The service, starting from a multi-class shapefile containing the land cover classes in the scene, expressed in FAO-LCCS taxonomy, aims to generate a series of shapefiles, one for each different class. A numeric code is also associated to each class. The algorithm uses as input training and test data used to obtain the multi-class land cover mapping of the scene by a supervised, pixel-based classification. Within the Ailanthus workflow of the Internal Joint Intiative, it represents the step 1 and 2 of the first stage (where a multi-class problem is considered).

This service aims at building two datacubes based on the occurrences. The datacube aggregates (=counts) occurrences on a regular grid. This count has a stochastic component that takes the uncertainty field into account. All this process has been developed in R in the frame of the TrIAS project. It represents the Step 4 of the Biotope vulnerability Workflow within the Internal Joint Initiative.

This service aims to create a dataset of environmental predictors linked to SIA’s coordinates by exploiting oceanographic and bioclimatic raster layers. It extracts Enviromental Data and represents the Step 4 of the Crustaceans Workflow within the Internal Joint Initiative.

This service extracts from GBIF (Global Biodiversity Information Facility) taxa occurrence records that were not classified as NIS in Step 3 (GBIF NIS Verifier) of the Metabarcoding workflow. This step aims to verify if eDNA detections were identified outside the known distribution range using GBIF occurrences records. Additionally, for such eDNA detections, this step produces a geographical spatial polygon based on occurrence records available in GBIF. It represents the Step 4 of the Metabarcoding Workflow within the Internal Joint Initiative.

This service aims at enabling the dataset uploading from the user. It represents the Step 1b of the Biotope vulnerability Workflow within the Internal Joint Initiative.

This service aims at crossing the datacube with a geographic layer in order to compute incidence information per zone. This information is extracted based on the geolocation code. It includes a tool to visualize the outputs rasters. It represents the Step 5 of the Biotope vulnerability Workflow within the Internal Joint Initiative.

Following the FAIR principles and best practices, the LifeWatch Italy Training Catalogue hosts the metadata of relevant learning resources so that these can be shared, searched, discovered, accessed and reused. The LifeWatch Italy training catalogue’s accurate and descriptive metadata allow all users to find the most appropriate and well-suited educational resources for their needs. Metadata are based on a subset of the IEEE Standard for Learning Object Metadata (IEEE 2002) that has been customised in order to be compliant with the EOSC Training Resource Profile - Data Model. The detail page of each single metadata record includes all the descriptive information and, on the right side of the page, a button “Start the course” that allows to access the resource and hence to start the training.

This service aims at checking which taxa detected and identified from eDNA metabarcoding sequences are listed as NIS and which taxa are not (i.e. native or unrecorded NIS). This service uses available GBIF (Global Biodiversity Information Facility) records of NIS for each Country provided by the Invasive Species Specialist Group (ISSG). it checks if a species is present in the checklist and if this is the case, the species is flagged as being invasive for that country by adding 1 (yes) or 0 (no) to the column isInChecklist of the data frame, and the checklist key or a note to the ref_checklistKey column, for the corresponding cases. It represents the Step 3 of the Metabarcoding Workflow within the Internal Joint Initiative.

This service aims at running PEMA on all the sequences from the samples selected in Step 4 (ARMS Choose and Parameterize) of the ARMS workflow. It additionally requires a parameter file (a tsv file). The service can take some hours to run. It represents the Step 5.2 of the ARMS Workflow within the Internal Joint Initiative.

This service aims at creating a stack of coregistered multi-spectral raster images. It groups two seasons images (summer and autumn) and stack them to obtain a unique image at native resolution (2 meters) by using the Worldview-2 sensor. It represents the Step 5 of the Ailanthus Workflow within the Internal Joint Initiative.