveness of different AES.

First approach to metadata was based on producer's point of view, since producers were responsible for documenting and sharing metadata about their products. Since 2012 (started in EU FP7 GeoViQua project), the Geospatial User Feedback approach described the user perspective on datasets/services (GUF, OGC standard in 2016). In the past users of the data gained knowledge about and with the data, but they lacked the means to easily and automatically share this knowledge in a formal way.In the EU H2020 NextGEOSS project, the NiMMbus system has been matured as an interoperable solution to manage and store feedback items following the OGC GUF standard. NiMMbus can be used as a component for any geospatial portal, and, so far, has been integrated in several H2020 project catalogues or portals (NextGEOSS, ECOPotential, GeoEssential and GroundTruth2.0).User feedback metadata complements producer's metadata and adds value to the resource description in a geospatial portal by collecting the knowledge gained by the user while using the data for the purpose originally foreseen by the producer or an innovative one.The current GEOSS platform provide access to endless data resources. But to truly assist decision making, GEOSS wants to add a knowledge base. We believe that the NiMMbus system is a significant NextGEOSS contribution is this direction.This communication describes how to extend the GUF to provide a set of knowledge elements and connect them to the original data creating a network of knowledge. They can be citations (publications and policy briefs), quality indications (QualityML vocabulary and ISO 19157), usage reports (code and analytical processes), etc. The NiMMbus offers tools to create different levels of feedback starting with comments, providing citations or extract quality indicators for the different quality classes (positional, temporal and attribute accuracy, completeness, consistency) and share them to other users as part of the user feedback and usage report. Usage reports in GUF standards can be extended to include code fragments that other users can apply to reproduce a previous usage. For example, in ECOPotential Protected Areas from Space map browser (continues on H2020 e-Shape project) a vegetation index optimum to observe phenological blooms can be encoded by a user in the layer calculation using a combination of original Sentinel-2 bands. The portal stores that in a JavaScript code (serialized as JSON) that describes which layers and formula were used. Once a user validated the new layer, can decide to make it available to everyone by publishing it as an open source JavaScript code in the NiMMbus system. From then on, any other user of the portal can import it and use it. As the usage description is a full feedback item, the user creating the dynamic layer can also describe any other related information such as comments or advertise a related publication.The system moves the focus to sharing user of the data and complements the producers documentation with the richness of the knowledge that user gain in their data driven research. In addition to augment GEOSS data the system enables a social network of knowledge.

European Geosciences Union (EGU) General Assembly 2020, 4-8 May 2020, Citizen Observatories are becoming a more and more popular source of input data in many scientific domains. This includes for example research on biodiversity (e.g. counts of specific species in an area of interest), air quality monitoring (e.g. low-cost sensor boxes), or traffic flow analysis (e.g. apps collecting floating car data). For the collection of such data, different approaches exist. Besides frameworks providing re-usable software building blocks (e.g. wq framework, Open Data Kit), many projects rely on custom developments. However, these solutions are mainly focused on providing the necessary software components. Further work is necessary to set-up the necessary IT infrastructure. In addition, aspects such as interoperability are usually less considered which often leads to the creation of isolated information silos. In our presentation, we will introduce selected activities of the European H2020 project COS4CLOUD (Co-designed citizen observatories for the EOS-Cloud). Among other objectives, COS4CLOUD aims at providing re-usable services for setting up Citizen Observatories based on the European Open Science (EOS) Cloud. We will especially discuss how it will make use of interoperability standards such as the Sensor Observation Service (SOS), SensorThings API as well as Observations and Measurements (O&M) of the Open Geospatial Consortium (OGC). As a result, COS4CLOUD will not only facilitate the collection of Citizen Observatory data by reducing the work necessary to set-up a corresponding IT infrastructure. It will also support the exchange and integration of Citizen Observatory data between different projects as well as the integration with other authoritative data sources. This shall increase the sustainability of data collection efforts as Citizen Science data may be used as input for many data analysis processes beyond the project that originally collected the data

Altres ajuts: Máster en Teledetección y SIG en la Universitat Autònoma de Barcelona Los estándares para la información geoespacial distribuida pueden ser de propósito general o particulares de un dominio. Algunos dominios han avanzado más que otros en la estandarización y en la interoperabilidad como por ejemplo el dominio Meteorológico-Climático o el Hidrológico. El colectivo de Hidrología detectó la necesidad del estándar WaterML, el cual ayuda a la óptima gestión de los recursos del agua. En términos generales, WaterML es un estándar que define un modelo de datos para la representación de las observaciones hidrológicas, con la intención de permitir el intercambio de este conjunto de datos a través de sistemas de información. Está basado en dos estándares: Geographic Markup Language (GML) y Observations and Measurements (O&M). WaterML en su versión 2.0 fue desarrollado por Open Geospatial Consortium (OGC), fue aprobado a mediados del 2012 y finalmente publicado a inicios del 2014. A pesar de ser un estándar emergente, diversas instituciones gubernamentales y no gubernamentales han considerado útil estandarizar la información sobre sus series temporales de datos hidrológicos y además publicarlas en la web. Este trabajo revisa y cuantifica el nivel de uso de WaterML en las aplicaciones hidrológicas actuales y sitúa a WaterML en la arquitectura del conjunto de los estándares OGC.

This paper reports on major outcomes of the ERA-PLANET (The European network for observing our changing planet) project, which was funded under Horizon 2020 ERA-net co-funding scheme. ERA-PLANET strengthened the European Research Area in the domain of Earth Observation (EO) in coherence with the European partici-pation to Group on Earth Observation and the Copernicus European Union's Earth Observation programme. ERA -PLANET was implemented through four projects focused on smart cities and resilient societies (SMURBS), resource efficiency and environmental management (GEOEssential), global changes and environmental treaties (iGOSP) and polar areas and natural resources (iCUPE). These projects developed specific science-policy workflows and interfaces to address selected environmental policy issues and design cost-effective strategies aiming to achieve targeted objectives. Key Enabling Technologies were implemented to enhancing 'data to knowledge' transition for supporting environmental policy making. Data cube technologies, the Virtual Earth Laboratory, Earth Observation ontologies and Knowledge Platforms were developed and used for such applications.SMURBS brought a substantial contribution to resilient cities and human settlements topics that were adopted by GEO as its 4th engagement priority, bringing the urban resilience topic in the GEO agenda on par with climate change, sustainable development and disaster risk reduction linked to environmental policies. GEOEssential is contributing to the development of Essential Variables (EVs) concept, which is encouraging and should allow the EO community to complete the description of the Earth System with EVs in a close future. This will clearly improve our capacity to address intertwined environmental and development policies as a Nexus.iGOSP supports the implementation of the GEO Flagship on Mercury (GOS4M) and the GEO Initiative on POPs (GOS4POPs) by developing a new integrated approach for global real-time monitoring of environmental quality with respect to air, water and human matrices contamination by toxic substances, like mercury and persistent organic pollutants. iGOSP developed end-user-oriented Knowledge Hubs that provide data repository systems integrated with data management consoles and knowledge information systems.The main outcomes from iCUPE are the novel and comprehensive data sets and a modelling activity that contributed to delivering science-based insights for the Arctic region. Applications enable defining and moni-toring of Arctic Essential Variables and sets up processes towards UN2030 SDGs that include health (SDG 3), clean water resources and sanitation (SDGs 6 and 14).