Name |
Description |
Requirements |

Absence Cells | An algorithm producing cells and features (HCAF) for a species containing absense points taken by an Aquamaps Distribution | Requires the DataMiner Cluster |

BiOnym | An algorithm implementing BiOnym, a flexible workflow approach to taxon name matching. The workflow allows to activate several taxa names matching algorithms and to get the list of possible transcriptions for a list of input raw species names with possible authorship indication. | Requires the DataMiner Cluster |

Dbscan | A clustering algorithm for real valued vectors that relies on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. A maximum of 4000 points is allowed. | Requires the DataMiner Cluster |

Ecopath with Ecosim | Ecopath with Ecosim (EwE) is a free ecological/ecosystem modeling software suite. This algorithm implementation expects a model and a configuration file as inputs; the result of the analysis is returned as a zip archive. References: Christensen, V., & Walters, C. J. (2004). Ecopath with Ecosim: methods, capabilities and limitations. Ecological modelling, 172(2), 109-139. | Requires the DataMiner Cluster |

ESRI-GRID Extraction | An algorithm that estimates activity hours (fishing or other) from vessels trajectories, adds bathymetry information to the table and classifies (point-by-point) fishing activity of the involved vessels according to two algorithms: one based on speed (activity_class_speed output column) and the other based on speed and bathymetry (activity_class_speed_bath output column). The algorithm produces new columns containing this information. This algorithm is based on the paper 'Deriving Fishing Monthly Effort and Caught Species' (Coro et al. 2013, in proc. of OCEANS - Bergen, 2013 MTS/IEEE). Example of input table (NAFO anonymised data): http://goo.gl/3auJkM | Requires the DataMiner Cluster |

Estimate Monthly Fishing Effort | An algorithm that estimates fishing exploitation at 0.5 degrees resolution from activity-classified vessels trajectories. Produces a table with csquare codes, latitudes, longitudes and resolution and associated overall fishing hours in the time frame of the vessels activity. Requires each activity point to be classified as Fishing or other. This algorithm is based on the paper 'Deriving Fishing Monthly Effort and Caught Species' (Coro et al. 2013, in proc. of OCEANS - Bergen, 2013 MTS/IEEE). Example of input table (NAFO anonymised data): http://goo.gl/3auJkM | Requires the DataMiner Cluster |

The algorithm simulates a real-valued vector function using a trained Feed Forward Artificial Neural Network and returns a table containing the function actual inputs and the predicted outputs | Requires the DataMiner Cluster | |

The algorithm trains a Feed Forward Artificial Neural Network using an online Back-Propagation procedure and returns the training error and a binary file containing the trained network | Requires the DataMiner Cluster | |

An algorithm producing generic charts of attributes vs. quantities. Charts are displayed per quantity column. Histograms, Scattering and Radar charts are produced for the top ten quantities. A gaussian distribution reports overall statistics for the quantities. | Requires the DataMiner Cluster | |

HRS | An algorithm that calculates the Habitat Representativeness Score, i.e. an indicator of the assessment of whether a specific survey coverage or another environmental features dataset, contains data that are representative of all available habitat variable combinations in an area. | Requires the DataMiner Cluster |

Kmeans | A clustering algorithm for real valued vectors that relies on the k-means algorithm, i.e. a method aiming to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. A Maximum of 4000 points is allowed. | Requires the DataMiner Cluster |

Lof | Local Outlier Factor (LOF). A clustering algorithm for real valued vectors that relies on Local Outlier Factor algorithm, i.e. an algorithm for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours. A Maximum of 4000 points is allowed. | Requires the DataMiner Cluster |

Maps Comparison | An algorithm for comparing two OGC/NetCDF maps in seamless way to the user. The algorithm assesses the similarities between two geospatial maps by comparing them in a point-to-point fashion. It accepts as input the two geospatial maps (via their UUIDs in the infrastructure spatial data repository - recoverable through the Geoexplorer portlet) and some parameters affecting the comparison such as the z-index, the time index, the comparison threshold. Note: in the case of WFS layers it makes comparisons on the last feature column. | Requires the DataMiner Cluster |

Mpa Intersect V2 | An algorithm to compute areas of geomorphic features in an EEZ or ECOREGION area and in its intersecting Marine Protected Areas (MPAs) | Requires the DataMiner Cluster |

An evaluator algorithm that assesses the effectiveness of a distribution model by computing the Receiver Operating Characteristics (ROC), the Area Under Curve (AUC) and the Accuracy of a model | Requires the DataMiner Cluster | |

Raster Data Publisher | This algorithm publishes a raster file as a maps or datasets in the e-Infrastructure. NetCDF-CF files are encouraged, as WMS and WCS maps will be produced using this format. For other types of files (GeoTiffs, ASC etc.) only the raw datasets will be published. The resulting map or dataset will be accessible via the VRE GeoExplorer by the VRE participants. | Requires the DataMiner Cluster |

SEADATANET Interpolator | A connector for the SeaDataNet infrastructure. This algorithms invokes the Data-Interpolating Variational Analysis (DIVA) SeaDataNet service to interpolate spatial data. The model uses GEBCO bathymetry data and requires an estimate of the maximum spatial span of the correlation between points and the signal-to-noise ratio, among the other parameters. It can interpolate up to 10,000 points randomly taken from the input table. As output, it produces a NetCDF file with a uniform grid of values. This powerful interpolation model is described in Troupin et al. 2012, 'Generation of analysis and consistent error ﬁelds using the Data Interpolating Variational Analysis (Diva)', Ocean Modelling, 52-53, 90-101. | Requires the DataMiner Cluster |

Simulfishkpis | Creates simulation models for KPIs fish production in Aquaculture. Import data from SimulFish Growth database via URLs. Calculated KPIs are FCR, SFR, Mortality using Regression models generated by GAMs and MARs methodologies. | Requires the DataMiner Cluster |

Species Maps from Points | An algorithm to produce a GIS map from a probability distribution made up of x,y coordinates and a certain resolution. | Requires the DataMiner Cluster |

Stat Val | Statistical validation of BIPARTITE WEIGHTED network. | Requires the DataMiner Cluster |

Time Geo Chart | An algorithm producing an animated gif displaying quantities as colors in time. The color indicates the sum of the values recorded in a country. | Requires the DataMiner Cluster |

An algorithms applying signal processing to a non uniform time series. A maximum of 10000 distinct points in time is allowed to be processed. The process uniformly samples the series, then extracts hidden periodicities and signal properties. The sampling period is the shortest time difference between two points. Finally, by using Caterpillar-SSA the algorithm forecasts the Time Series. The output shows the detected periodicity, the forecasted signal and the spectrogram. |
Requires the DataMiner Cluster | |

WEB App Publisher | This algorithm publishes a zip file containing a Web site, based on html and javascript in the e-Infrastructure. It generates a public URL to the application that can be shared. | Requires the DataMiner Cluster |

Whole Steps Vpa Iccat Bft E | ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute a whole Stock assessment workflow | Requires the DataMiner Cluster |

Xmeans | A clustering algorithm for occurrence points that relies on the X-Means algorithm, i.e. an extended version of the K-Means algorithm improved by an Improve-Structure part. A Maximum of 4000 points is allowed. | Requires the DataMiner Cluster |

XYExtractor | An algorithm to extract values associated to an environmental feature repository (e.g. NETCDF, ASC, GeoTiff files etc. ). A grid of points at a certain resolution is specified by the user and values are associated to the points from the environmental repository. It accepts as one geospatial repository ID (via their UUIDs in the infrastructure spatial data repository - recoverable through the Geoexplorer portlet) or a direct link to a file and the specification about time and space. The algorithm produces one table containing the values associated to the selected bounding box. | Requires the DataMiner Cluster |

ZExtraction | An algorithm to extract the Z values from a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the repository and automatically extracts the Z values according to the resolution wanted by the user. It produces one chart of the Z values and one table containing the values. | Requires the DataMiner Cluster |