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Control their (marine) biological datasets by performing a varied number of quality checks on both published and unpublished datasets.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").

pyhydrophone is an open-source Python package that has been developed to ease the import of underwater sound data recorded with a hydrophone to python, so postprocessing and AI can be easily performed on the data afterwards. Different recorders can be added with their different way of reading metadata, so the users do not have to worry about the format but just about the outcome.

This interactive online tool gives access to all sensor data collected in the framework of the Flemish LifeWatch project, and provides an interface to explore and analyze these data. Several thematic portals have been set up as part of the Data Explorer: - Underway Data Explorer - Station Data Explorer - Zooplankton Data Explorer - GPS Bird Tracking Data Explorer - Fish Telemetry Data Explorer - Batcorder Data Explorer - CPOD (marine mammals) Data Explorer Within the RShiny LifeWatch Data Explorer, five general sections are available to explore, plot, visualize and download data. Some of the more recent data is temporarily under moratorium and therefore protected by password access. The LifeWatch Data Explorer is built using RShiny server, Leaflet, ggplot2, PLotly, Dygraph and DataTables. The system is able to query MSSQL, PostgreSQL, Geoserver (WFS) and MongoDB servers.

The goal of MarineSPEED is to provide a benchmark data set for presence-only species distribution modeling (SDM) in order to facilitate reproducible and comparable SDM research. It contains species occurrences (coordinates) from a wide diversity of marine species and associated environmental data from Bio-ORACLE and MARSPEC. Some additional information about MarineSPEED can be found in the R Shiny viewer at https://rshiny.lifewatch.be/marinespeed/.

BVMtool is a set of R scripts automating marine biological valuation calculations based on the biological valuation concept as developed by Derous et al. 2007 and described by Deneudt et al 2013. Based on a recommended format for data input, the script facilitates the calculation of a number of valuation questions that are commonly solved when observational data on species densities are available. The results of the valuation questions are summarized in final scores for each ecosystem component and can be combined with the final results obtained for other ecosystem components. Subzones can be defined as raster grid cells of a desired size or can be based on polygons of a habitat classification provided by the user. The script also offers the possibility to run a number of quality control procedures on the input data, including a taxonomic quality control using the web services built on the World Register of Marine Species.

This online and interactive environment provides access to all data of the European Tracking Network. The VRE includes a database for storage and integration of acoustic telemetry data and a number of analytical tools for analysing the data using R that are: - the LifeWatch Data Explorer for fish telemetry, a RShiny GUI for data exploration; - an RStudio IDE that allows the user to develop and run R scripts online on the available telemetry data; - an Rpackage that incorporates specific functions to start a smooth analysis of telemetry data. The ETN data management platform is an online web application to store, access and share aquatic telemetry data and metadata. The portal is open to all European users for data management of telemetry data in marine, estuarine and freshwater environments. ETN now contains data of 15 fish species. Currently ETN supports acoustic telemetry data, but aims to extend this to different telemetry techniques (e.g. PIT data-storage tags and satellite tags) to be able to monitor habitat use and migration patterns of a range of species in the aquatic environment. On a technical note, the portal requires the receiver and deployment metadata, as well as the transmitter tag and animal metadata before detection data can be uploaded. The uploaded data are subjected to quality control. Access is password protected and data moratorium rules are in place. The ETN data portal is developed by the Flanders Marine Institute (VLIZ) as part of the Flemish contribution to LifeWatch. New developments and additional features are added on a continuous basis. The web application is built using PHP (using the Symfony framework) for the back-end side and Bootstrap/jQuery/Datatables/… (among others) to facilitate the development of the front-end side.

One of the virtual laboratories developed by LifeWatch Belgium is the Belgian LifeWatch eLab. This online application allows users to standardise, analyse and visualise their data, making use of web services built on top of internal and external reference databases. The ultimate goal of LifeWatch is to set up a network for data exchange and data analysis through web services. Web services are systems that allow communication between two computers over the web, and allow the user to access the most recent and up-to-date information directly from within other applications. Within LifeWatch Belgium, several web services are available to standardise, analyse and visualise your data, and to extract additional data from several sources. The user can select several data services (taxonomic, geographic, thematic, etc.) and run them successively through a straightforward online user interface. You can also use the LifeWatch.be web services in a concatenated way, i.e. the output of one web service is the input for the next web service. Establishing such workflows helps solving (complicated) biological questions. Several use cases demonstrate the use of the LifeWatch web services. So as to facilitate the use of the LifeWatch web services, several applications and tools were documented in use cases and tutorials. These can be found on the links below, as well as on the specific websites of software packages and Github repositories. The Belgian LifeWatch E-Lab online application allows users to standardize, analyze and visualize their data, making use of web services built on top of internal and external reference databases. A user can select several data services (taxonomic, geographic, thematic, etc.) and run them successively through a straightforward user interface. As explained in the user guide, the LifeWatch.be web services can be used in a concatenated way, i.e. the output of one web service is the input for the next web service.

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.