Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to Rural Digital Europe. Are you interested to view more results? Visit OpenAIRE - Explore.
1,387 Research products, page 1 of 139

  • Rural Digital Europe
  • Research data
  • Other research products
  • EU
  • IT

10
arrow_drop_down
Date (most recent)
arrow_drop_down
  • Research data . 2022
    Open Access English
    Authors: 
    Langsrud, Solveig; Skuland, Silje E.;
    Publisher: Zenodo
    Project: EC | SafeConsumE (727580)

    The Risk-behaviour map is a document intended to aid access to and transfer of key data between research groups in the European project Safeconsume. The map covers only steps from retail to consumption for the case studies in Safeconsume where the consumer can reduce risk for foodborne infection (CCHs, Critical Consumer Handling). The map contains information about observed/reported behaviours that can affect risk for foodborne infection divided by country, consumer group, pathogen, food and step in the journey from retail to consumption. Details about data collection is given in: Skuland, S.E., Borda, D., Didier, P., Dumitras¸cu, L., Ferreira, V., Foden, M., Langsrud, S., Maître, I., Martens, L., Møretrø, T., Nguyen-The, C., Nicolau, A. I., Nunes, C., Rosenberg, T. G., Teigen, H. M., Teixeira, P., Truninger, M., 2020. European Food Safety: Mapping Critical Food Practices and Cultural Differences in France, Norway, Portugal, Romania and the UK, in: Skuland, S.E. (Ed.). SIFO report, Oslo. ODA Open Digital Archive: European food safety: Mapping critical food practices and cultural differences in France, Norway, Portugal, Romania and the UK (oslomet.no) Questions about the RM-map can be raised to the SafeConsume project coordinator: Solveig.langsrud@nofima.no Variable list: Name Description CCH/Critical steps Identification of the step and flow diagram the entry belongs to: The step in the flow diagram where the consumer through actions or choices can significantly reduce risk of foodborne infection The CCHs/critical steps belong to one of the following processes: Poultry and vegetables (PVF), Eggs (EGG), Shellfish (SHE), Ready-to-Eat (RTE). Each step is accompanied by the principle of risk reducing effect: Food choice: Buy or eat food with lower risk (e.g avoid buying food if not stored properly in shop, buying pasteurised products, choosing to eat food before use-by-date). Applies to all pathogens. Inhibit growth: Storing ready-to-eat food at cool temperature and consume within expiration date or adding preservatives. Applies to Listeria and Salmonella Wash/Remove: Wash vegetables and fruit. Applies to all pathogens Kill/Heat: Heat treatment to kill pathogens, freezing (Campylobacter) Personal hygiene: Avoid cross-contamination through hand washing or not touching food. Not preparing food when sick Hygiene: Avoid cross-contamination through washing surfaces and using clean utensils Cause or sources Description of causes and sources for the hazard to occur (presence, survival, transfer or growth of pathogen). See Appendix 3 for details Consumer Id Unique identifier of consumer. Pathogen The pathogen(s) that are relevant for the specific CCH/critical step Expert opinion: Effect on pathogen Effect of behaviour on the hazard estimated by a team of microbiologists. Effect on pathogen The effect on pathogen is an estimate of the change in the level of viable pathogens as a direct or indirect consequence of the behaviour, action or process. Consumer group, education, income, rural/urban and country When applicable, demographic data associated with the entry. Classification Name Attributes Classification, llist of codes/units CCH/Critical step Predefined, multiple choices EGG 1 Food choice EGG 3.2 Hygiene EGG 4a Inhibit growth EGG 4b Inhibit growth EGG 5.1 Hygiene EGG 5.2 Personal hygiene EGG 6a Kill EGG 6b Kill EGG 6c Food choice EGG 6c Inhibit growth EGG 7.3 Inhibit growth EGG 8.3 Inhibit growth EGG 9.1 Inhibit growth EGG 11.3 Inhibit growth PVF 1.1 Food choice PVF 1.2 Food choice PVF 2.1 Inhibit growth PVF 3a Inhibit growth PVF 3a Kill PVF 3b Inhibit growth PVF 5.1 Personal hygiene PVF 5.2 Personal hygiene PVF 6.1 Kill PVF 7a Wash/Remove PVF 7b Personal hygiene PVF 7b Wash/Remove PVF 8b Hygiene PVF 8b Personal Hygiene PVF 9.1 Hygiene PVF 10.1 Hygiene PVF 11.1 Inhibit growth PVF 11.2 Inhibit growth RTE 1.1 Food choice RTE 3.1 Inhibit growth RTE 6.1 Inhibit growth RTE 4b Personal hygiene RTE 5.2 Hygiene RTE 5.2 Personal hygiene RTE 6.1 Inhibit growth RTE 7.1 Inhibit growth RTE 7.2 Personal hygiene SHE 1.1 Food choice SHE 7.1 Kill No risk Not designated to CCH Causes/sources Free text Consumer ID Free text Pathogen Predefined, multiple choice Salmonella: S. Enterica Campylobacter: C. jejuni Listeria: Listeria monocytogenes Norovirus Toxoplasma: Toxoplasma gondii Expert opinion: Effect on pathogen Predefined High reduction: This behaviour will have a high reduction on the level of pathogens on food/surfaces/hands Median reduction: This behaviour will reduce the level of pathogens on food/surfaces/hands No effect: This behaviour will most likely not have a significant effect on the level of viable pathogens (< 1 log10 reduction/increase or less than 10 cells/particles transfer) For food choice: Random choice is rated as no effect Median increase: This behaviour will lead to a higher number of pathogens High increase: This behaviour will significantly increase the number of pathogens on food/surfaces/hands Effect on pathogen comment Free text Consumer group Predefined Elderly; >70 years, men and women Pregnant women; immunocompromized Young family: Couples (married or cohabitant) where the women is pregnant or living with their own child(ren) (including stepchildren and adopted children) aged less than 12 months Young, single man: Men age 20-29, Living alone or with flatmates Other: Consumers not belonging to the defined groups Educational level Predefined Basic Secondary Tertiary Not given Living area Predefined Rural Urban Income Predefined Low Median High Country Predefined Portugal, France, Romania, UK, Norway, Hungary, More details about the dataset can be achieved from the authors

  • Open Access
    Authors: 
    Krietemeyer, Andreas; Veldhuis, Marie-Claire ten; van de Giesen, N.C. (Nick);
    Publisher: 4TU.ResearchData
    Country: Netherlands
    Project: EC | BRIGAID (700699)

    RINEX3 (https://files.igs.org/pub/data/format/rinex305.pdf) Hatanaka-compressed (http://sopac.ucsd.edu/hatanaka.shtml) GNSS (Global Navigation Satellite System) data of single-frequency observations obtained by the Ublox Neo M8T receiver (Evaluation Toolkit) and standard Ublox patch antenna. The data is downsampled to 15-second observations spanning from DOY (day of year) 95 in 2017 to DOY 83 in 2020. The unit was placed on the rooftop of the observatory of the NMi building in Delft (approx. coordinate 51.986166, 4.387678). The receiver was connected to a constant power supply. The antenna was placed on the flat rooftop (no significant obstruction in the sky) with a 10cm circular glound plane underneath.

  • Other research product . Other ORP type . 2022
    Restricted English
    Authors: 
    Lazar Luminita; Rodino Steliana; Pop Ruxandra;
    Publisher: Zenodo
    Project: EC | COASTAL (773782)

    A general conclusion of the stakeholders' meetings outlined that governance and excessive bureaucracy are disturbing the economic activity (planning, facilities for investors (lack of), lack of compensatory measures, tourism, infrastructure) and social areas (health, incomes, protection, jobs), avoid real problems like the conflict between Marine Protected Areas (and restrictive measures) and the exploitation of resources or the Danube Delta’s clogged canals and invasive species. Agriculture has clear impacts on both inland and coastal water quality and the locals are not aware of causes, effects and impacts of the pollution on the Black Sea and even on the surrounding neighbourhood. The agriculture is for subsistence and the area is very poor developed. Due to the Danube Delta protected area, there is a pressure down the coastal zone for seasonal tourism (only three - four months/year). Thus, there is an artificial population “growth” that is not sustained by the “real” economic development. The goal of the model is to explore alternative scenarios to improve the quality of life and sustainability within the Danube Delta Biosphere Reserve and its marine waters (Black Sea) as one of the most impacted areas along the Romanian littoral. Land-sea interactions in the coastal MAL5 region were identified through separate sector workshops and a combined multi-sectoral workshop as part of WP1 in the COASTAL project. Land-sea interactions are at the core of our study case. For practical reasons due to data availability and considering that the activity on the area upstream has effect on this highly biodiverse area we will include in the model data collected for the entire county of Tulcea. The model combines the 3 main economic activities in Danube's Delta region: agriculture, aquaculture and tourism. The core objective of agriculture sub model is to model the transformation from conventional farming vs eco farming by trying to fulfil the EU’s recent recommendations, while assuring food security and farmer’s competitiveness on the market. For aquaculture sub model development, the freshwater aquaculture stock was considered as the fish farming area (ha), which has two components – normal and intensive aquaculture stocks. The normal fish farming area is influenced by the development rate, which is a function of the spatial pressure. In the tourism sub model we tried to answer to the following question: how far can the tourism activity can be developed in the region, without harming the environment of Danube's Delta.

  • Open Access
    Authors: 
    Ugo Nanni;
    Publisher: Zenodo
    Project: EC | COLD (759639)

    This repository contains the codes and processed data used to retrieve 10-day changes in glacier surface velocity over the Western Pamir. The supp_CODES.zip contains all details and codes to use COSI-CORR (http://www.tectonics.caltech.edu/slip_history/spot_coseis/) to process a large batch of satellite images. The images can be downloaded directly via https://earthexplorer.usgs.gov/ or https://scihub.copernicus.eu. Please read the Methods and Data section of the associated manuscript for details. The Matrix_velocities.zip contains, for each of the 48 investigated glaciers, the DEM, X, Y (NANNI_2022_supp_glacier_centreline_DEM_XY_1px_30m_1.txt) as well as a matrix of n*m with m the distance along flow and n the number of time step over which the velocity is calculated (NANNI_2022_supp_glacier_centreline_vel_matrix_1px_30m_1.txt), ans the associated figure that show the multi year velocity changes together with the one year average and the along centreline profiles. An example is shown in the two figures for glacier 48 in the main repository. The NANNI_2022_supp_glacier_characteristics file contains the glacier characteristics (48*8), as shown in the associated figures. The NANNI_2022_supp_pickedpoints_migration_AUTUMN/SPRING contains the automatically picked points for the onset of the acceleration in Spring and Autmun for each glacier. The headers contains the information, and the files contains is shown in the associated figure. the temperature profiles used to calculate the Iso 0C are in NANNI_2022_supp_temp_perday_fedchenko_2400m The position of each 48 glacier is shown in the associated figure. You can also find the processed velocity fields (velocity magnitude) under the different path an row: p151r33.zip and p152r33.zip for Landsat8, T42SYJ.zip and T43SBD.zip for Sentinel 2. In these folder you will a find a .tif file names similar to: Working_cosicorr_windows_FCorr_16days_p152r33_159_175_AB_1101110_Filtered_correlations_p152r33_filtered_abs.tif The name of the files gives information about the time span used (16days), the path and raw (p152r33), the data of the slave in DOY from 2013 (159) and of the master (175). The Statistics.zip file contains for each path and row the associated DEM, glacier mask (RGI), median magnitude (ABS), median NS displacement (NS), median EW displacemnt (EW), with the associated median absolute deviation (MAD). The files containing 'bflt' corresponds to the values computed before the filtering procedure, and the one without, after the filtering procedure. The .tif files are not georeferenced, but are all projected on the same grid with a 30m square pixel size on a UTM 33 42N projection. Please contact me for any question.

  • Restricted
    Authors: 
    Ugo Nanni;
    Publisher: Zenodo
    Project: EC | COLD (759639)

    This repository contains the codes and processed data used to retrieve 10-day changes in glacier surface velocity over the Western Pamir. The supp_CODES.zip contains all details and codes to use COSI-CORR (http://www.tectonics.caltech.edu/slip_history/spot_coseis/) to process a large batch of satellite images. The images can be downloaded directly via https://earthexplorer.usgs.gov/ or https://scihub.copernicus.eu. Please read the Methods and Data section of the associated manuscript for details. The Matrix_velocities.zip contains, for each of the 48 investigated glaciers, the DEM, X, Y (NANNI_2022_supp_glacier_centreline_DEM_XY_1px_30m_1.txt) as well as a matrix of n*m with m the distance along flow and n the number of time step over which the velocity is calculated (NANNI_2022_supp_glacier_centreline_vel_matrix_1px_30m_1.txt), ans the associated figure that show the multi year velocity changes together with the one year average and the along centreline profiles. An example is shown in the two figures for glacier 48 in the main repository. The NANNI_2022_supp_glacier_characteristics file contains the glacier characteristics (48*8), as shown in the associated figures. The NANNI_2022_supp_pickedpoints_migration_AUTUMN/SPRING contains the automatically picked points for the onset of the acceleration in Spring and Autmun for each glacier. The headers contains the information, and the files contains is shown in the associated figure. The position of each 48 glacier is shown in the associated figure. Please contact me for any question.

  • Open Access
    Authors: 
    Panagea, Ioanna;
    Publisher: Zenodo
    Project: EC | SOILCARE (677407)

    Raw data: Experimental plot ids and information, mass distribution of all aggregate fractions after wet sieving, Sand content of each fraction to conduct the sand correction, mass distribution of all fractions after isolating the micro-aggregates held within the macroaggregates, yields per treatment, carbon content per fraction (raw data) All data per plot: SOC content, MAOM and POM content of each fraction presented in the fractionation scheme included in the manuscript, together with the mass of the relative fractions.

  • Research data . Audiovisual . 2022
    Open Access English
    Authors: 
    Symanczik, Sarah;
    Publisher: Zenodo
    Project: EC | SolACE (727247)

    Step-by-step guide in visualising mycorrhizal fungi in roots. Why should you visualize them? - To study the mycorrhizal status of plant roots - To assess the efficiency of crop cultivars to form AMF symbiosis - To investigate biotic/abiotic factors affecting the root colonization potential of AMF This training material is aimed at researchers in crop science and sustainable agriculture.

  • Other research product . Other ORP type . 2022
    Open Access
    Authors: 
    De Kok, Jean-Luc; Notebaert, Bastiaan; D'Haese, Nele; Viaene, Peter; Wouter, Hendrik; Van Isacker, WIm; Goethals, Els;
    Publisher: Zenodo
    Project: EC | COASTAL (773782)

    This System Dynamics model was developed together with the Flemish Land Agency (VLM) to obtain a high-level, systemic understanding of the mid- and long-term impacts of water management actions for the Oudlandpolder in Belgium in the framework of the new Spatial Implementation Plan, aimed at climate robust and balanced land and water management (see https://doi.org/10.5281/zenodo.7081821). The model is based on two artificial compartments, one for agriculture and one for nature, and driven by scenarios for climate change, land use and crop schemes. Water levels in the agriculture and nature compartment are optimized based on monthly target levels and day-to-day decisions on water management actions such as canal water intake, sea discharge and creek ridge water extraction or infiltration. The model uses a time horizon of 80 years (2020-2100) and a time step of 1 day, to align with the practice of water management decisions (such as the opening of sluices). The model uses diverse data related to land use cover change, climate change, water management, and crop farming. Important data sources include: the Flemish Institute for Technological Research (VITO) for meteorological forecasts for different climate change scenarios, the Food and Agriculture Organization of the United Nations (FAO) for crop factors and the Flemish Land Agency (VLM) for water control parameters. Driving scenarios are based on the Shared-Social Economic Pathways (for crop schemes and land use patterns, see https://doi.org/10.5281/zenodo.7081500 ), the VITO RuimteModel for land use change (see https://vito.be/en/product/geodynamix-spatial-modelling-tools), RCP-based projections for temperature, potential evapotranpiration and precipitation, and related sea level projections obtained from Fox-Kemper, B., et al., 2021, Ocean, Cryosphere and Sea Level Change. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Masson-Delmotte, V., P., et al. (eds.)). Cambridge University Press. In Press.

  • Open Access English
    Authors: 
    Lescot Jean-Marie; Vernier Françoise; Othoniel Benoit; Sabatié Sandrine;
    Publisher: Zenodo
    Project: EC | COASTAL (773782)

    This dataset includes the causal loop diagrams (CLDs) developed by the H2020 COASTAL project’s MAL #4 for the Charente River basin and its coastal zone. These CLDs represent the functioning of the territory in a systemic way, highlighting its main components and interactions among them. The CLDs are the result of multiple sectoral and multi-actor workshops during which stakeholders from different sectors discussed and collaborated to establish a common vision of the land-sea system. The CLDs concern the whole territory and some specific sectors.

  • Open Access English
    Authors: 
    Françoise, Vernier; Jean-Marie, Lescot; Benoit, Othoniel; Sandrine, Sabatié;
    Publisher: Zenodo
    Project: EC | COASTAL (773782)

    This dataset includes the territorial development scenarios developed by the H2020 COASTAL project’s MAL #4 for the Charente River basin and its coastal zone. These scenarios were co-designed with local stakeholders to depict possible futures of the territory. “Towards a desirable future” represents the implementation of the business roadmap also designed in collaboration with stakeholders to achieve a desirable and sustainable future. “Improving current trends” describes the expected evolution of the territory if current efforts are maintained without significant innovation. “Towards a fragmented territory” illustrates a negative development of the territory, exacerbating current issues and inequalities. Each scenario consists in a narrative and in a set of values attributed to the decision variables of the MAL #4 system dynamics model. These values are converted into time-series to simulate the scenarios (cf. data_scenarios.xlsx in https://doi.org/10.5281/zenodo.7075123).