Metadatabase

FL9  Natura 2000 - Spatial data   ⇑

🌐 https://sdi.eea.europa.eu/data/dae737fd-7ee1-4b0a-9eb7-1954eec00c65

Description: Natura 2000 is the key instrument to protect biodiversity in the European Union. It is an ecological network of protected areas, set up to ensure the survival of Europe's most valuable species and habitats. Natura 2000 is based on the 1979 Birds Directive and the 1992 Habitats Directive. This version covers the reporting in 2021, revision 1. Compared to the earlier version 2021 of the European dataset, two member states, Germany and Ireland, were rolled back to their previous submissions. Natura 2000 is an ecological network composed of sites designated under the Birds Directive (Special Protection Areas or SPAs) and the Habitats Directive (Sites of Community Importance or SCIs, and Special Areas of Conservation or SACs).

Model / methods

: Member States update Natura 2000 spatial data continuously. The EEA integrates and validates the data, producing one release a year. More information about the production of the European Natura 2000 database can be found in the document "Natura 2000 dataflow doc 2017.docx" available on www.eea.europa.eu/themes/biodiversity/document-library/natura-2000/the-natura-2000-data-flow/view.

Availability: Available

Licence

: EEA standard re-use policy: unless otherwise indicated, re-use of content on the EEA website for commercial or non-commercial purposes is permitted free of charge, provided that the source is acknowledged (https://www.eea.europa.eu/legal/copyright).Copyright holder: Directorate-General for Environment (DG ENV). This data is provided for general information purposes only. Only the data possessed by the competent authorities of the Member States is authentic. Therefore, no rights or legal claims can be derived from the data displayed on this site. No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

FL11  Conservation status of habitat types and species (Habitats Directive)   ⇑

🌐 https://www.eea.europa.eu/en/datahub/datahubitem-view/d8b47719-9213-485a-845b-db1bfe93598d?activeAccordion=1084870%2C1084677%2C1082742

Description

: The tool gives access to biogeographical assessments of conservation status of species and habitats under Article 17 of the Habitats Directive at Member State biogeographical level done by Member States and at EU biogeographical level done by the ETC/BD and the EEA. For more information see metadata factsheet: sdi.eea.europa.eu/catalogue/datahub/api/records/d8b47719-9213-485a-845b-db1bfe93598d/formatters/xsl-view

Model / methods: All Member States are requested by the Habitats Directive (92/43/EEC) to monitor habitat types and species listed in its annexes and send a report every 6 years following an agreed format. The assessment of conservation status is based on information about the status and trends of species populations and of habitats at the level of the biogeographical or marine region. The spatial dataset contains habitat and species distribution data (10km grid cells) as reported by Member States. The tabular dataset this includes information on habitat areas, population sizes, trends, pressures and threats, and conservation status at the national biogeographical level and on conservation status and trends in conservation status at the EU biogeographical level. This metadata refers to: 1) the public dataset, without sensitive species, 2) the full dataset, which includes data on sensitive species. This dataset is with restricted access only to be used internally by EEA.

Availability: Available

FL14  Waterbase biology   ⇑

🌐 https://sdi.eea.europa.eu/data/27edf083-e903-4b53-b757-81a266b0151d

Description

: Waterbase is the generic name given to the EEA's databases on the status and quality of Europe's rivers, lakes, groundwater bodies and transitional, coastal and marine waters, on the quantity of Europe's water resources, and on the emissions to surface waters from point and diffuse sources of pollution. The dataset contains normalised EQR (environmental quality ratio) values for biological quality elements (BQEs) such as phytoplankton, phytobenthos, macroalgae, angiosperms, macroinvertebrates and/or fish in rivers, lakes, transitional and/or coastal waters. A list of spatial object identifiers with selected attributes, reported through WFD and WISE Spatial data reporting, is added to dataset as spatial reference. The data has been compiled and processed by EEA. Please refer to the metadata for additional information: sdi.eea.europa.eu/catalogue/datahub/api/records/27edf083-e903-4b53-b757-81a266b0151d/formatters/xsl-view

Model / methods: The data was delivered between 2012 and 2022 by EEA member countries and cooperating countries, in the scope of the current in the scope of the current WISE SoE - Biology (WISE-2) reporting obligation and the retired WISE SoE - Water Quality (WISE-4), River quality (EWN-1) and Lake quality (EWN-2) reporting obligations. The national data deliveries are compiled into a European-wide Waterbase. The data is used for EEA core set indicators that assess the state, trends in water related pressures and monitor the progress of European policy objectives. No data are available for the United Kingdom after Brexit. The original data is available in the EIONET Central Data Repository.

Availability: Available

Licence

: EEA standard re-use policy: unless otherwise indicated, re-use of content on the EEA website for commercial or non-commercial purposes is permitted free of charge, provided that the source is acknowledged ( www.eea.europa.eu/legal/copyright). Copyright holder: European Environment Agency (EEA).No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

FL20  DAISIE - inventory of alien invasive species in Europe   ⇑

🌐 https://www.gbif.org/dataset/39f36f10-559b-427f-8c86-2d28afff68ca

Description: The DAISIE - inventory of alien invasive species in Europe is a species checklist dataset published by the Research Institute for Nature and Forest (INBO) and the Centre for Ecology and Hydrology (CEH). It contains information on 12,104 taxa (mostly species and mostly introduced) occurring in the wild in Europe since 1500. It covers a broad taxonomic spectrum of terrestrial and aquatic free living and parasitic organisms. Here the DAISIE checklist is published as a standardized Darwin Core Archive and includes for each species: the scientific name, higher classification, and stable taxon identifier (in the taxon core), the vernacular names (in the vernacular names extension), the presence in a specific region, the year of the first introduction (first collection) and/or last assessment/observation in that region, as well as extra information (in the distribution extension), and the habitat, native range, and ecofunctional group (in the description extension). The DAISIE dataset is no longer maintained, but can be used as a historical archive for researching and managing alien plants or compiling regional and national registries of alien species.

Model / methods: The collation of the alien species list is the result of the efforts of the DAISIE (http://www.europe-aliens.org/) project partners and more than 300 collaborators from Europe and neighbouring countries, involved in different fields of expertise and organisations.

Availability: Available

Licence: CC-BY 4.0

Reference:

Please follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data.Roy D, Alderman D, Anastasiu P, Arianoutsou M, Augustin S, Bacher S, Başnou C, Beisel J, Bertolino S, Bonesi L, Bretagnolle F, Chapuis J L, Chauvel B, Chiron F, Clergeau P, Cooper J, Cunha T, Delipetrou P, Desprez-Loustau M, Détaint M, Devin S, Didžiulis V, Essl F, Galil B S, Genovesi P, Gherardi F, Gollasch S, Hejda M, Hulme P E, Josefsson M, Kark S, Kauhala K, Kenis M, Klotz S, Kobelt M, Kühn I, Lambdon P W, Larsson T, Lopez-Vaamonde C, Lorvelec O, Marchante H, Minchin D, Nentwig W, Occhipinti-Ambrogi A, Olenin S, Olenina I, Ovcharenko I, Panov V E, Pascal M, Pergl J, Perglová I, Pino J, Pyšek P, Rabitsch W, Rasplus J, Rathod B, Roques A, Roy H, Sauvard D, Scalera R, Shiganova T A, Shirley S, Shwartz A, Solarz W, Vilà M, Winter M, Yésou P, Zaiko A, Adriaens T, Desmet P, Reyserhove L (2020). DAISIE - Inventory of alien invasive species in Europe. Version 1.7. Research Institute for Nature and Forest (INBO). Checklist dataset doi.org/10.15468/ybwd3x accessed via GBIF.org on 2025-03-24.

FL32  Red List Index   ⇑

🌐 https://unstats.un.org/sdgs/dataportal/database

Description: The Red List Index measures change in aggregate extinction risk across groups of species. It is based on genuine changes in the number of species in each category of extinction risk on The IUCN Red List of Threatened Species (www.iucnredlist.org) is expressed as changes in an index ranging from 0 to 1 where 1 is the maximum contribution that the country or region can make to global species survival, equating to all species being classified as Least Concern on the IUCN Red List, and 0 is the minimum contribution that the country or region can make to global species survival, equating to all species in the country or region having gone extinct.

Model / methods: Threatened species are those listed on The IUCN Red List of Threatened Species in the categories Vulnerable, Endangered, or Critically Endangered (i.e., species that are facing a high, very high, or extremely high risk of extinction in the wild in the medium-term future). Changes over time in the proportion of species threatened with extinction are largely driven by improvements in knowledge and changing taxonomy. The indicator excludes such changes to yield a more informative indicator than the simple proportion of threatened species. It therefore measures change in aggregate extinction risk across groups of species over time, resulting from genuine improvements or deteriorations in the status of individual species. It can be calculated for any representative set of species that have been assessed for The IUCN Red List of Threatened Species at least twice (Butchart et al. 2004, 2005, 2007). To calculate the Red List Index for individual countries and regions, each species contributing to the index is weighted by the proportion of its global range within the particular country or region. The resulting index therefore shows the aggregate extinction risk for species within the country or region relative to its potential contribution to global species extinction risk (within the taxonomic groups included). The Red List Index is based on data from The IUCN Red List of Threatened Species (www.iucnredlist.org), in particular the numbers of species in each Red List category of extinction risk, and changes in these numbers over time resulting from genuine improvements or deteriorations in the status of species. Data on species’ distribution, population size, trends and other parameters that underpin Red List assessments are gathered from published and unpublished sources, species experts, scientists, and conservationists through correspondence, workshops, and electronic fora.

Availability: Available to download (search 15.5.1)

Licence

: All rights reserved (https://www.un.org/en/about-us/copyright/). See terms of use www.un.org/en/about-us/terms-of-use

FL35  IUCN Red List of Threatened Species   ⇑

🌐 https://www.iucnredlist.org/resources/spatial-data-download

Description: The IUCN Red List of Threatened Species™ contains global assessments for more than 163,000 species. More than 83% of these (>136,200 species) have spatial data. The spatial data provided below are mostly for comprehensively assessed taxonomic groups and selected freshwater groups.

Model / methods

: www.iucnredlist.org/assessment/process

Availability: Need to submit request

Licence

: www.iucnredlist.org/terms/terms-of-use

Reference:

IUCN <Red List version year>. The IUCN Red List of Threatened Species. <Red List version>. www.iucnredlist.org. Downloaded on <insert appropriate date>. where <Red List version year> is the year of the dataset version (e.g. 2018) and <Red List version> is the full version of the dataset (e.g. 2018-2)

FL47  Global Biodiversity Information Facility (GBIF)   ⇑

🌐 https://www.gbif.org/occurrence/download

Description: Species occurrence records. GBIF is an international network and data infrastructure funded by the world's governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth.

Model / methods: Records derive from many different kinds of sources, including everything from museum specimens collected in the 18th and 19th century to DNA barcodes and smartphone photos recorded in recent days and weeks.

Availability: Requires an account on GBIF

Licence: Different records under different CC licenses (CC0, CC BY 4.0 and CC BY-NC 4.0)

Reference:

Each species page includes a default citation, for example: GBIF Secretariat: GBIF Backbone Taxonomy. doi.org/10.15468/39omei Accessed via www.gbif.org/species/5284517 [13 January 2020]. To cite GBIF in broad terms: GBIF: The Global Biodiversity Information Facility (year) What is GBIF?. Available from www.gbif.org/what-is-gbif [13 January 2020]. Full citation guidelines here: www.gbif.org/citation-guidelines

FL50  European Red List   ⇑

🌐 https://www.eea.europa.eu/data-and-maps/data/european-red-lists-2/european-red-list/european-red-list-csv-files

🌐 https://www.iucnredlist.org/regions/european-red-list

Description: Since 2005, the European Red List has been serving as a critical tool for assessing the conservation status of Europe's species, while raising awareness about their vulnerability, and informing and influencing decision-making. Funded by the European Commission, nearly 16,000 taxa (species, subspecies and varieties) have been assessed for the European Red List to date, including all vertebrate species (mammals, amphibians, reptiles, birds and fishes), terrestrial and aquatic molluscs, dragonflies, butterflies, bees, grasshoppers, crickets and bush-crickets, trees, medicinal plants, bryophytes (mosses, liverworts and hornworts), hoverflies, and pteridophytes (ferns and lycopods), and a selection of saproxylic beetles, endemic shrubs, and further selected vascular plants (including crop wild relatives and 'policy’ taxa that appear on international policy instruments such as the EU Habitats Directive).

Availability: Available to download

FL30  Future climate projections (CMIP6)   ⇑

🌐 https://aims2.llnl.gov/search

Description: Monthly values of minimum temperature, maximum temperature, and precipitation were processed for 23 global climate models (GCMs), and for four Shared Socio-economic Pathways (SSPs): 126, 245, 370 and 585.

Model / methods

: Downscaling: Global climate models GCMs. See www.worldclim.org/data/downscaling.html

Availability: Available to download

Licence

: Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/) but Must see Terms of Use pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-1.html

Reference:

cite authors of specific models used, see pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-1.html

FL31  Historical climate data (WorldClim version 2.1)   ⇑

🌐 https://www.worldclim.org/data/worldclim21.html#google_vignette

Description: Monthly climate data for minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, water vapor pressure, and for total precipitation.

Model / methods

: Climate data sources used included databases with long-term average values, time-series of monthly averages by year and daily weather data. See methods: rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.5086

Availability: Available to download

Reference: Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315.

FL40  Precipitation (historical and projected)   ⇑

🌐 https://catalogue.ceda.ac.uk/uuid/c107618f1db34801bb88a1e927b82317

Description: Global gridded daily precipitation for the historical (1981–2014) and future (2015–2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5).

Model / methods: Novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events.

Availability: Available to download with CEDA login

Reference:

Paper: Gebrechorkos, S., Leyland, J., Slater, L. et al. A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses. Sci Data 10, 611 (2023). doi.org/10.1038/s41597-023-02528-x and CEDA: School of Geography and Environmental Science, University of Southampton, UK; Gebrechorkos, S.; Leyland, J.; Darby, S.; Parsons, D. (2022): High-resolution daily global climate dataset of BCCAQ statistically downscaled CMIP6 models for the EVOFLOOD project. NERC EDS Centre for Environmental Data Analysis, 14 December 2022. doi:10.5285/c107618f1db34801bb88a1e927b82317. dx.doi.org/10.5285/c107618f1db34801bb88a1e927b82317

FL44  GloboLakes: Lake Surface Water Temperature (LSWT) v4.0 (1995-2016)   ⇑

🌐 https://catalogue.ceda.ac.uk/uuid/76a29c5b55204b66a40308fc2ba9cdb3

Description: This dataset contains the GloboLakes LSWT v4.0 of daily observations of Lake Surface Water Temperature (LSWT), its uncertainty and quality levels. The dataset consist of two sets of files: 1) a single file per day on a 0.05° regular latitude- longitude grid covering the period from June 1995 to December 2016 (folder = daily), 2) a file per lake which contains the time series (daily) of the lake on a 0.05° regular grid (folder = per-lake). The list of the GloboLakes lakes is included as a CSV file and it contains name, GLWD identifier, coordinate of the lake centre and a set of coordinates that can be used to locate the lake in the daily-file dataset. The LSWTs consists of the daily observations of the temperature of the water (skin temperature). Uncertainty estimates and quality levels are provided for each value.

Model / methods: The LSWTs are obtained by combining the orbit data from the AVHRR (Advanced Very High Resolution Radiometer) on MetOpA, AATSR (Advanced Along Track Scanning Radiometer) on Envisat and ATSR-2 (Along Track Scanning Radiometer) on ERS-2 (European Remote Sensing Satellite). The temperatures from the different instruments have been derived with the same algorithm and harmonised to insure consistency for the period 1995-2016. The GloboLakes LSWT v4.0 was produced by the University of Reading in 2018 for long term observations of surface water temperature for about 1000 lakes globally.

Availability: Requires to be CEDA user to download

Licence

: Open Government License: www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

Reference:

Carrea, L.; Merchant, C.J. (2019): GloboLakes: Lake Surface Water Temperature (LSWT) v4.0 (1995-2016). Centre for Environmental Data Analysis, 29 March 2019. doi:10.5285/76a29c5b55204b66a40308fc2ba9cdb3. dx.doi.org/10.5285/76a29c5b55204b66a40308fc2ba9cdb3

FL46  Global Aridity Index and Potential Evapotranspiration Climate Database v3 (historical and future)   ⇑

🌐 https://www.scidb.cn/en/detail?dataSetId=11e920c1ee144fc2a691951096b96cbc

Description: Global raster dataset of average monthly and annual potential evapotransipation (PET) and aridity index (AI). PET datasets are available as monthly averages (12 datasets, i.e. one dataset for each month, averaged over the specified time period) or as an annual average (1 dataset) for the specified time period.

Model / methods: Based on the results of comparative validations, the Hargreaves model has been evaluated as one of the best fit to model PET and Aridity index globally with the available high resolution downscaled and bias corrected climate projections and chosen for the implementation of the Global-AI_PET- CMIP6 Future Projections. This method performs almost as well as the Penman-Monteith method, but requires less parameterization, and has significantly lower sensitivity to error in climatic inputs (Hargreaves and Allen, 2003). The currently available downscaled CMIP6 projections (available from WorldClim) do provide fewer climate variables idoneous for implementation of temperature-based evapotranspiration methods, such as the Hargreaves method.

Availability: Available to download

Licence: CC By 4.0

Reference:

Robert John Zomer, Antonio Trabucco. Future Global Aridity Index and PET Database (CMIP_6)[DS/OL]. V6. Science Data Bank, 2024[2024-07-10]. cstr.cn/16666.11.sciencedb.nbsdc.00086. CSTR:16666.11.sciencedb.nbsdc.00086.

FL21  Land-side aquaculture Ponds Distribution   ⇑

🌐 https://doi.org/10.1016/j.jag.2022.103100

Description: Global distribution pattern of aquaculture ponds

Model / methods: Acquired from 10-m Sentinel-2 time-series images from Google Earth Engine

Availability: Need to request

Licence: CC BY 4.0 DEED

Reference:

Zhihua Wang, Junyao Zhang, Xiaomei Yang, Chong Huang, Fenzhen Su, Xiaoliang Liu, Yueming Liu, Yuanzhi Zhang. Global mapping of the landside clustering of aquaculture ponds from dense time-series 10 m Sentinel-2 images on Google Earth Engine, International Journal of Applied Earth Observation and Geoinformation, Volume 115, 2022, 103100, doi.org/10.1016/j.jag.2022.103100.

FL22  Phosphorus transfers in global fisheries and aquaculture   ⇑

🌐 https://doi.org/10.1038/s41467-019-14242-7

Description: P-harvest, P-input, and P-net from fisheries and aquaculture

Model / methods: World fishery production (1950–2016) is obtained by combining two databases, the Food and Agriculture Organization of the United Nations (FAO) Global Fishery Production database, FishStatJ version 3.04.625 and the reconstructed wild marine fish capture database from Sea Around Us (http://www.seaaroundus.org/).

Availability: Available to download

Licence: Creative Commons Attribution 4.0

Reference:

Huang, Y., Ciais, P., Goll, D.S. et al. The shift of phosphorus transfers in global fisheries and aquaculture. Nat Commun 11, 355 (2020). doi.org/10.1038/s41467-019-14242-7

FL23  Global Aquaculture Imports and Exports   ⇑

🌐 https://www.kaggle.com/datasets/zhengtzer/global-fisheries-aquaculture-department

Description: This database contains statistics on the annual production of fishery commodities and imports and exports of fishery commodities by country and commodities in terms of volume and value from 2000 to 2015

Model / methods: data from fao.org

Availability: Requires login account to download data

Licence: CC0: Public Domain

FL24  Global aquaculture production Quantity (1950 - 2021)   ⇑

🌐 https://www.fao.org/fishery/statistics-query/en/aquaculture/aquaculture_quantity

Description: This database contains aquaculture production statistics by country or territory, species item, FAO Major Fishing Area and culture environment.

Model / methods: data from fao.org

Availability: Available to download but must request license use: All requests for translation and adaptation rights, and for resale and other commercial use rights should be made via www.fao.org/contact-us/licence-request or addressed to copyright@fao.org.

Licence

: This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; creativecommons.org/licenses/by-nc-sa/3.0/igo ). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

Reference: The Food and Agriculture Organization of the United Nations ("FAO") is mandated to collect, analyze, interpret, and disseminate information related to nutrition, food, and agriculture. In this regard, it publishes a number of databases on topics related to FAO’s mandate, and encourages the use of them for statistical, scientific, and research purposes. Accordingly, all databases provide datasets free of charge, in machine-readable format, and subject to the terms of use of this agreement ("Dataset terms") and the Terms and Conditions regarding the Reuse of Web content , which are incorporated herein by reference.

FL0  Boundaries (Countries)   ⇑

🌐 http://myintracomm.ec.europa.eu/dg/ESTAT/6-tools/GISCO/AccessGeographicalRef %20Database/Pages/AccessGeographicalRefDatabase.aspx

Description: This dataset contains the administrative boundaries at country level of the world and is based on the geometry from EBM v2020 (ReferenceDate 31.12.2018) of EuroGeographics for the members of Eurogeographics, and GISCO Countries 2020. This dataset consists of 2 feature classes (regions, boundaries) per scale level and there are 6 different scale levels (100K, 1M, 3M, 10M, 20M and 60M).

Model / methods: Based on the geometry from EBM v2020. of EuroGeographics for the members of Eurogeographics,and the generalised scales are based on GISCO Countries 2016 due to the lack of updates of the UN FAO Gaul dataset. This resulted in a common repository of geometry of which the different datasets were derived. The different scale levels were derived of generalisations of the common repository on 100K scale.

Availability: The full data set (100K - 60M) GISCO.CNTR_2020 is available via the EC restricted download link.

Licence: Generalised dataset derived from EuroGeographics, Turkstat and UN-FAO GI data. The dataset may be used and distributed if: The source (EuroGeographics and UN-FAO) is acknowledged, AND The data is not used for commercial purpose, AND The original geometry is generalised to the equivalent of a scale of 1:1.000.000 or smaller. The source, copyright and branding will be acknowledged if the geographic data are used in Commission products. The acknowledgement will be displayed as “@EuroGeographics” on the map or in an acknowledgement text. The size of the text on the map will be proportional to the size of the map. The maximum length of copyright texts on electronic maps (web maps or electronic applications) is 20 characters. No copyright text will be applied for online icon maps with less than 150 x 150 pixels

Reference: European Commission, Eurostat (ESTAT), GISCO- Geoportal of the European Commission (EUROSTAT), Countries, 2020 - Administrative Units - Dataset.

FL17  Unemployment (% of total labor force)   ⇑

🌐 https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS

Description: Unemployment refers to the share of the labor force that is without work but available for and seeking employment.

Availability: Available

Licence: CC BY-4.0

Reference: Unemployment, total (% of total labor force) (modeled ILO Estimate). International Labour Organization. “ILO Modelled Estimates and Projections database ( ILOEST )” ILOSTAT. Accessed January 07, 2025. ilostat.ilo.org/data.

FL18  Unemployment rate (%)   ⇑

🌐 https://gateway.euro.who.int/en/indicators/hfa_29-0200-unemployment-rate/#id=18836

Description: The International Labour Organization (ILO) definition is applied. \"Unemployed\" comprise all persons above a specified age who during the reference period were: without work, currently available for work or seeking work. See any issue of the Yearbook of Labour Statistics for details. Ratio (in %) of total labour force is used.

Model / methods: The official estimates from the Employment Statistical Office, as most commonly available, are recommended to be provided if data from ILO are not available. (WHO/EURO uses the ILO Yearbook of Labour Statistics as a common source of data). The unemployment rate is calculated by dividing the number of unemployed individuals by the total number of persons in the labor force, and then multiplying the result by 100 to get a percentage.

Availability: Available

Reference:

WHO Regional Office for Europe. “Unemployment rate (%)” European Health for All explorer. Web. Accessed March 19, 2025. gateway.euro.who.int/en/indicators/hfa_29-0200-unemployment-rate/

FL19  Inland waterways transport measurement - goods   ⇑

🌐 https://doi.org/10.2908/TTR00007

Description: Inland waterway (IWW) transport statistics provide information on the volume and performance of freight transport on EU inland waterway network. Eurostat collects the following statistics on IWW: Transport of goods (annual and quarterly mandatory and voluntary data provision); Vessel traffic (annual voluntary data provision); Transport of dangerous goods (annual voluntary data provision); Number of accidents (annual voluntary data provision). The definitions covering the main concepts used in this domain are included in Article 1 and Annex II to Regulation 425/2007

Model / methods: They are reported based on the 'territoriality principle' which means that each country reports the loading, unloading and movements of goods that take place on its national territory, irrespective of country of origins of undertakings or place of first loading and final unloading. The full data provision obligation includes: annually: goods transport by type of goods, by nationality of vessels and by type of vessel as well as container transport by type of goods; quarterly: goods and container transport by nationality of vessels. In addition, the legislation foresees voluntary annual data on vessel traffic. An exhaustive survey is conducted by all reporting countries for national IWW transport statistics. For international IWW transport statistics, all but one country undertake an exhaustive survey. The exception, Poland, relies on assistance from the German statistical authorities to estimate international traffic, undertaken by non-Polish units. For the transit IWW transport, many countries conduct an exhaustive survey, while few use sampling techniques to estimate it. Others rely on cooperation with neighbouring countries to provide the necessary information. Data are collected and/or compiled by the competent national authorities, which can be either the National Statistical Office or the ministries responsible. Original data sources are the IWW transport undertakings but the actual data providers are mainly national administrative authorities, national port authorities or IWW operators. In addition, the River Information System (RIS) is used as data sources in several countries.

Availability: Available

Reference: Eurostat

FL38  Population density   ⇑

🌐 https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density-rev11/data-download

Description: Gridded Population of the World, Version 4 (GPWv4)

Model / methods: Based on counts consistent with national censuses and population registers, as raster data to facilitate data integration.

Availability: Available to download

Licence: When authors make use of data they should cite both the data set and the scientific publication, if available. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility. Please visit the data citations page (https://sedac.ciesin.columbia.edu/citations) for details. Users who would like to choose to format the citation(s) for this dataset using a myriad of alternate styles can copy the DOI number and paste it into Crosscite's website.

Reference:

Center for International Earth Science Information Network - CIESIN - Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). doi.org/10.7927/H49C6VHW. Accessed DAY MONTH YEAR.

FL39  Global Gridded Relative Deprivation Index (GRDI) Version 1 (GRDIv1)   ⇑

🌐 https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1/data-download

Description: Global gridded relative levels of multidimensional deprivation and poverty per pixel. Value of 100 represents the highest level of deprivation and a value of 0 the lowest.

Model / methods: GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.

Availability: Available to download

Licence: When authors make use of data they should cite both the data set and the scientific publication, if available. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility. Please visit the data citations page (https://sedac.ciesin.columbia.edu/citations) for details. Users who would like to choose to format the citation(s) for this dataset using a myriad of alternate styles can copy the DOI number and paste it into Crosscite's website.

Reference:

Center for International Earth Science Information Network - CIESIN - Columbia University. 2022. Global Gridded Relative Deprivation Index (GRDI), Version 1. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). doi.org/10.7927/3xxe-ap97. Accessed DAY MONTH YEAR.

FL41  World Bank GDP (current $)   ⇑

🌐 https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?skipRedirection=true&view=map&year=2023

Description: GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products.

Model / methods: World Bank national accounts data, and OECD National Accounts data files.

Availability: Available to download

Licence: CC BY-4.0

Reference: World Bank national accounts data, and OECD National Accounts data files.

FL42  World Bank GDP growth   ⇑

🌐 https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?skipRedirection=true&view=map&year=2023

Description: Annual percentage growth rate of GDP at market prices based on constant local currency - aggregates are based on constant 2015 prices, expressed in U.S. dollars.

Model / methods: World Bank national accounts data, and OECD National Accounts data files.

Availability: Available to download

Licence: CC BY-4.1

Reference: World Bank national accounts data, and OECD National Accounts data files.

FL48  Life expectancy   ⇑

🌐 https://ourworldindata.org/life-expectancy

Description: The period life expectancy at birth, in a given year.

Model / methods: This data is compiled from three sources: the United Nations’ World Population Prospects (UN WPP), Zijdeman et al. (2015)2, and Riley (2005)3. For data points before 1950, we use Human Mortality Database data4 combined with Zijdeman (2015). From 1950 onwards, we use UN WPP data. For pre-1950 data on world regions and the world as a whole, we use estimates from Riley (2005).

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: UN WPP (2022); HMD (2023); Zijdeman et al. (2015); Riley (2005) – with minor processing by Our World in Data. “Life expectancy at birth – Various sources – period tables” [dataset]. Human Mortality Database, “Human Mortality Database”; United Nations, “World Population Prospects 2022”; United Nations, “World Population Prospects”; Zijdeman et al., “Life Expectancy at birth 2”; James C. Riley, “Estimates of Regional and Global Life Expectancy, 1800-2001” [original data].

FL1  HydroLAKES   ⇑

🌐 https://www.hydrosheds.org/products/hydrolakes

Description: Shoreline polygons of all global lakes with a surface area of at least 10 ha and pour points

Model / methods: Developed using a suite of auxiliary data sources of lake polygons and gridded lake surface areas. HydroLAKES only includes a limited amount of (mostly geometric) attribute information, such as surface area, shoreline length, and estimates of average depth, water volume and residence time.

Availability: Available to download

Licence: Creative Commons Attribution-ShareAlike 4.0 International License

Reference:

Messager, M.L., Lehner, B., Grill, G., Nedeva, I., Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7: 13603. doi.org/10.1038/ncomms13603

FL2  HydroBASINS   ⇑

🌐 https://www.hydrosheds.org/products/hydrobasins

Description: Vectorized polygon layers that depict sub-basin boundaries at a global scale

Model / methods: HydroBASINS has been extracted from the gridded HydroSHEDS core layers at 15 arc-second resolution.

Availability: Freely available for scientific, educational and commercial use.

Licence: The HydroBASINS database is freely available for scientific, educational and commercial use. The data are distributed under the same license agreement as the HydroSHEDS core products, which is included in the Technical Documentation (https://data.hydrosheds.org/file/technical-documentation/HydroSHEDS_TechDoc_v1_4.pdf). For all regulations regarding license grants, copyright, redistribution restrictions, required attributions, disclaimer of warranty, indemnification, liability, and waiver of damages, please refer to the license agreement. By downloading and using the data the user agrees to the terms and conditions of this license.

Reference:

Lehner, B., Grill G. (2013). Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrological Processes, 27(15): 2171–2186. doi.org/10.1002/hyp.9740

FL3  Global Lakes and Wetlands Database (GLWD)   ⇑

🌐 https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database

Description: Database which focuses in three coordinated levels on (1) large lakes and reservoirs, (2) smaller water bodies, and (3) wetlands. Level 1 (GLWD-1) comprises the 3067 largest lakes (area ≥ 50 km2) and 654 largest reservoirs (storage capacity ≥ 0.5 km3) worldwide. Level 2 (GLWD-2) comprises permanent open water bodies with a surface area ≥ 0.1 km2 excluding the water bodies contained in GLWD-1. Level 3 (GLWD-3) comprises lakes, reservoirs, rivers and different wetland types in the form of a global raster map at 30-second resolution.

Model / methods

: Drawing upon a variety of existing maps, data and information, as detailed in the data documentation (which downloads with the data). References of main data sources applied to generate GLWD - Birkett, C.M., Mason, I.M. (1995): A new global lakes database for a remote sensing program studying climatically sensitive large lakes. Journal of Great Lakes Research 21(3): 307-318. - ESRI (Environmental Systems Research Institute) (1992): ArcWorld 1:3 Mio. Continental Coverage. Redlands, CA. Data obtained on CD. - ESRI (Environmental Systems Research Institute) (1993): Digital Chart of the World 1:1 Mio. Redlands, CA. Data obtained on 4 CDs (also available online at www.maproom.psu.edu/dcw/). - ICOLD (International Commission on Large Dams) (1998): Word Register of Dams. 1998 book and CD-ROM. ICOLD, Paris. - Loveland, T.R., Reed, B.C., Brown, J.F., Ohlen, D.O., Zhu, J, Yang, L., and Merchant, J.W. (2000): Development of a global land cover characteristics database and IGBP DISCover from 1-km AVHRR data. International - Journal of Remote Sensing 21(6/7): 1303–1330 (available online at edcdaac.usgs.gov/glcc/glcc.html). - Vörösmarty, C.J., Sharma, K.P., Fekete, B.M., Copeland, A.H., Holden, J., Marble, J., Lough, J.A. (1997): The storage and aging of continental runoff in large reservoir systems of the world. Ambio 26(4): 210-219. - WCMC (World Conservation Monitoring Centre) (1993): Digital wetlands data set. Cambridge, UK. Data obtained from WCMC in 1999.

Availability: The data is available for free download (for non-commercial scientific, conservation and educational purposes).

Reference: Lehner, B. and Döll, P. (2004): Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296/1-4: 1-22.

FL4  UK Lakes   ⇑

🌐 https://uklakes.ceh.ac.uk/

Description: A GIS-based inventory of lakes for Great Britain was originally developed by University College London and the UK Centre for Ecology & Hydrology in 2004 (Hughes et.al. 2004). The inventory includes more than 40000 water bodies in England, Scotland, Wales and the Isle of Man and catchment data for all water bodies with a surface area >1 ha. This version has been updated with additional water bodies from Northern Ireland and supplemented with more recent data during the development and implementation of the Water Framework Directive over the period 2003-2013.

Model / methods: In Great Britain, lake polygons were obtained from Ordnance Survey PANORAMA dataset while the polygons in Northern Ireland were provided by the Department of Environment Northern Ireland. Data on the Biology tab in each lake details page is provided by the National Biodiversity Network (NBN) and its use is subject to the NBN Atlas Terms and Conditions.

Availability: Available

Licence: Lake polygon geometry in Northern Ireland is based upon Crown Copyright and is reproduced with the permission of Land & Property Services under delegated authority from the Controller of Her Majesty's Stationery Office, Crown copyright and database rights, EMOU206.2. Northern Ireland Environment Agency Copyright 2015. Lake polygon geometry in Great Britain is based on Ordnance Survey data and contains public sector information licensed under the Open Government Licence v3.0. Data about species occurrence presented on this page is provided by the National Biodiversity Network (NBN) and its use is subject to the NBN Atlas Terms and Conditions.

Reference: The development of the database was jointly funded by the Environment Agency, Natural England, Countryside Council for Wales (now Natural Resources Wales), and the Scotland and Northern Ireland Forum for Environmental Research (SNIFFER). Recent updates funded by UK-SCAPE.

FL7  Reference Spatial Datasets reported under Water Framework Directive   ⇑

🌐 https://sdi.eea.europa.eu/data/a0731ebf-6bcc-4afe-bab0-39e7aa88eaba

Description

: The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the above mentioned surface water bodies and groundwater bodies.Technical report: sdi.eea.europa.eu/catalogue/srv/api/records/a0731ebf-6bcc-4afe-bab0-39e7aa88eaba/attachments/WISE_WFD_ReferenceSpatialDataSets_2024-07-04.pdf

Model / methods

: The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting.

Availability: Available

Licence

: No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations For further information and specification regarding the use limitations and constraints please consult the technical report which is provided together with the data.

FL8  Lake-TopoCat   ⇑

🌐 https://zenodo.org/records/7916729

Description: A global Lake drainage Topology and Catchment database. LakeTopoCat contains the outlet(s) and catchment(s) of each lake; the interconnecting reaches among lakes; and a wide suite of attributes depicting lake drainage topology such as upstream and downstream relationship, drainage distance between lakes, and a priori drainage type and connectivity with river networks

Model / methods: This version of Lake-TopoCat was constructed using the HydroLAKES v1.0 (Messager et al., 2016) lake mask and the 3-arc-second-resolution hydrography dataset MERIT Hydro v1.0.1 (Yamazaki et al., 2019). The drainage type of each HydroLAKES lake, such as isolated, inflow-headwater, headwater, flow-through, terminal, and coastal, was determined with assistance of MERIT Hydro-Vector (Lin et al., 2021), a high-resolution river network dataset with spatially-variable drainage densities. Furthermore, the seasonal or intra-annual stability of water area in each HydroLAKES lake was calculated using six-year (2010–2015) statistics from the Global Lake area, Climate, and Population (GLCP) database (Meyer et al., 2020).

Availability: Available to download

Licence: CC By 4.0 International

Reference:

Sikder, M. S., Wang, J., Allen, G. H., Sheng, Y., Yamazaki, D., Song, C., Ding, M., Crétaux, J.-F., and Pavelsky, T. M., 2023. Lake-TopoCat: A global lake drainage topology and catchment dataset. Earth System Science Data, 15, 3483-3511, doi.org/10.5194/essd-15-3483-2023

FL13  Waterbase emissions   ⇑

🌐 https://sdi.eea.europa.eu/data/7e833c37-fb4b-4b45-a943-4631788ece4b

Description

: Waterbase is the generic name given to the EEA's databases on the status and quality of Europe's rivers, lakes, groundwater bodies and transitional, coastal and marine waters, on the quantity of Europe's water resources, and on the emissions to surface waters from point and diffuse sources of pollution. This Waterbase contains data on emissions of nutrients, organic matter and other chemical substances to water, from point sources (mostly from industrial and urban waste waster treatment plants) and from diffuse sources (e.g. agriculture, atmospheric deposition, urban runoff not connected to collecting systems). It also contains data on yearly riverine input loads to transitional, coastal and marine waters. The data on emissions are reported as totals per river basin district sub-unit, river basin district or country. The riverine input loads are reported as totals per monitoring site. Please refer to the metadata for additional information: sdi.eea.europa.eu/catalogue/datahub/api/records/7e833c37-fb4b-4b45-a943-4631788ece4b/formatters/xsl-view

Model / methods: The data was delivered between 2009 and 2022 by EEA member countries and cooperating countries, in the scope of the current WISE SoE - Emissions (WISE-1) reporting obligation.No data are available for the United Kingdom after Brexit. The original data is available in the EIONET Central Data Repository

Availability: Available

Licence

: Waterbase data is collected and published to produce comparable indicators of pressures, state and impacts on European waters. Waterbase is intended for a European-wide scale of analysis. It is not intended for assessing compliance with any European Directive or any other legal instrument. Information on the national and sub-national scales should be sought from other sources. By downloading Waterbase, you are accepting and agreeing to the EEA data policy ( www.eea.europa.eu/legal/eea-data-policy).No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

FL37  Land cover classes and extent   ⇑

🌐 https://forobs.jrc.ec.europa.eu/products/glc2000/glc2000.php

Description: The GLC2000 (Global Land Cover in the year 2000) database distinguishes 22 land cover classes.

Model / methods: Produced by an international partnership of 30 research groups coordinated by the European Commission’s Joint Research Centre. Land cover maps were based on daily data from the SPOT vegetation sensor (VEGA 2000 dataset: a dataset of 14 months of pre-processed daily global data acquired by the VEGETATION instrument on board the SPOT 4 satellite) and other Earth observing sensors. The general objective was to provide a harmonized land cover database over the whole globe for the year 2000. The year 2000 is considered as a reference year for environmental assessment in relation to various activities, in particular the United Nation's Ecosystem-related International Conventions

Availability: Available to download (in BASINAtlas)

Licence: Creative Commons CC-BY 4.0

Reference: Bartholomé, E., Belward, A.S. (2005). GLC2000: a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, 26(9), 1959-1977

FL45  GloboLakes: high-resolution global limnology dataset v1   ⇑

🌐 https://catalogue.ceda.ac.uk/uuid/84d4f66b668241328df0c43f8f3b3e16

Description: These data are high-resolution datasets related to in-land water for limnology (study of in-land waters) and remote sensing applications. This includes: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates on a high-resolution (1/360x1/360 degree) grid, produced by the Department of Meteorology at the University of Reading. Datasets containing information to locate and identify water bodies have been generated from high-resolution (1/360x1/360 degree, about 300mx300m) data locating static-water-bodies recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The new datasets provide: distance to land, distance to water, water body identifiers and lake centre locations. The lake identifiers (IDs) are from the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database.

Model / methods: Data was derived using the ESA CCI Land Cover Map (https://maps.elie.ucl.ac.be/CCI/viewer/index.php). The LC CCI water bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR (Advanced Synthetic Aperture Radar) on Envisat between 2005 and 2010.

Availability: Requires to be CEDA user to download

Licence

: Open Government License: www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

Reference:

Carrea, L.; Embury, O.; Merchant, C.J. (2015): GloboLakes: high-resolution global limnology dataset v1. Centre for Environmental Data Analysis, 21 July 2015. doi:10.5285/6be871bc-9572-4345-bb9a-2c42d9d85ceb. dx.doi.org/10.5285/6be871bc-9572-4345-bb9a-2c42d9d85ceb

FL15  EU research and innovation projects on nature-based solutions   ⇑

🌐 https://knowledge.networknature.eu/ridb

Description: In 2021, NetworkNature and Biodiversa+ created the NbS projects database to offer insights into where major funding for NbS is allocated at the European level. This tool serves as a vital resource for policymakers, funders, and programmers, facilitating a better understanding of funding trends and enabling a more coordinated approach to NbS R&I investment.

Model / methods: This database gathers European R&I projects on NbS from several major European research and innovation or implementation programmes: BiodivERsA, Horizon 2020, Seventh framework programme (FP7), Interreg and LIFE (EU’s funding instrument for the environment and climate action).

Availability: Available

Licence: See specific programme guidance

Reference: By specific programme

FL16  Blue economy indicators   ⇑

🌐 https://blue-economy-observatory.ec.europa.eu/blue-economy-indicators_en

Description: The blue economy has been defined by the World Bank as the ‘sustainable use of ocean resources for economic growth, improved livelihoods, and jobs while preserving the health of ocean ecosystem.’ The blue economy of the European Union (EU) encompasses every industry and sector linked to oceans, seas and coasts, whether they operate directly within the marine environment or on land. The established sectors include marine living resources (such as fishing and aquaculture), marine non-living resources (mining), marine renewable energy, port activities (such as cargo and passenger services), shipbuilding and repair, maritime transport and coastal tourism. The data and charts in the online dashboard show the economic indicators used for the established sectors in the EU Blue Economy report. Various filters allow for the customisation of data can in terms of sub-sector, activity, Member State, indicator and time period.

Model / methods

: Structural Business Statistics (SBS) compiled by Eurostat. The SBS were complemented by the EU Data Collection Framework (DCF)[1] for the primary sectors (capture fisheries and aquaculture). Given the time lag in the release of SBS and DCF data, the latest available year is 2020, which is used as the reference year for the current report. See methodology detail: blue-economy-observatory.ec.europa.eu/methodology-estimation-established-sectors-data_en

Availability: Available

Licence

: European Commission reuse notice eur-lex.europa.eu/eli/dec/2011/833/oj

Reference:

European Commission, Directorate-General for Maritime Affairs and Fisheries, ‘Blue economy indicators’, accessed 2025-03-19, data.europa.eu/88u/dataset/blue-economy-indicators

FL6  Waterbase water quantity   ⇑

🌐 https://sdi.eea.europa.eu/data/81e4c3c2-4acc-4196-aa30-d497ddd7b3bc

Description

: Waterbase is the generic name given to the EEA's databases on the status and quality of Europe's rivers, lakes, groundwater bodies and transitional, coastal and marine waters, on the quantity of Europe's water resources, and on the emissions to surface waters from point and diffuse sources of pollution. The dataset contains time series of water quantity data, reported by EEA member countries and cooperating countries. The data has been compiled and processed by EEA. A list of spatial object identifiers with selected attributes, reported through WFD and WISE Spatial data reporting, is added to dataset as spatial reference. Please refer to the metadata for additional information: sdi.eea.europa.eu/catalogue/datahub/api/records/81e4c3c2-4acc-4196-aa30-d497ddd7b3bc/formatters/xsl-view

Model / methods: The original data is available in the EIONET Central Data Repository. This Waterbase contains data on freshwater resources availability, water abstraction and water use at national or regional scale. The data was delivered between 2002 and 2022 by EEA member countries and cooperating countries, in the scope of the current WISE SoE - Water Quantity (WISE-3) reporting. No data are available for the United Kingdom after Brexit. The national data deliveries are compiled into a European-wide Waterbase. The data is used for EEA core set indicators that assess the state, trends in water related pressures and monitor the progress of European policy objectives.

Availability: Available

Licence

: By downloading Waterbase, you are accepting and agreeing to the EEA data policy ( www.eea.europa.eu/legal/eea-data-policy). No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

FL10  EU Wastewater Surveillance   ⇑

🌐 https://wastewater-observatory.jrc.ec.europa.eu/#/content/the-eu-dashboard

🌐 https://joint-research-centre.ec.europa.eu/jrc-news-and-updates/tracking-diseases-sewer-2025-01-29_en

Description

: The EU Wastewater Surveillance Dashboard provides near real-time insights into the spread of pathogens. The dashboard was developed by the EU Wastewater Observatory for Public Health of the Joint Research Centre (JRC) in collaboration with the European Health Preparedness and Response Authority (HERA). The dashboard includes 14 dashboards connected out of 42 available, 13 countries connected, 1,703,528 measurements, 3 pathogens, 109 pathogen subtypes. Dashboard guidance here: wastewater-observatory.jrc.ec.europa.eu/media/content_files/The_European_WWS_Dashboard_Guidance.pdf

Model / methods

: It displays data from across the EU by bringing together existing national and research-based dashboards and combining them with near real-time wastewater monitoring. Data sources here: wastewater-observatory.jrc.ec.europa.eu/media/content_files/Data_Sources_V2025_02_06.pdf

Availability: Available

Reference:

European Commission. The European Wastewater Surveillance Dashboard, EU Wastewater Observatory for Public Health. arcgis.jrc.ec.europa.eu/portal/apps/dashboards/e296cdf0c0d042e6b60b07a351f2dc5c (Accessed 19/03/2025)

FL12  Waterbase water quality   ⇑

🌐 https://sdi.eea.europa.eu/data/beb570c1-4dd3-4edd-973c-9fe912cfaca5

Description

: Waterbase is the generic name given to the EEA's databases on the status and quality of Europe's rivers, lakes, groundwater bodies and transitional, coastal and marine waters, on the quantity of Europe's water resources, and on the emissions to surface waters from point and diffuse sources of pollution. The dataset contains time series of nutrients, organic matter, hazardous substances, pesticides and other chemicals in rivers, lakes, groundwater, transitional, coastal and marine waters. A list of spatial object identifiers with selected attributes, reported through WFD and WISE Spatial data reporting, is added to dataset as spatial reference. The data has been compiled and processed by EEA. Please refer to the metadata for additional information: sdi.eea.europa.eu/catalogue/datahub/api/records/beb570c1-4dd3-4edd-973c-9fe912cfaca5/formatters/xsl-view. *** The dataset is split into two parts: Part 1: DisaggregatedData; Part 2: AggregatedData, AggregatedDataByWaterBody, SpatialObject_DerivedData. ***

Model / methods: Data is reported by EEA member countries as individual samples from monitoring sites in the DisaggregatedData table or as annual aggregates of samples from monitoring sites in the AggregatedData table. Therefore data found in one table is not found in the other, and visa versa. Data in the the AggregatedDataByWaterBody is mostly historical. Methodology: The data was delivered between 2000 and 2023 by EEA member countries and cooperating countries, in the scope of the current WISE SoE - Water Quality ICM (WISE-6) reporting obligation and the retired WISE SoE - Water Quality (WISE-4), River quality (EWN1), Lake quality (EWN-2) and Groundwater quality (EWN-3) reporting obligations. It includes WFD watch list data from 2016 onwards, reported by EU Member States.The national data deliveries are compiled into a European-wide Waterbase. The data is used for EEA core set indicators that assess the state, trends in water related pressures and monitor the progress of European policy objectives. Data sources: The original data is available in the EIONET Central Data Repository.

Availability: Available

Licence

: EEA standard re-use policy: unless otherwise indicated, re-use of content on the EEA website for commercial or non-commercial purposes is permitted free of charge, provided that the source is acknowledged ( www.eea.europa.eu/legal/copyright). Copyright holder: European Environment Agency (EEA). No limitations to public access: inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

FL25  Per capita water withdrawal   ⇑

🌐 http://www.fao.org/nr/water/aquastat/data/query/results.html

🌐 https://ourworldindata.org/water-use-stress

Description: Average level of water withdrawal from agricultural, industrial and municipal purposes per person per year. Water withdrawal is defined as the quantity of freshwater taken from groundwater or surface water sources (such as lakes or rivers) for use in agricultural, industrial, or domestic purposes.

Model / methods: Data source: Food and Agriculture Organization of the United Nations - AQUASTAT

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: Water withdrawals and consumption - Aquastat – processed by Our World in Data. “Total water withdrawal per capita” [dataset]. Water withdrawals and consumption - Aquastat [original data].

FL26  Freshwater use in agriculture   ⇑

🌐 http://www.fao.org/nr/water/aquastat/data/query/results.html

🌐 https://ourworldindata.org/water-use-stress

Description: Total quantity of freshwater withdrawals that are used in agriculture, whether in the form of food crops, livestock, biofuels, or other non-food crop production.

Model / methods: Data source: Food and Agriculture Organization of the United Nations - AQUASTAT

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: Water withdrawals and consumption - Aquastat – processed by Our World in Data. “Agricultural water withdrawal” [dataset]. Water withdrawals and consumption - Aquastat [original data].

FL27  Share of agricultural land that is irrigated   ⇑

🌐 https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators

🌐 https://ourworldindata.org/water-use-stress

Description: The percentage of total agricultural land area which is irrigated (i.e. purposely provided with water), including land irrigated by controlled flooding. Agricultural land is the combination of crop (arable) and grazing land.

Model / methods: Data source: Food and Agriculture Organization of the United Nations - AQUASTAT

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: Food and Agriculture Organization of the United Nations (via World Bank) – processed by Our World in Data. “Agricultural irrigated land (% of total agricultural land)” [dataset]. Food and Agriculture Organization of the United Nations (via World Bank) [original data].

FL28  Industrial water withdrawal   ⇑

🌐 http://www.fao.org/nr/water/aquastat/data/query/results.html

🌐 https://ourworldindata.org/water-use-stress

Description: The annual quantity of self-supplied water withdrawn for industrial uses. It includes water for the cooling of thermoelectric and nuclear power plants, but it does not include hydropower. Water withdrawn by industries that are connected to the public supply network is generally included in municipal water withdrawal

Model / methods: Data source: Food and Agriculture Organization of the United Nations - AQUASTAT

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: Water withdrawals and consumption - Aquastat – processed by Our World in Data. “Industrial water withdrawal” [dataset]. Water withdrawals and consumption - Aquastat [original data].

FL29  Municipal water withdrawal   ⇑

🌐 http://www.fao.org/nr/water/aquastat/data/query/results.html

🌐 https://ourworldindata.org/water-use-stress

Description: Total water withdrawal for municipal (domestic) purposes. Municipal water is defined as the water we use for domestic, household purposes, or public services. This is typically the most 'visible' form of water: the water we use for drinking, cleaning, washing, and cooking.

Model / methods: Data source: Food and Agriculture Organization of the United Nations - AQUASTAT

Availability: Available to download

Licence: CC BY 4.0 DEED

Reference: Water withdrawals and consumption - Aquastat – processed by Our World in Data. “Municipal water withdrawal” [dataset]. Water withdrawals and consumption - Aquastat [original data].

FL33  Water quality of global lakes   ⇑

🌐 https://github.com/roohollahnoori/AWQDFGL

Description: Our database contains 264,061 unique Chla datapoints collected from 13,876 lakes in 77 countries worldwide, TP and TN in 138,591 locations. We also compiled information on additional water quality parameters for each of our lakes includeding NH4+, NO3¯/NO2¯, DO, DOS %, DOC, TOC, TON, TSS, and TFe. We collected the information for the lake surface area, lake perimeter, maximum depth and altitude, and the country in which the lake is located from the repositories used in our study

Model / methods

: see figure 1 in methods of www.sciencedirect.com/science/article/pii/S0921344923005359

Availability: Available to download

Licence

: Request rights: s100.copyright.com/AppDispatchServlet

Reference:

Danial Naderian, Roohollah Noori, Essam Heggy, Sayed M. Bateni, Rabin Bhattarai, Ahmad Nohegar, Sapna Sharma. A water quality database for global lakes, Resources, Conservation and Recycling, Volume 202, 2024, 107401, ISSN 0921-3449, doi.org/10.1016/j.resconrec.2023.107401.

FL34  SGD Water Quality Hub   ⇑

🌐 https://sdg632hub.org/

Description: Dissolved oxygen, electrical conductivity, total nitrogen, Total Oxidized Nitrogen/Nitrate and Nitrite Nitrogen, total phosphorus, Total Reactive Phosphorus/Total Orthophosphate, ph of water bodies by country

Model / methods: Portal designed for those tasked with reporting on SDG indicator 6.3.2 (tracks progress towards SDG target 6.3. This target aims to improve water quality of rivers, lakes and aquifers globally) for their country. It streamlines the reporting process, provides real-time feedback and insight into submissions, as well as information on the supports available.

Availability: Need an invite to be able to login

Reference: UN Development Programme SDG water quality hub (The Global Environment Monitoring System for Freshwater)

FL36  GEMSTAT data portal   ⇑

🌐 https://gemstat.org/data-gemstat/data-portal/

Description: GEMStat hosts water quality data of ground and surface waters providing a global overview of the condition of water bodies and the trends at global, regional and local levels. Many parameters including nutrients (P and N).

Model / methods: Countries and organisations voluntarily provide water quality data from their own monitoring networks.

Availability: Need to request download, email gwdc@bafg.de

Licence

: Users do not obtain title to the intellectual property of the data provided by GEMStat, nor any copyright or propriety rights to its content. Must sign declaration of data user: gemstat.org/2019-07/wp-content/uploads/2018/10/user_declaration.pdf

Reference: United Nations Environment Programme (2017). GEMStat database of the Global Environment Monitoring System for freshwater (GEMS/Water) Programme. International Centre for Water Resources and Global Change, Koblenz. Accessed DD MONTH YYYY. Available upon request from GEMS/Water Data Centre: gemstat.org

FL43  Aqueduct Water Risk Atlas   ⇑

🌐 https://www.wri.org/applications/aqueduct/water-risk-atlas/

Description: Water risk (e.g. water stress, depletion, drought risk) for present and future scenarios, global data. 13 indicators representing baseline annual water risks. 3 indicators representing baseline monthly water risks. 6 indicators representing future projections of annual water risks.

Model / methods: Aqueduct™ 4.0, the latest iteration of WRI’s water risk framework designed to translate complex hydrological data into intuitive indicators of water-related risk.

Availability

: Need login, request download from here: www.wri.org/data/aqueduct-global-maps-40-data

Reference:

Download publication from here: www.wri.org/data/aqueduct-global-maps-40-data but must create login

FL5  Greenhouse Gas Datasets   ⇑

Description: A collation of datasets created for the Greenhouse Gas Modelling using WFD Data and UK monitoring.

Availability: Modelled

Licence: Various

FL49  WFD Typologies   ⇑

Description: Various papers and appraoches to setting WFD lake and chl-a typologies for EU countries

Availability: Provided directly

FL51  Danish WFD lake data   ⇑

FL52  Dutch WFD lake data   ⇑

FL53  UK WFD lake data   ⇑