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Processes in this service

Use case Name Description
Hello World An example process that takes a name as input, and echoes it back as output. Intended to demonstrate a simple process with a single literal input.
Daugava Group points by region Merge data points with the attributes of the study region the points fall into (R function 'points_att_polygon').
Daugava Group data to groups based on date This process groups the data into groups based on the date. If requested (by setting "year_starts_at_Dec1"), it adds December to the next year (i.e. all winter months together). In that case, in the result, every year starts at Dec-01 and ends on...
Daugava Return group average description: This function calculates and returns the average value for each defined group (for example per site, per year, per season and per HELCOM_ID) (R function 'mean_by_group').
Daugava Select and Interpolate Time Series This process selects time series with sufficient data for interpolation and returns continuous time series where missing values (NAs) are replaced using linear interpolation (R function zoo::na.approx). The result is a complete time series without...
Daugava Man-Kendall Trend Analysis on Time Series This process performs a Man-Kendall trend analysis to identify the presence or absence of significant trends in time series data. It returns statistical analysis coefficients (e.g., p-values, tau, and slope) for each defined group, allowing for...
Daugava Visualisation of statistical analysis results This process visualizes statistical analysis results, where the test value (stat.value) is plotted on the Y-axis and id are plotted on the X-axis. Bar color is determined by groups and is displayed in the legend. Bar opacity is controlled by the...
Daugava Spatial visualisation of regions and data points This process maps the trend analysis results onto a study region map, visually representing each region according to the statistical results (significant increase vs. significant decrease vs. insignificant trend). The map helps in understanding the...
Daugava Spatial visualisation of regions and data points This process maps the study region and data point locations on OpenStreetMap, providing a visual representation of the geographic distribution of in-situ data points within the defined study area (R function 'map_shapefile_points').
HEREON OWT Classification Optical Water Type classification for ocean, coastal and inland waters.
Catalunya Inland SWAT+, Soil and Water Assessment Tool The Soil and Water Assessment Tool (SWAT+) is a hydrological model used to simulate processes such as surface runoff, groundwater flow, and water quality across watersheds of varying scales. It evaluates the effects of land use, management practices,...
Catalunya Inland SWAT+ output to MITgcm input connection tool This code converts SWAT output (https://swat.tamu.edu/) of water quantity (Flow out and Temperature) in sqlite format to date input for MITgcm in txt format.The tool uses R code al libraries DBI, RSQLite, and dplyr to correct the date format and...
BOKU Retrieve biodiversity data from the web This process retrieves biodiveryity data, i.e. occurrences for various species, from the sources GBIF, iNaturalist and VertNet. For more details, please ask BOKU.
BOKU Combine and match biodiversity data from separate sources This process combines and matches biodiveryity data, i.e. occurrences for various species, from the sources GBIF, iNaturalist and VertNet, with data provided by the user or other sources. For more details, please ask BOKU.
BOKU Check species names in biodiversity data from separate sources This process XYZ HERE PLEASE, from the sources GBIF, iNaturalist and VertNet, with data provided by the user or other sources. For more details, please ask BOKU.
BOKU pred extract for extraction of environmnetal data pred_extract. For extraction of environmental data used for species distribution modeling.
BOKU Run multidetect and clean the data This process detects outliers using various methods and cleans the data: Ensemble multiple outlier detection methods to ably compare the outliers flagged by each method; then extract final clean data using either absolute or best method generated...
SYKE Compute River Load This process computes daily river loading values from input data which consists of: ((1)) TOC (Total Organic Carbon, mg/l) concentration values based on laboratory samples (in Syke's case coming from the VESLA database) ((2)) Daily discharge values...
SYKE Compute areas of CORINE classes within shapefile polygons This process computes the size of the area in hectares (ha) covered by CORINE Land Cover (CLC) classes within user-defined polygonal regions. The analysis is based on harmonized Finnish CORINE raster datasets for the years 2000, 2006, 2012, and 2018....
SYKE Riverload Plot Analyse and plot results from the CORINE and Compute River Load -tools
Catalunya MITgcm Plotting Tool Plot the results of the MITgcm runs. The plots are lat lon maps of the selected variable for the selected time and depth. This tool will only work with NetCDF files that were configured in a specific way (variables, ...), for example, with the output...
Catalunya MITgcm Preprocessing Preprocessing phase of the AquaINFRA marine modeling chain. Initial conditions, boundary conditions and atmospheric forcing files are generated from Copernicus data to be used as input to the MITgcm model in the Model Run phase.
Catalunya MITgcm Model Run Model Run phase of the AquaINFRA marine modeling chain. A simulation for the Catalan marine model is run, using the MITgcm modeling code, for the selected time period. Inputs are initial and boundary conditions files and atmospheric forcing files...
Malta Malta Groundwater Model (SEAWAT) This process runs a 3D variable-density groundwater flow and transport model (SEAWAT) for the Malta aquifer system. It is configured to simulate the effects of sea-level changes and groundwater recharge on aquifer salinity over a 30-year period. Users...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Generate the Assessment Units Generate the gridded assessment units to be used for reproducing the HOLAS assessment using HELCOM's HEAT assessment tool, covering the Baltic Sea, for a selected HOLAS assessment period. The area is gridded, the grid cells have different sizes. For...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Combine the samples Combine the various types of samples to be used for reproducing the HOLAS assessment using HELCOM's HEAT assessment tool, for a selected HOLAS assessment period. For every assessment period, the configation and the spatial grid are predefined. Default...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Annual Indicators Compute the Annual Indicators (i.e. the calculated HEAT EQRS per indicator per year per assessment unit) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. For every assessment period, the configation and the spatial grid are...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Assessment Indicators Compute the Assessment Indicators (i.e. EQRS per assessment period per assessment unit) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. The calculation is based on the Annual Indicators (i.e. the calculated HEAT EQRS per...
HELCOM HEAT HOLAS Reproducing HEAT HOLAS results: Compute Assessment Compute the Assessment (i.e. EQRS per assessment unit, grouped by overall and criterial level indicators) using HELCOM's HEAT assessment code, for a selected HOLAS assessment period. The calculation is based on the Assessment Indicators (i.e. EQRS per...
HELCOM HEAT Assessing Eutrophication: Generate the Assessment Units Generate the gridded assessment units to be used for the eutrophication assessment using HELCOM's HEAT assessment tool. The area is gridded, the grid cells have different sizes. The spatial units and configuration (e.g. grid size) have to be provided....
HELCOM HEAT Assessing Eutrophication: Combine the samples Combine the various types of samples to be used for the eutrophication assessment using HELCOM's HEAT assessment tool. Please provide input data for at least one of the three sample types (bottle, pump/ferrybox, CTD). Of course you can also provide...
HELCOM HEAT Assessing Eutrophication: Compute Annual Indicators Compute the Annual Indicators (i.e. the calculated HEAT EQRS per indicator per year per assessment unit), as part the eutrophication assessment using HELCOM's HEAT assessment tool. As input, please provide a file containing combined and filtered...
HELCOM HEAT Assessing Eutrophication: Compute Assessment Indicators Compute the Assessment Indicators (i.e. EQRS per assessment period per assessment unit), as part the eutrophication assessment using HELCOM's HEAT assessment tool. The calculation is based on the Annual Indicators (i.e. the calculated HEAT EQRS per...
HELCOM HEAT Assessing Eutrophication: Compute Assessment Compute the Assessment (i.e. EQRS per assessment unit, grouped by overall and criterial level indicators), as part the eutrophication assessment using HELCOM's HEAT assessment tool. The calculation is based on the Assessment Indicators (i.e. EQRS per...
Elbe Attach human population statistics to EU NUTS3 regions. Attach EU human population statistics for chosen year to EU NUTS3 regions using temporally matching NUTS3 version.
Elbe Calculating human population density-derived weights for CORINE CLC classes. Mapping CORINE CLC raster to Eurostat 2021 Census Grid to calculate human population density-derived weights for significant urban CLC classes.
Elbe Validate geometries (e.g. river catchments) Validate geometries and save them as multi-polygons (R function 'preprocess_catchment_geometry')
Elbe Align extents of three datasets (D1=NUTS3 regions; D2=LAU regions; D3=river catchments) including validation steps. Clip three overlapping datasets (D1=NUTS3 regions; D2=LAU regions; D3=river catchments) to the same analysis extent defined as the overlap of D1 and D3 and validate the geometries of the clipped D2.
Elbe Visualising final outputs of dasymetric refinement process. Visualising final urban significant CLC-class specific dasymetric refinement input weights in table (output 1), error map of dasymetric refinement process at LAU (Local Areal Unit) level (output 2), and estimated human population density for target...
Elbe Dasymetric refinement of human population from NUTS3 regions to significant urban CORINE CLC polygons. Dasymetric refinement of human population from NUTS3 regions to significant urban CORINE CLC polygons using CLC-class-specific input weights.
Elbe Measure precision of human population dasymetric refinement by comparing observed and estimated human population for EU LAU regions. Estimate annual human population for Eurostat LAU (Local Areal Units) regions based on area-weighted ancillary data and compare with observed LAU human population values.
Elbe Area-weighted interpolation of ancillary data to calculate human population in target regions Area-weighted interpolation of ancillary data to calculate human population in target regions. The ancillary dataset should contain a polygon ID column called 'nuts_cor_int_id' and an estimated human population numeric column called 'estPopCor'. The...