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  • 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.

  • Brolio-AGRESTO-AIF3P6 is one of the trials of the Agresto plot within the Brolio site. Trial: ground cover plants.

  • This service aims to be a citizen science portal where users can contribute with images of Glacier Lagoons in Sierra Nevada and its surroundings.

  • TITAN comprises a well-grounded stack of Big Data technologies including Apache Kafka for inter-component communication, Apache Avro for data serialisation and Apache Spark for data analytics. Furthermore, DRAMA framework is the underlying workflow orchestrator engine used by TITAN.

  • The Remote Monitoring and Smart Sensing Analysis Service is a web server designed to cover the entire process (from the selection, downloading to the view and analysis) required to work with satellite data products. First, the web server provides an Interface to search, find and download Sentinel & Landsat satellite products easily, and after then provides different tools to manage and work with the products. During the downloading process, the user can perform a valid search for different zones, and also restrict the queries by different keywords: cloud coverage, date, platform name (S1, S2, L8). In case of interruptions or other exceptions, downloading will restart from where it left off. At the same time, a geospatial integration with Smart Sensing data (where applicable, mainly from isolated areas) will be performed In terms of data treatment, the following products are available to be processed: • Sentinel-1 • Sentinel-2 • Landsat 8

  • This package provides functionality to access data from the European Tracking Network (ETN) database hosted by the Flanders Marine Institute (VLIZ) as part of the Flemish contribution to LifeWatch. ETN data is subject to the ETN data policy and can be: - restricted: under moratorium and only accessible to logged-in data owners/collaborators - unrestricted: publicly accessible without login and routinely published to international biodiversity facilities The ETN infrastructure currently requires the package to be run within the LifeWatch.be RStudio server, which is password protected. A login can be requested at http://www.lifewatch.be/etn/contact.

  • PEMA is a HPC-centered, containerized assembly of key metabarcoding analysis tools. It supports the downstream analysis of four marker genes (16S/18S rRNA, ITS and COI) but also, by allowing the user to train the classifiers with custom reference databases, it can be used for further marker genes. By combining state-of-the art technologies and algorithms with an easy to get-set-use framework, PEMA allows researchers to tune thoroughly each study thanks to roll-back checkpoints and on-demand partial pipeline execution features.

  • Camera Trap Data Package (or Camtrap DP for short) is a community developed data exchange format for camera trap data. A Camtrap DP is a Frictionless Data Package (https://frictionlessdata.io/data-package/) that consists of 4 files: - datapackage.json: metadata regarding the data package and camera trap project. - deployments.csv: a table with camera trap deployments. - multimedia.csv: a table compiling multimedia files taken by the camera traps. - observations.csv: a table with observations based on the multimedia files. The Camtrap DP package is documented on a website (https://tdwg.github.io/camtrap-dp/). Camtrap DP is managed by the Machine Observations Interest Group of Biodiversity Information Standards (TDWG). It was originally developed by the Open Science Conservation Fund and the Research Institute for Nature and Forest (INBO). Camtrap DP is endorsed the camera trap data management systems Agouti, eMammal, TRAPPER, Wildlife Insights and already available as an export format in some of these.

  • Acoustic monitoring is a powerful technique for learning about the ecology of bats. Bat recorders provide continuous registration of bat activity by recording echolocation calls of passing bats. Since the bat calls are highly reliable taxonomic features, the acquired data can be used to estimate diversity and relative abundance of the occurring species. The generated data provides a basis for ecological and behavioral research of the bat species occurring in our coastal and marine areas. BatSounds is an open source repository that contains scripts to work with BatCorder data and BatCorder devices. The repository contains two scripts that are useful to process and send the audio data retrieved by ecoObs Batcorders (https://ecoobs.com/): - Raw_to_wav is a python script that adds a header to raw audio files from the BatCorder so it can more easily be used by different softwares as a wav file. - beaglebone_batcorder is a bash-script to run on a Beaglebone Black minicomputer connected to a BatCorder. It copies the data from the BatCorder daily to its own SD card and sends it to an FTP server over Ethernet. It allows for remote data transfer and memory management of the BatCorder. LifeWatch Belgium has currently four ecoObs BatCorders installed. You can find more information here: https://lifewatch.be/en/sensor-network-bat-detection

  • The LifeWatch Italy Data Portal is a national data infrastructure facilitating data sharing for biological and environmental research and making it accessible and reusable.