The LifeWatch and EMODnet Biology QC Tool allows you to assess to what extend a dataset published on an IPT or a DwC-A file meets the EMODnet Biology Data Quality Criteria. This tool is based on the EMODnetBioCheck R package (https://github.com/EMODnet/EMODnetBiocheck) that was created using the obistools package (https://github.com/iobis/obistools) and it is available from the LifeWatch services at http://rshiny.lifewatch.be/BioCheck/. The Biocheck tool performs a detailed Quality Control on OBIS-env datasets and occurrence core dataset. It provides a way for a visual exploration of the dataset and highlights potential issues.

A tool for Quality Controlling Darwin Core based datasets according to the EMODnet Biology guidelines. The tool performs a thorough QC on OBIS-env datasets and occurrence core datasets. It can use an IPT resource URL as input. Quality controlling a dataset is fundamental in order to ensure its appropriate usage. The EMODnetBiocheck R package is developed in the framework of the LifeWatch and EMODnet Biology projects, and managed by the EurOBIS (European Ocean Biodiversity Information System) Data Management Team at the Flanders Marine Institute (VLIZ). It helps users to Quality Control their (marine) biological datasets by performing a varied number of quality checks on both published and unpublished datasets. This R package also allows a thorough visual exploration of the dataset, while highlighting potential issues within the dataset. The R package can be used on: i) public IPT resources; ii) loaded data tables. The only requirement to use the R package is the existence of an Occurrence table in the dataset, although the analysis reaches its full potential using an IPT resource with OBIS-ENV data format (Core: "Event"; Extensions: "Occurrence" and "Extended Measurements or Facts").

rgbif is an R package to search and retrieve data from the Global Biodiverity Information Facilty (GBIF). rgbif wraps R code around the GBIF API to allow you to talk to GBIF from R.

An R package to get downloads from the EurOBIS database. In 2019, development started for the eurobis R package, to serve as an easy to use interface to download EurOBIS data in R. Currently, the main functions and documentation are being developed and are working, but need some further testing and user feedback before it can be officially released.

pyporcc is an open-source Python package developed to detect and classify harbour porpoise’s clicks in audio files using the PorCC algorithm and offering the possibility to create new clicks classifiers. It provides a framework to train different models such as Support Vector Machines, Linear Support Vector Machines, Random Forest and K-Nearest Neighbour that classify sound clips in Noise, and Low-Quality and High-Quality harbour porpoises’ clicks. The algorithm from PAMGuard to detect possible clicks clips is also implemented.

EurOBIS is the european node of the Ocean Biodiversity Information System (OBIS) and part of the LifeWatch Belgium Species Information Backbone and EMODnet Biology. It aims at containing a wide range of taxonomic and species related data; the main goal being the integration of distributed biodiversity data repositories and operating facilities. EurOBIS plays an important role in this as the central storage facility for marine biogeographic data from all over Europe. The EurOBIS data infrastructure is used as the central hub for making biological data available within the biological lot of EMODnet. Through EMODnet Biology the biodiversity occurrence data are available as a Web Feature Service (WFS) in accordance with the Open Geospatial Consortium (OGC) specifications. This webservice supports requests for geographical feature data (with vector geometry and attributes).

The package lwdataexplorer retrieves biodiversity, environmental or genetic data from the projects supported by LifeWatch Belgium. These data are also available to explore and download through the LifeWatch Data Explorer: an R Shiny application that allows you to check and download data from your browser.