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This service aims at running a species distribution modelling (sdm) service based on Maximum Entropy (maxent) algorithm. It is intended to predict the potential geographic distribution of a species based on environmental variables. Maxent algorithm is a probabilistic modelling technique used for making predictions based on incomplete information or limited data. It is based on the principle of maximum entropy, which states that when making predictions, one should choose the probability distribution that is the least informative, or maximally uncertain, while still satisfying a set of known constraints. The application calculates the distribution model of a species by taking as input files a vector of presence and a group of raster files that represent the background or environmental layers and providing five output files: elapid_object.ela, maxent_prediction_model.tif, maxent_prediction_plot.png, dependency_plots.png, and auc_score.txt. The application can take as input also a set of parameters (optional), which have default values in case the user does not want to configure them.
Prepare animal tracking data from Movebank (https://www.movebank.org/cms/movebank-main) for publication in a research repository or the Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/).
Read, explore and visualize Camera Trap Data Packages (Camtrap DP) (https://tdwg.github.io/camtrap-dp/). Camtrap DP is a community developed data exchange format for this type of data. With camtraptor you can read and filter data, create overviews of observed species, relative abundance or effort, and plot these data on a map.
Read and write Frictionless Data Packages. A 'Data Package' (https://specs.frictionlessdata.io/data-package/) is a simple container format and standard to describe and package a collection of (tabular) data. It is typically used to publish FAIR (https://www.go-fair.org/fair-principles/) and open datasets.