Difference between revisions of "DataMiner Algorithms"

Revision as of 15:31, 26 November 2016

The complete list of algorithms supported by the DataMiner service is reported below.

CATCHES_BY_SPECIES
Description	The output is a plot of the catches by species given the filters applied by the user
ICHTHYOP_MODEL_ONE_BY_ONE
Description	This R code packages some extraction to get observed trajectories from data sources (FADs or Drifters) and the execution of Ichthyop driven by OSCAR data to confront simulation with these observatios. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
GENERIC_CHARTS
Description	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.
TIME_GEO_CHART
Description	An algorithm producing an animated gif displaying quantities as colors in time. The color indicates the sum of the values recorded in a country.
GENETICALGORITHM
Description	Genetic Algorithm
MAX_ENT_NICHE_MODELLING
Description	A Maximum-Entropy model for species habitat modeling, based on the implementation by Shapire et al. v 3.3.3k, Princeton University, http://www.cs.princeton.edu/schapire/maxent/. In this adaptation for the D4Science infrastructure, the software accepts a table produced by the Species Product Discovery service and a set of environmental layers in various formats (NetCDF, WFS, WCS, ASC, GeoTiff) via direct links or GeoExplorer UUIDs. The user can also establish the bounding box and the spatial resolution (in decimal deg.) of the training and the projection. The application will adapt the layers to that resolution if this is higher than the native one.The output contains: a thumbnail map of the projected model, the ROC curve, the Omission/Commission chart, a table containing the raw assigned values, a threshold to transform the table into a 0-1 probability distribution, a report of the importance of the used layers in the model, ASCII representations of the input layers to check their alignment.Other processes can be later applied to the raw values to produce a GIS map (e.g. the Statistical Manager Points-to-Map process) and results can be shared. Demo video: http://goo.gl/TYYnTO and instructions http://wiki.i-marine.eu/index.php/MaxEnt
EGIP_ENERGY_YEAR_DISTRIBUTION
Description	An algorithm reporting the energy produced per year by the countries contributing to EGIP
RANDOMSAMPLEONTABLE
Description	Algorithm that allows to perform a sample operation on a table randomly
LISTDBNAMES
Description	Algorithm that allows to view the available database resources names in the Infrastructure
MOST_OBSERVED_TAXA
Description	An algorithm producing a bar chart for the most observed taxa in a certain years range (with respect to the OBIS database)
TIMEEXTRACTION_TABLE
Description	An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
FAO_OCEAN_AREA_COLUMN_CREATOR_FROM_QUADRANT
Description	An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude, latitude and quadrant columns.
FIGIS_SDMX_DATA_CONVERTER
Description	This tool allows to convert easily a SDMX dataset into CSV, by callingthe rsdmx package for R
LISTDBINFO
Description	Algorithm that allows to view information about one chosen resource of Database Type in the Infrastructure
LISTDBSCHEMA
Description	Algorithm that allows to view the schema names of a chosen database for which the type is Postgres
GETTABLEDETAILS
Description	Algorithm that allows to view table details of a chosen database
XYEXTRACTOR
Description	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.
ZEXTRACTION
Description	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.
BIONYM_LOCAL
Description	A fast version of the 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.
STEP_1___VPA_ICCAT_BFT_E_RETROS
Description	STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
SMARTSAMPLEONTABLE
Description	Algorithm that allows to perform a smart sample operation on a table
AQUAMAPSNN
Description	The AquaMaps model trained using a Feed Forward Neural Network. This is a method to train a generic Feed Forward Artifical Neural Network to be used by the AquaMaps Neural Network algorithm. Produces a trained neural network in the form of a compiled file which can be used later.
ABSENCE_CELLS_FROM_AQUAMAPS
Description	An algorithm producing cells and features (HCAF) for a species containing absense points taken by an Aquamaps Distribution
AQUAMAPS_NATIVE_2050
Description	Algorithm for Native 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing species distribution probabilities on half-degree cells according to the AquaMaps approach with native distribution estimated for 2050.
AQUAMAPS_SUITABLE_2050
Description	Algorithm for Suitable 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions for the 2050 scenario.
AQUAMAPS_NATIVE
Description	Algorithm for Native Distribution by AquaMaps. A distribution algorithm that generates a table containing species distribution probabilities on half-degree cells according to the AquaMaps approach for Native (Actual) distributions.
BIOCLIMATE_HSPEN
Description	A transducer algorithm that generates a table containing species envelops (HSPEN) in time, i.e. models capturing species tolerance with respect to environmental parameters, used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the salinity values in several ranges of a set of species envelopes
BIOCLIMATE_HCAF
Description	A transducer algorithm that generates an Half-degree Cells Authority File (HCAF) dataset for a certain time frame, with environmental parameters used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the ocean features contained in HCAF tables
BIONYM
Description	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.
BIONYM_BIODIV
Description	An algorithm implementing BiOnym oriented to Biodiversity Taxa Names Matching with a predefined and optimized workflow. This version applies in sequence the following Matchers: GSay (thr:0.6, maxRes:10), FuzzyMatcher (thr:0.6, maxRes:10), Levenshtein (thr:0.4, maxRes:10), Trigram (thr:0.4, maxRes:10). BiOnym is 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.
DBSCAN
Description	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.
FEED_FORWARD_ANN
Description	A method to train a generic Feed Forward Artifical Neural Network in order to simulate a function from the features space (R^n) to R. Uses the Back-propagation method. Produces a trained neural network in the form of a compiled file which can be used in the FEED FORWARD NEURAL NETWORK DISTRIBUTION algorithm.
LWR
Description	An algorithm to estimate Length-Weight relationship parameters for marine species, using Bayesian methods. Runs an R procedure. Based on the Cube-law theory.
FEED_FORWARD_A_N_N_DISTRIBUTION
Description	A Bayesian method using a Feed Forward Neural Network to simulate a function from the features space (R^n) to R. A modeling algorithm that relies on Neural Networks to simulate a real valued function. It accepts as input a table containing the training dataset and some parameters affecting the algorithm behaviour such as the number of neurons, the learning threshold and the maximum number of iterations.
SUBMITQUERY
Description	Algorithm that allows to submit a query
HRS
Description	An evaluator 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.
HCAF_FILTER
Description	An algorithm producing a HCAF table on a selected Bounding Box (default identifies Indonesia)
HSPEN
Description	The AquMaps HSPEN algorithm. A modeling algorithm that generates a table containing species envelops (HSPEN), i.e. models capturing species tolerance with respect to environmental parameters, to be used by the AquaMaps approach.
KMEANS
Description	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.
OCCURRENCES_MARINE_TERRESTRIAL
Description	A transducer algorithm that produces a table containing occurrence points by filtering them by type of area, i.e. by recognising whether they are marine or terrestrial. Works with up to 10000 points per table.
OCCURRENCES_DUPLICATES_DELETER
Description	A transducer algorithm that produces a duplicate free table of species occurrence points where duplicates have been identified via user defined comparison thresholds. Works with up to 100 000 points
SPECIES_MAP_FROM_POINTS
Description	A transducer algorithm to produce a GIS map from a probability distribution made upf of x,y coordinates and a certain resolution. A maximum of 259000 is allowed
QUALITY_ANALYSIS
Description	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
SPECIES_OBSERVATIONS_PER_AREA
Description	An algorithm producing a bar chart for the distribution of a species along a certain type of marine area (e.g. LME or MEOW)
SPECIES_OBSERVATION_LME_AREA_PER_YEAR
Description	Algorithm returning most observed species in a specific years range (data collected from OBIS database).
TAXONOMY_OBSERVATIONS_TREND_PER_YEAR
Description	Algorithm returning most observations taxonomy trend in a specific years range (with respect to the OBIS database)
XMEANS
Description	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.
LOF
Description	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.
TIMEEXTRACTION
Description	An algorithm to extract a time series of values associated to a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
ZEXTRACTION_TABLE
Description	An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
XYEXTRACTOR_TABLE
Description	An algorithm to extract values associated to a table containing geospatial features (e.g. Vessel Routes, Species distribution maps 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 table and the specification about time and space. The algorithm produces one table containing the values associated to the selected bounding box.
TIMEEXTRACTION
Description	An algorithm to extract a time series of values associated to a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
SAMPLEONTABLE
Description	Algorithm that allows to perform a sample operation on a table
FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED
Description	The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
LISTTABLES
Description	Algorithm that allows to view the table names of a chosen database
MAPS_COMPARISON
Description	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.
FIGIS_SPATIAL_REALLOCATION_GENERIC
Description	The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation.
EGIP_ENERGY_TRENDS
Description	An algorithm reporting the energy trends for the countries contributing to EGIP
TIME_SERIES_ANALYSIS
Description	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.
FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED_TABLE
Description	The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
DISCREPANCY_ANALYSIS
Description	An evaluator algorithm that compares two tables containing real valued vectors. It drives the comparison by relying on a geographical distance threshold and a threshold for K-Statistic.
XYEXTRACTOR
Description	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.
ZEXTRACTION
Description	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.
SGVM_INTERPOLATION
Description	An interpolation method relying on the implementation by the Study Group on VMS (SGVMS). The method uses two interpolation approached to simulate vessels points at a certain temporal resolution. The input is a file in TACSAT format uploaded on the Statistical Manager. The output is another TACSAT file containing interpolated points.The underlying R code has been extracted from the SGVM VMSTools framework. This algorithm comes after a feasibility study (http://goo.gl/risQre) which clarifies the features an e-Infrastructure adds to the original scripts. Limitation: the input will be processed up to 10000 vessels trajectory points. Credits: Hintzen, N. T., Bastardie, F., Beare, D., Piet, G. J., Ulrich, C., Deporte, N., Egekvist, J., et al. 2012. VMStools: Open-source software for the processing, analysis and visualisation of fisheries logbook and VMS data. Fisheries Research, 115-116: 31-43. Hintzen, N. T., Piet, G. J., and Brunel, T. 2010. Improved estimation of trawling tracks using cubic Hermite spline interpolation of position registration data. Fisheries Research, 101: 108-115. VMStools, available as an add-on package for R. Documentation available at https://code.google.com/p/vmstools/. Build versions of VMStools for Window, Mac, Linux available at https://docs.google.com/. Authors: Niels T. Hintzen, Doug Beare
POINTS_TO_MAP
Description	A transducer algorithm to produce a GIS map of points from a set of points with x,y coordinates indications. A maximum of 259000 is allowed
SPECIES_MAP_FROM_CSQUARES
Description	A transducer algorithm to produce a GIS map from a probability distribution associated to a set of csquare codes. A maximum of 259000 is allowed
AQUAMAPS_SUITABLE
Description	Algorithm for Suitable Distribution by AquaMaps. A distribution algorithm that generates a table containing species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions.
MOST_OBSERVED_SPECIES
Description	An algorithm producing a bar chart for the most observed species in a certain years range (with respect to the OBIS database)
BIOCLIMATE_HSPEC
Description	A transducer algorithm that generates a table containing an estimate of species distributions per half-degree cell (HSPEC) in time. Evaluates the climatic changes impact on species presence.
TIMEEXTRACTION_TABLE
Description	An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
OCCURRENCE_ENRICHMENT
Description	An algorithm performing occurrences enrichment. Takes as input one table containing occurrence points for a set of species and a list of environmental layer, taken either from the e-infrastructure GeoNetwork (through the GeoExplorer application) or from direct HTTP links. Produces one table reporting the set of environmental values associated to the occurrence points.
HCAF_INTERPOLATION
Description	Evaluates the climatic changes impact on species presence
POLYGONS_TO_MAP
Description	A transducer algorithm to produce a GIS map of filled polygons associated to x,y coordinates and a certain resolution. A maximum of 259000 is allowed
SPECIES_OBSERVATIONS_TREND_PER_YEAR
Description	An algorithm producing the trend of the observations for a certain species in a certain years range.
PRESENCE_CELLS_GENERATION
Description	An algorithm producing cells and features (HCAF) for a species containing presence points
OCCURRENCE_ENRICHMENT
Description	An algorithm performing occurrences enrichment. Takes as input one table containing occurrence points for a set of species and a list of environmental layer, taken either from the e-infrastructure GeoNetwork (through the GeoExplorer application) or from direct HTTP links. Produces one table reporting the set of environmental values associated to the occurrence points.
ZEXTRACTION_TABLE
Description	An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
EGIP_ENERGY_COUNTRY_DISTRIBUTION
Description	An algorithm reporting the energy produced by the countries contributing to EGIP
SPECIES_OBSERVATION_MEOW_AREA_PER_YEAR
Description	Algorithm returning most observed species in a specific years range (data collected from OBIS database).
EGIP_ENERGY_AGGREGATED_DISTRIBUTION
Description	An algorithm reporting the aggregated energy in a time range produced by the countries contributing to EGIP
XYEXTRACTOR_TABLE
Description	An algorithm to extract values associated to a table containing geospatial features (e.g. Vessel Routes, Species distribution maps 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 table and the specification about time and space. The algorithm produces one table containing the values associated to the selected bounding box.
GEO_CHART
Description	An algorithm producing a charts that displays quantities as colors of countries. The color indicates the sum of the values recorded in a country.
GLOBAL_CATCHES
Description	The output is a plot of the catches given the filters applied by the user
CSQUARE_COLUMN_CREATOR
Description	An algorithm that adds a column containing the CSquare codes associated to longitude and latitude columns.
FAOMSY
Description	An algorithm to be used by Fisheries managers for stock assessment. Estimates the Maximum Sustainable Yield (MSY) of a stock, based on a catch trend. The algorithm has been developed by the Resource Use and Conservation Division of the FAO Fisheries and Aquaculture Department (contact: Yimin Ye, yimin.ye@fao.org). It is applicable to a CSV file containing metadata and catch statistics for a set of marine species and produces MSY estimates for each species. The CSV must follow a FAO-defined format (e.g. http://goo.gl/g6YtVx). The output is made up of two (optional) files: one for sucessfully processed species and another one for species that could not be processed because data were not sufficient to estimate MSY.
PROJECTIONS_REPORT_VPA_ICCAT_BFT_E
Description	Projections_report: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
FAO_OCEAN_AREA_COLUMN_CREATOR
Description	An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude and latitude columns.
WTG
Description	An algorithm to process Eiscat sites data
ABSENCE_GENERATION_FROM_OBIS
Description	An algorithm to estimate absence records from survey data in OBIS. Based on the work in Coro, G., Magliozzi, C., Berghe, E. V., Bailly, N., Ellenbroek, A., & Pagano, P. (2016). Estimating absence locations of marine species from data of scientific surveys in OBIS. Ecological Modelling, 323, 61-76.
TUNA_ATLAS_DATA_ACCESS
Description	This R code enables users to adapt a SQL query to get data from Sardara database storing global
CATCHES_BY_FLAGS_SIMPLIFIED_VERSION
Description	The output is a plot of the catches by flags given the filters applied by the user
TIME_SERIES_CHARTS
Description	An algorithm producing time series charts of attributes vs. quantities. Charts are displayed per quantity column and superposing quantities are summed.
RASTER_DATA_PUBLISHER
Description	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.
SIMULFISHKPIS
Description	Create 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. Updated version on 30.08.2016
CATCHES_BY_TYPE_OF_SCHOOL
Description	The output is a plot of the catches by type of school given the filters applied by the user
ESTIMATE_MONTHLY_FISHING_EFFORT
Description	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
ECOPATH_WITH_ECOSIM
Description	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.
GRID_CWP_TO_COORDINATES
Description	An algorithm that adds longitude, latitude and resolution columns analysing a column containing FAO Ocean Area codes (CWP format).
ICHTHYOP_MODEL_MULTIPLE_RUNS
Description	This R code enables to extract multiple observed trajectories from data sources (FADs or Drifters) and to run (for each trajectory) an execution of Ichthyop driven by OSCAR data oin order to confront simulation with these observations. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION
Description	The outputs are temporal and spatial distribution of the catches aggregated following a selected variable and given the filters applied by the user
ESTIMATE_FISHING_ACTIVITY
Description	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
FEED_FORWARD_NEURAL_NETWORK_DEEP_REGRESSOR
Description	The algorithm simulates a real-valued vector function using a set of interconnected trained Feed Forward Artificial Neural Network and returns a table containing the function actual inputs and the predicted outputs
IMPORT_FISHERIES_FORMATTED_DATASET___QUICK_IMPORT
Description	Import into the global database a dataframe that has previously been formatted to the standard database format. After the import you will be able to compute the fisheries indicators (e.g. the algorithm Compute fisheries indicators from own formatted dataset) using your data.
COMPUTE_FISHERIES_INDICATORS_FROM_OWN_FORMATTED_DATASET
Description	Compute some fisheries indicators (plots and maps) from a dataset that you have previously formatted and imported through the algorithm Import Fisheries Formatted Dataset. The codes to use for the filters in this algorithm must be the input dataset ones.
CSQUARES_TO_COORDINATES
Description	An algorithm that adds longitude, latitude and resolution columns analysing a column containing c-square codes.
ESRI_GRID_EXTRACTION
Description	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 ESRI GRID ASCII file containing the values associated to the selected bounding box.
ICHTHYOP_NETCDF_OUTPUT_TO_SHAPEFILE
Description	This code turns trajectories of ichthyop model outputs delivered with netCDF into a shapefile
SEADATANET_INTERPOLATOR
Description	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.
WEB_APP_PUBLISHER
Description	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.
CATCHES_BY_GEAR_SIMPLIFIED_VERSION
Description	The output is a plot of the catches by gear given the filters applied by the user
MPA_INTERSECT_V2
Description	An algorithm to compute areas of geomorphic features in an EEZ or ECOREGION area and in its intersecting Marine Protected Areas (MPAs)
TRAJECTORY_BUILDER
Description	A module to build trajectories from raw GPS observation using several constraints.
CATCHES_AGGREGATED_FOLLOWING_A_SELECT_VARIABLE
Description	The outputs are temporal and spatial distribution of the catches aggregated gollowing a selected variable and given the filters applied by the user
CCAMLR_EXPORTER_TOOL
Description	Functions to generates json data and graphs based on CCMLAR input data
STAT_VAL
Description	statistical validation of BIPARTITE WEIGHTED network
NCOUTPUTS2CSV_VPA_ICCAT_BFT_E
Description	ncOutputs2csv: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
READWFS
Description	Read WFS requests and export attributes
PARALLELIZED_STEP1_VPA_ICCAT_BFT_E_RETROS
Description	STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
STEP_4_VPA_ICCAT_BFT_E_REPORT
Description	ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
QUICK_RANK_TRAIN
Description	QuickRank algorithm suite for training
QUICK_RANK_TRAIN_NO_VALIDATION
Description	QuickRank algorithm suite for training with no validation file
QUICK_RANK_TEST
Description	QuickRank algorithm suite for test
MAKE_ICHTHYOP_NETCDF_CF_COMPLIANT
Description	This code turns ichthyop netCDF into another netCDF whis is compliant with CF conventions and enables agreggation with NCML files
FEED_FORWARD_NEURAL_NETWORK_REGRESSOR
Description	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
CATCHES_BY_FLAGS
Description	The output is a plot of the catches by flags given the filters applied by the user
STEP_2__VPA_ICCAT_BFT_E_VISUALISATION
Description	ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
CATCHES_BY_GEARS
Description	The output is a plot of the catches by gears for tuna fisheries given the filters applied by the user
STEP_3___VPA_ICCAT_BFT_E_PROJECTION
Description	STEP 3: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
CMSY_2
Description	The CMSY method for data-limited stock assessment. Described in Froese, R., Demirel, N., Coro, G., Kleisner, K. M., Winker, H. (2016). Estimating fisheries reference points from catch and resilience. Fish and Fisheries. Paper link: http://onlinelibrary.wiley.com/doi/10.1111/faf.12190/ Full Instructions and code: https://github.com/SISTA16/cmsy
FEED_FORWARD_NEURAL_NETWORK_TRAINER
Description	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
CATCHES_BY_SPECIES_SIMPLIFIED_VERSION
Description	The output is a plot of the catches by species given the filters applied by the user
SHARK_ABUNDANCY
Description	SHARK Abundancy simple computation
TUNA_ATLAS_INDICATOR_1__SPECIES_BY_OCEAN_
Description	This visualization shows a time serie of Tuna Catches per species per ocean by using multiple interactive visualization libraries
ENSEMBLE_MODEL
Description	Implementation of an ensemble model approach to support advice and management in fisheries. Implementation on Thorpe et al. (2015). Evaluation and management implications of uncertainty in a multispecies size structured model of population and community responses to fishing. Methods in Ecology and Evolution, 6(1), 49-58.
FEED_FORWARD_NEURAL_NETWORK_CLOUD_REGRESSOR
Description	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
CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION_V2
Description	The outputs are temporal and spatial distribution of the catches aggregated following a selected variable and given the filters applied by the user
WHOLE_STEPS_VPA_ICCAT_BFT_E
Description	Whole Steps: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD

Difference between revisions of "DataMiner Algorithms"

Revision as of 15:31, 26 November 2016

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@@ Line 6: / Line 6: @@
 {|border="1" cellpadding="5" cellspacing="0"
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_SPECIES">CATCHES_BY_SPECIES</div>
+|-
+|| Description
+||The output is a plot of the catches by species given the filters applied by the user
+|-
-! colspan=2 bgcolor=lightgrey | <div id="ENSEMBLE_MODEL">ENSEMBLE_MODEL</div>
+! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_MODEL_ONE_BY_ONE">ICHTHYOP_MODEL_ONE_BY_ONE</div>
 |-
 || Description
-||Implementation of an ensemble model approach to support advice and management in fisheries. Implementation on Thorpe et al. (2015). Evaluation and management implications of uncertainty in a multispecies size structured model of population and community responses to fishing. Methods in Ecology and Evolution, 6(1), 49-58.
+||This R code packages some extraction to get observed trajectories from data sources (FADs or Drifters) and the execution of Ichthyop driven by OSCAR data to confront simulation with these observatios. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SAMPLEONTABLE">SAMPLEONTABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="GENERIC_CHARTS">GENERIC_CHARTS</div>
 |-
 || Description
-||Algorithm that allows to perform a sample operation on a table
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="POINTS_TO_MAP">POINTS_TO_MAP</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIME_GEO_CHART">TIME_GEO_CHART</div>
 |-
 || Description
-||A transducer algorithm to produce a GIS map of points from a set of points with x,y coordinates indications. A maximum of 259000 is allowed
+||An algorithm producing an animated gif displaying quantities as colors in time. The color indicates the sum of the values recorded in a country.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SMARTSAMPLEONTABLE">SMARTSAMPLEONTABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="GENETICALGORITHM">GENETICALGORITHM</div>
 |-
 || Description
-||Algorithm that allows to perform a smart sample operation on a table
+||Genetic Algorithm
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION">TIMEEXTRACTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="MAX_ENT_NICHE_MODELLING">MAX_ENT_NICHE_MODELLING</div>
 |-
 || Description
-||An algorithm to extract a time series of values associated to a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
+||A Maximum-Entropy model for species habitat modeling, based on the implementation by Shapire et al. v 3.3.3k, Princeton University, http://www.cs.princeton.edu/schapire/maxent/. In this adaptation for the D4Science infrastructure, the software accepts a table produced by the Species Product Discovery service and a set of environmental layers in various formats (NetCDF, WFS, WCS, ASC, GeoTiff) via direct links or GeoExplorer UUIDs. The user can also establish the bounding box and the spatial resolution (in decimal deg.) of the training and the projection. The application will adapt the layers to that resolution if this is higher than the native one.The output contains: a thumbnail map of the projected model, the ROC curve, the Omission/Commission chart, a table containing the raw assigned values, a threshold to transform the table into a 0-1 probability distribution, a report of the importance of the used layers in the model, ASCII representations of the input layers to check their alignment.Other processes can be later applied to the raw values to produce a GIS map (e.g. the Statistical Manager Points-to-Map process) and results can be shared. Demo video: http://goo.gl/TYYnTO and instructions http://wiki.i-marine.eu/index.php/MaxEnt
 |-
-! colspan=2 bgcolor=lightgrey | <div id="HCAF_FILTER">HCAF_FILTER</div>
+! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_YEAR_DISTRIBUTION">EGIP_ENERGY_YEAR_DISTRIBUTION</div>
 |-
 || Description
-||An algorithm producing a HCAF table on a selected Bounding Box (default identifies Indonesia)
+||An algorithm reporting the energy produced per year by the countries contributing to EGIP
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FAO_OCEAN_AREA_COLUMN_CREATOR">FAO_OCEAN_AREA_COLUMN_CREATOR</div>
+! colspan=2 bgcolor=lightgrey | <div id="RANDOMSAMPLEONTABLE">RANDOMSAMPLEONTABLE</div>
 |-
 || Description
-||An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude and latitude columns.
+||Algorithm that allows to perform a sample operation on a table randomly
+|-
+! colspan=2 bgcolor=lightgrey | <div id="LISTDBNAMES">LISTDBNAMES</div>
+|-
+|| Description
+||Algorithm that allows to view the available database resources names in the Infrastructure
 |-
@@ Line 55: / Line 66: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="DBSCAN">DBSCAN</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION_TABLE">TIMEEXTRACTION_TABLE</div>
 |-
 || Description
-||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.
+||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
+|-
+! colspan=2 bgcolor=lightgrey | <div id="FAO_OCEAN_AREA_COLUMN_CREATOR_FROM_QUADRANT">FAO_OCEAN_AREA_COLUMN_CREATOR_FROM_QUADRANT</div>
+|-
+|| Description
+||An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude, latitude and quadrant columns.
 |-
@@ Line 67: / Line 84: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="HCAF_INTERPOLATION">HCAF_INTERPOLATION</div>
+! colspan=2 bgcolor=lightgrey | <div id="LISTDBINFO">LISTDBINFO</div>
 |-
 || Description
-||Evaluates the climatic changes impact on species presence
+||Algorithm that allows to view information about one chosen resource of Database Type in the Infrastructure
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION">ZEXTRACTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="LISTDBSCHEMA">LISTDBSCHEMA</div>
 |-
 || Description
-||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.
+||Algorithm that allows to view the schema names of a chosen database for which the type is Postgres
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FAO_OCEAN_AREA_COLUMN_CREATOR_FROM_QUADRANT">FAO_OCEAN_AREA_COLUMN_CREATOR_FROM_QUADRANT</div>
+! colspan=2 bgcolor=lightgrey | <div id="GETTABLEDETAILS">GETTABLEDETAILS</div>
 |-
 || Description
-||An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude, latitude and quadrant columns.
+||Algorithm that allows to view table details of a chosen database
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SGVM_INTERPOLATION">SGVM_INTERPOLATION</div>
+! colspan=2 bgcolor=lightgrey | <div id="XYEXTRACTOR">XYEXTRACTOR</div>
 |-
 || Description
-||An interpolation method relying on the implementation by the Study Group on VMS (SGVMS). The method uses two interpolation approached to simulate vessels points at a certain temporal resolution. The input is a file in TACSAT format uploaded on the Statistical Manager. The output is another TACSAT file containing interpolated points.The underlying R code has been extracted from the SGVM VMSTools framework. This algorithm comes after a feasibility study (http://goo.gl/risQre) which clarifies the features an e-Infrastructure adds to the original scripts. Limitation: the input will be processed up to 10000 vessels trajectory points. Credits: Hintzen, N. T., Bastardie, F., Beare, D., Piet, G. J., Ulrich, C., Deporte, N., Egekvist, J., et al. 2012. VMStools: Open-source software for the processing, analysis and visualisation of fisheries logbook and VMS data. Fisheries Research, 115-116: 31-43. Hintzen, N. T., Piet, G. J., and Brunel, T. 2010. Improved estimation of trawling tracks using cubic Hermite spline interpolation of position registration data. Fisheries Research, 101: 108-115. VMStools, available as an add-on package for R. Documentation available at https://code.google.com/p/vmstools/.  Build versions of VMStools for Window, Mac, Linux available at https://docs.google.com/. Authors: Niels T. Hintzen, Doug Beare
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_SUITABLE_2050">AQUAMAPS_SUITABLE_2050</div>
+! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION">ZEXTRACTION</div>
 |-
 || Description
-||Algorithm for Suitable 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions for the 2050 scenario.
+||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.
 |-
@@ Line 103: / Line 120: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATION_MEOW_AREA_PER_YEAR">SPECIES_OBSERVATION_MEOW_AREA_PER_YEAR</div>
+! colspan=2 bgcolor=lightgrey | <div id="STEP_1___VPA_ICCAT_BFT_E_RETROS">STEP_1___VPA_ICCAT_BFT_E_RETROS</div>
 |-
 || Description
-||Algorithm returning most observed species in a specific years range (data collected from OBIS database).
+||STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
-! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HCAF">BIOCLIMATE_HCAF</div>
+! colspan=2 bgcolor=lightgrey | <div id="SMARTSAMPLEONTABLE">SMARTSAMPLEONTABLE</div>
 |-
 || Description
-||A transducer algorithm that generates an Half-degree Cells Authority File (HCAF) dataset for a certain time frame, with environmental parameters used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the ocean features contained in HCAF tables
+||Algorithm that allows to perform a smart sample operation on a table
 |-
-! colspan=2 bgcolor=lightgrey | <div id="MAPS_COMPARISON">MAPS_COMPARISON</div>
+! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPSNN">AQUAMAPSNN</div>
 |-
 || Description
-||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.
+||The AquaMaps model trained using a Feed Forward Neural Network. This is a method to train a generic Feed Forward Artifical Neural Network to be used by the AquaMaps Neural Network algorithm. Produces a trained neural network in the form of a compiled file which can be used later.
 |-
@@ Line 127: / Line 144: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="DISCREPANCY_ANALYSIS">DISCREPANCY_ANALYSIS</div>
+! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_NATIVE_2050">AQUAMAPS_NATIVE_2050</div>
 |-
 || Description
-||An evaluator algorithm that compares two tables containing real valued vectors. It drives the comparison by relying on a geographical distance threshold and a threshold for K-Statistic.
+||Algorithm for Native 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach with native distribution estimated for 2050.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="PRESENCE_CELLS_GENERATION">PRESENCE_CELLS_GENERATION</div>
+! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_SUITABLE_2050">AQUAMAPS_SUITABLE_2050</div>
 |-
 || Description
-||An algorithm producing cells and features (HCAF) for a species containing presence points
+||Algorithm for Suitable 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions for the 2050 scenario.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LWR">LWR</div>
+! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_NATIVE">AQUAMAPS_NATIVE</div>
 |-
 || Description
-||An algorithm to estimate Length-Weight relationship parameters for marine species, using Bayesian methods. Runs an R procedure. Based on the Cube-law theory.
+||Algorithm for Native Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for Native (Actual) distributions.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CMSY">CMSY</div>
+! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HSPEN">BIOCLIMATE_HSPEN</div>
 |-
 || Description
-||An algorithm to estimate the Maximum Sustainable Yield from a catch statistic. If also a Biomass trend is provided, MSY estimation is provided also with higher precision. The method has been developed by R. Froese, G. Coro, N. Demirel and K. Kleisner.
+||A transducer algorithm that generates a table containing species envelops (HSPEN) in time, i.e. models capturing species tolerance with respect to environmental parameters, used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the salinity values in several ranges of a set of species envelopes
 |-
-! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_NATIVE">AQUAMAPS_NATIVE</div>
+! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HCAF">BIOCLIMATE_HCAF</div>
 |-
 || Description
-||Algorithm for Native Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for Native (Actual) distributions.
+||A transducer algorithm that generates an Half-degree Cells Authority File (HCAF) dataset for a certain time frame, with environmental parameters used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the ocean features contained in HCAF tables
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_MERGER">OCCURRENCES_MERGER</div>
+! colspan=2 bgcolor=lightgrey | <div id="BIONYM">BIONYM</div>
 |-
 || Description
-||A transducer algorithm that produces a duplicate-free table resulting from the union of two occurrence points tables where points equivalence is identified via user defined comparison thresholds. Works with up to 10000 points per table. Between two Ocurrence Sets, enrichs the Left Set with the elements of the Right Set that are not in the Left Set. Updates the elements of the Left Set with more recent elements in the Right Set. If one element in the Left Set corresponds to several recent elements in the Right Set, these will be all substituted to the element of the Left Set.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="QUALITY_ANALYSIS">QUALITY_ANALYSIS</div>
+! colspan=2 bgcolor=lightgrey | <div id="BIONYM_BIODIV">BIONYM_BIODIV</div>
 |-
 || Description
-||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
+||An algorithm implementing BiOnym oriented to Biodiversity Taxa Names Matching with a predefined and optimized workflow. This version applies in sequence the following Matchers: GSay (thr:0.6, maxRes:10), FuzzyMatcher (thr:0.6, maxRes:10), Levenshtein (thr:0.4, maxRes:10), Trigram (thr:0.4, maxRes:10). BiOnym is 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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="BIONYM_BIODIV">BIONYM_BIODIV</div>
+! colspan=2 bgcolor=lightgrey | <div id="DBSCAN">DBSCAN</div>
 |-
 || Description
-||An algorithm implementing BiOnym oriented to Biodiversity Taxa Names Matching with a predefined and optimized workflow. This version applies in sequence the following Matchers: GSay (thr:0.6, maxRes:10), FuzzyMatcher (thr:0.6, maxRes:10), Levenshtein (thr:0.4, maxRes:10), Trigram (thr:0.4, maxRes:10). BiOnym is 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.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LISTDBINFO">LISTDBINFO</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_ANN">FEED_FORWARD_ANN</div>
 |-
 || Description
-||Algorithm that allows to view information about one chosen resource of Database Type in the Infrastructure
+||A method to train a generic Feed Forward Artifical Neural Network in order to simulate a function from the features space (R^n) to R. Uses the Back-propagation method. Produces a trained neural network in the form of a compiled file which can be used in the FEED FORWARD NEURAL NETWORK DISTRIBUTION algorithm.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_TRENDS">EGIP_ENERGY_TRENDS</div>
+! colspan=2 bgcolor=lightgrey | <div id="LWR">LWR</div>
 |-
 || Description
-||An algorithm reporting the energy trends for the countries contributing to EGIP
+||An algorithm to estimate Length-Weight relationship parameters for marine species, using Bayesian methods. Runs an R procedure. Based on the Cube-law theory.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LISTTABLES">LISTTABLES</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_A_N_N_DISTRIBUTION">FEED_FORWARD_A_N_N_DISTRIBUTION</div>
 |-
 || Description
-||Algorithm that allows to view the table names of a chosen database
+||A Bayesian method using a Feed Forward Neural Network to simulate a function from the features space (R^n) to R. A modeling algorithm that relies on Neural Networks to simulate a real valued function. It accepts as input a table containing the training dataset and some parameters affecting the algorithm behaviour such as the number of neurons, the learning threshold and the maximum number of iterations.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="MOST_OBSERVED_SPECIES">MOST_OBSERVED_SPECIES</div>
+! colspan=2 bgcolor=lightgrey | <div id="SUBMITQUERY">SUBMITQUERY</div>
 |-
 || Description
-||An algorithm producing a bar chart for the most observed species in a certain years range (with respect to the OBIS database)
+||Algorithm that allows to submit a query
 |-
-! colspan=2 bgcolor=lightgrey | <div id="RANDOMSAMPLEONTABLE">RANDOMSAMPLEONTABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="HRS">HRS</div>
 |-
 || Description
-||Algorithm that allows to perform a sample operation on a table randomly
+||An evaluator 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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SPECIES_MAP_FROM_CSQUARES">SPECIES_MAP_FROM_CSQUARES</div>
+! colspan=2 bgcolor=lightgrey | <div id="HCAF_FILTER">HCAF_FILTER</div>
 |-
 || Description
-||A transducer algorithm to produce a GIS map from a probability distribution associated to a set of csquare codes. A maximum of 259000 is allowed
+||An algorithm producing a HCAF table on a selected Bounding Box (default identifies Indonesia)
 |-
-! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPSNN">AQUAMAPSNN</div>
+! colspan=2 bgcolor=lightgrey | <div id="HSPEN">HSPEN</div>
 |-
 || Description
-||The AquaMaps model trained using a Feed Forward Neural Network. This is a method to train a generic Feed Forward Artifical Neural Network to be used by the AquaMaps Neural Network algorithm. Produces a trained neural network in the form of a compiled file which can be used later.
+||The AquMaps HSPEN algorithm. A modeling algorithm that generates a table containing species envelops (HSPEN), i.e. models capturing species tolerance with respect to environmental parameters, to be used by the AquaMaps approach.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HSPEC">BIOCLIMATE_HSPEC</div>
+! colspan=2 bgcolor=lightgrey | <div id="KMEANS">KMEANS</div>
 |-
 || Description
-||A transducer algorithm that generates a table containing an estimate of species distributions per half-degree cell (HSPEC) in time. Evaluates the climatic changes impact on species presence.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="HSPEN">HSPEN</div>
+! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_MARINE_TERRESTRIAL">OCCURRENCES_MARINE_TERRESTRIAL</div>
 |-
 || Description
-||The AquMaps HSPEN algorithm. A modeling algorithm that generates a table containing species envelops (HSPEN), i.e. models capturing species tolerance with respect to environmental parameters, to be used by the AquaMaps approach.
+||A transducer algorithm that produces a table containing occurrence points by filtering them by type of area, i.e. by recognising whether they are marine or terrestrial. Works with up to 10000 points per table.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATION_LME_AREA_PER_YEAR">SPECIES_OBSERVATION_LME_AREA_PER_YEAR</div>
+! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_DUPLICATES_DELETER">OCCURRENCES_DUPLICATES_DELETER</div>
 |-
 || Description
-||Algorithm returning most observed species in a specific years range (data collected from OBIS database).
+||A transducer algorithm that produces a duplicate free table of species occurrence points where duplicates have been identified via user defined comparison thresholds. Works with up to 100 000 points
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED">FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED</div>
+! colspan=2 bgcolor=lightgrey | <div id="SPECIES_MAP_FROM_POINTS">SPECIES_MAP_FROM_POINTS</div>
 |-
 || Description
-||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
+||A transducer algorithm to produce a GIS map from a probability distribution made upf of x,y coordinates and a certain resolution. A maximum of 259000 is allowed
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCE_ENRICHMENT">OCCURRENCE_ENRICHMENT</div>
+! colspan=2 bgcolor=lightgrey | <div id="QUALITY_ANALYSIS">QUALITY_ANALYSIS</div>
 |-
 || Description
-||An algorithm performing occurrences enrichment. Takes as input one table containing occurrence points for a set of species and a list of environmental layer, taken either from the e-infrastructure GeoNetwork (through the GeoExplorer application) or from direct HTTP links. Produces one table reporting the set of environmental values associated to the occurrence points.
+||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
 |-
@@ Line 253: / Line 270: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_SUBTRACTION">OCCURRENCES_SUBTRACTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATION_LME_AREA_PER_YEAR">SPECIES_OBSERVATION_LME_AREA_PER_YEAR</div>
 |-
 || Description
-||A transducer algorithm that produces a table resulting from the difference between two occurrence points tables where points equivalence is identified via user defined comparison thresholds. Works with up to 10000 points per table. Between two Ocurrence Sets, keeps the elements of the Left Set that are not similar to any element in the Right Set.
+||Algorithm returning most observed species in a specific years range (data collected from OBIS database).
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_DUPLICATES_DELETER">OCCURRENCES_DUPLICATES_DELETER</div>
+! colspan=2 bgcolor=lightgrey | <div id="TAXONOMY_OBSERVATIONS_TREND_PER_YEAR">TAXONOMY_OBSERVATIONS_TREND_PER_YEAR</div>
 |-
 || Description
-||A transducer algorithm that produces a duplicate free table of species occurrence points where duplicates have been identified via user defined comparison thresholds. Works with up to 100 000 points
+||Algorithm returning most observations taxonomy trend in a specific years range (with respect to the OBIS database)
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SPECIES_MAP_FROM_POINTS">SPECIES_MAP_FROM_POINTS</div>
+! colspan=2 bgcolor=lightgrey | <div id="XMEANS">XMEANS</div>
 |-
 || Description
-||A transducer algorithm to produce a GIS map from a probability distribution made upf of x,y coordinates and a certain resolution. A maximum of 259000 is allowed
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GENERIC_CHARTS">GENERIC_CHARTS</div>
+! colspan=2 bgcolor=lightgrey | <div id="LOF">LOF</div>
 |-
 || Description
-||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.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_YEAR_DISTRIBUTION">EGIP_ENERGY_YEAR_DISTRIBUTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION">TIMEEXTRACTION</div>
 |-
 || Description
-||An algorithm reporting the energy produced per year by the countries contributing to EGIP
+||An algorithm to extract a time series of values associated to a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="XYEXTRACTOR">XYEXTRACTOR</div>
+! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION_TABLE">ZEXTRACTION_TABLE</div>
 |-
 || Description
-||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.
+||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FAOMSY">FAOMSY</div>
+! colspan=2 bgcolor=lightgrey | <div id="XYEXTRACTOR_TABLE">XYEXTRACTOR_TABLE</div>
 |-
 || Description
-||An algorithm to be used by Fisheries managers for stock assessment. Estimates the Maximum Sustainable Yield (MSY) of a stock, based on a catch trend. The algorithm has been developed by the Resource Use and Conservation Division of the FAO Fisheries and Aquaculture Department (contact: Yimin Ye, yimin.ye@fao.org). It is applicable to a CSV file containing metadata and catch statistics for a set of marine species and produces MSY estimates for each species. The CSV must follow a FAO-defined format (e.g. http://goo.gl/g6YtVx). The output is made up of two (optional) files: one for sucessfully processed species and another one for species that could not be processed because data were not sufficient to estimate MSY.
+||An algorithm to extract values associated to a table containing geospatial features (e.g. Vessel Routes, Species distribution maps 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 table and the specification about time and space. The algorithm produces one table containing the values associated to the selected bounding box.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GRID_CWP_TO_COORDINATES">GRID_CWP_TO_COORDINATES</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION">TIMEEXTRACTION</div>
 |-
 || Description
-||An algorithm that adds longitude, latitude and resolution columns analysing a column containing FAO Ocean Area codes (CWP format).
+||An algorithm to extract a time series of values associated to a geospatial features repository (e.g. NETCDF, ASC, GeoTiff files etc. ). The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION_TABLE">ZEXTRACTION_TABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="SAMPLEONTABLE">SAMPLEONTABLE</div>
 |-
 || Description
-||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
+||Algorithm that allows to perform a sample operation on a table
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SUBMITQUERY">SUBMITQUERY</div>
+! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED">FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED</div>
 |-
 || Description
-||Algorithm that allows to submit a query
+||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CSQUARES_TO_COORDINATES">CSQUARES_TO_COORDINATES</div>
+! colspan=2 bgcolor=lightgrey | <div id="LISTTABLES">LISTTABLES</div>
 |-
 || Description
-||An algorithm that adds longitude, latitude and resolution columns analysing a column containing c-square codes.
+||Algorithm that allows to view the table names of a chosen database
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GEO_CHART">GEO_CHART</div>
+! colspan=2 bgcolor=lightgrey | <div id="MAPS_COMPARISON">MAPS_COMPARISON</div>
 |-
 || Description
-||An algorithm producing a charts that displays quantities as colors of countries. The color indicates the sum of the values recorded in a country.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_MARINE_TERRESTRIAL">OCCURRENCES_MARINE_TERRESTRIAL</div>
+! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_GENERIC">FIGIS_SPATIAL_REALLOCATION_GENERIC</div>
 |-
 || Description
-||A transducer algorithm that produces a table containing occurrence points by filtering them by type of area, i.e. by recognising whether they are marine or terrestrial. Works with up to 10000 points per table.
+||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATIONS_TREND_PER_YEAR">SPECIES_OBSERVATIONS_TREND_PER_YEAR</div>
+! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_TRENDS">EGIP_ENERGY_TRENDS</div>
 |-
 || Description
-||An algorithm producing the trend of the observations for a certain species in a certain years range.
+||An algorithm reporting the energy trends for the countries contributing to EGIP
 |-
-! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HSPEN">BIOCLIMATE_HSPEN</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIME_SERIES_ANALYSIS">TIME_SERIES_ANALYSIS</div>
 |-
 || Description
-||A transducer algorithm that generates a table containing species envelops (HSPEN) in time, i.e. models capturing species tolerance with respect to environmental parameters, used by the AquaMaps approach. Evaluates the climatic changes impact on the variation of the salinity values in several ranges of a set of species envelopes
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_AGGREGATED_DISTRIBUTION">EGIP_ENERGY_AGGREGATED_DISTRIBUTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED_TABLE">FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED_TABLE</div>
 |-
 || Description
-||An algorithm reporting the aggregated energy in a time range produced by the countries contributing to EGIP
+||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CSQUARE_COLUMN_CREATOR">CSQUARE_COLUMN_CREATOR</div>
+! colspan=2 bgcolor=lightgrey | <div id="DISCREPANCY_ANALYSIS">DISCREPANCY_ANALYSIS</div>
 |-
 || Description
-||An algorithm that adds a column containing the CSquare codes associated to longitude and latitude columns.
+||An evaluator algorithm that compares two tables containing real valued vectors. It drives the comparison by relying on a geographical distance threshold and a threshold for K-Statistic.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TIME_SERIES_CHARTS">TIME_SERIES_CHARTS</div>
+! colspan=2 bgcolor=lightgrey | <div id="XYEXTRACTOR">XYEXTRACTOR</div>
 |-
 || Description
-||An algorithm producing time series charts of attributes vs. quantities. Charts are displayed per quantity column and superposing quantities are summed.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="HRS">HRS</div>
+! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION">ZEXTRACTION</div>
 |-
 || Description
-||An evaluator 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.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_GENERIC">FIGIS_SPATIAL_REALLOCATION_GENERIC</div>
+! colspan=2 bgcolor=lightgrey | <div id="SGVM_INTERPOLATION">SGVM_INTERPOLATION</div>
 |-
 || Description
-||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation.
+||An interpolation method relying on the implementation by the Study Group on VMS (SGVMS). The method uses two interpolation approached to simulate vessels points at a certain temporal resolution. The input is a file in TACSAT format uploaded on the Statistical Manager. The output is another TACSAT file containing interpolated points.The underlying R code has been extracted from the SGVM VMSTools framework. This algorithm comes after a feasibility study (http://goo.gl/risQre) which clarifies the features an e-Infrastructure adds to the original scripts. Limitation: the input will be processed up to 10000 vessels trajectory points. Credits: Hintzen, N. T., Bastardie, F., Beare, D., Piet, G. J., Ulrich, C., Deporte, N., Egekvist, J., et al. 2012. VMStools: Open-source software for the processing, analysis and visualisation of fisheries logbook and VMS data. Fisheries Research, 115-116: 31-43. Hintzen, N. T., Piet, G. J., and Brunel, T. 2010. Improved estimation of trawling tracks using cubic Hermite spline interpolation of position registration data. Fisheries Research, 101: 108-115. VMStools, available as an add-on package for R. Documentation available at https://code.google.com/p/vmstools/.  Build versions of VMStools for Window, Mac, Linux available at https://docs.google.com/. Authors: Niels T. Hintzen, Doug Beare
 |-
-! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_COUNTRY_DISTRIBUTION">EGIP_ENERGY_COUNTRY_DISTRIBUTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="POINTS_TO_MAP">POINTS_TO_MAP</div>
 |-
 || Description
-||An algorithm reporting the energy produced by the countries contributing to EGIP
+||A transducer algorithm to produce a GIS map of points from a set of points with x,y coordinates indications. A maximum of 259000 is allowed
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION_TABLE">TIMEEXTRACTION_TABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="SPECIES_MAP_FROM_CSQUARES">SPECIES_MAP_FROM_CSQUARES</div>
 |-
 || Description
-||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
+||A transducer algorithm to produce a GIS map from a probability distribution associated to a set of csquare codes. A maximum of 259000 is allowed
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TIME_SERIES_ANALYSIS">TIME_SERIES_ANALYSIS</div>
+! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_SUITABLE">AQUAMAPS_SUITABLE</div>
 |-
 || Description
-||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.
+||Algorithm for Suitable Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="STEP_3___VPA_ICCAT_BFT_E_PROJECTION">STEP_3___VPA_ICCAT_BFT_E_PROJECTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="MOST_OBSERVED_SPECIES">MOST_OBSERVED_SPECIES</div>
 |-
 || Description
-||STEP 3: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||An algorithm producing a bar chart for the most observed species in a certain years range (with respect to the OBIS database)
 |-
-! colspan=2 bgcolor=lightgrey | <div id="MAX_ENT_NICHE_MODELLING">MAX_ENT_NICHE_MODELLING</div>
+! colspan=2 bgcolor=lightgrey | <div id="BIOCLIMATE_HSPEC">BIOCLIMATE_HSPEC</div>
 |-
 || Description
-||A Maximum-Entropy model for species habitat modeling, based on the implementation by Shapire et al. v 3.3.3k, Princeton University, http://www.cs.princeton.edu/schapire/maxent/. In this adaptation for the D4Science infrastructure, the software accepts a table produced by the Species Product Discovery service and a set of environmental layers in various formats (NetCDF, WFS, WCS, ASC, GeoTiff) via direct links or GeoExplorer UUIDs. The user can also establish the bounding box and the spatial resolution (in decimal deg.) of the training and the projection. The application will adapt the layers to that resolution if this is higher than the native one.The output contains: a thumbnail map of the projected model, the ROC curve, the Omission/Commission chart, a table containing the raw assigned values, a threshold to transform the table into a 0-1 probability distribution, a report of the importance of the used layers in the model, ASCII representations of the input layers to check their alignment.Other processes can be later applied to the raw values to produce a GIS map (e.g. the Statistical Manager Points-to-Map process) and results can be shared. Demo video: http://goo.gl/TYYnTO and instructions http://wiki.i-marine.eu/index.php/MaxEnt
+||A transducer algorithm that generates a table containing an estimate of species distributions per half-degree cell (HSPEC) in time. Evaluates the climatic changes impact on species presence.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="BIONYM">BIONYM</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIMEEXTRACTION_TABLE">TIMEEXTRACTION_TABLE</div>
 |-
 || Description
-||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.
+||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TIME_GEO_CHART">TIME_GEO_CHART</div>
+! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCE_ENRICHMENT">OCCURRENCE_ENRICHMENT</div>
 |-
 || Description
-||An algorithm producing an animated gif displaying quantities as colors in time. The color indicates the sum of the values recorded in a country.
+||An algorithm performing occurrences enrichment. Takes as input one table containing occurrence points for a set of species and a list of environmental layer, taken either from the e-infrastructure GeoNetwork (through the GeoExplorer application) or from direct HTTP links. Produces one table reporting the set of environmental values associated to the occurrence points.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_NATIVE_2050">AQUAMAPS_NATIVE_2050</div>
+! colspan=2 bgcolor=lightgrey | <div id="HCAF_INTERPOLATION">HCAF_INTERPOLATION</div>
 |-
 || Description
-||Algorithm for Native 2050 Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach with native distribution estimated for 2050.
+||Evaluates the climatic changes impact on species presence
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ESRI_GRID_EXTRACTION">ESRI_GRID_EXTRACTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="POLYGONS_TO_MAP">POLYGONS_TO_MAP</div>
 |-
 || Description
-||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 ESRI GRID ASCII file containing the values associated to the selected bounding box.
+||A transducer algorithm to produce a GIS map of filled polygons associated to x,y coordinates and a certain resolution. A maximum of 259000 is allowed
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TUNA_ATLAS_INDICATOR_1__SPECIES_BY_OCEAN_">TUNA_ATLAS_INDICATOR_1__SPECIES_BY_OCEAN_</div>
+! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATIONS_TREND_PER_YEAR">SPECIES_OBSERVATIONS_TREND_PER_YEAR</div>
 |-
 || Description
-||This visualization shows a time serie of Tuna Catches per species per ocean by using multiple interactive visualization libraries
+||An algorithm producing the trend of the observations for a certain species in a certain years range.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_MODEL_MULTIPLE_RUNS">ICHTHYOP_MODEL_MULTIPLE_RUNS</div>
+! colspan=2 bgcolor=lightgrey | <div id="PRESENCE_CELLS_GENERATION">PRESENCE_CELLS_GENERATION</div>
 |-
 || Description
-||This R code enables to extract multiple observed trajectories from data sources (FADs or Drifters) and to run (for each trajectory) an execution of Ichthyop driven by OSCAR data oin order to confront simulation with these observations. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
+||An algorithm producing cells and features (HCAF) for a species containing presence points
 |-
-! colspan=2 bgcolor=lightgrey | <div id="AQUAMAPS_SUITABLE">AQUAMAPS_SUITABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCE_ENRICHMENT">OCCURRENCE_ENRICHMENT</div>
 |-
 || Description
-||Algorithm for Suitable Distribution by AquaMaps. A distribution algorithm that generates a table containing  species distribution probabilities on half-degree cells according to the AquaMaps approach for suitable (potential) distributions.
+||An algorithm performing occurrences enrichment. Takes as input one table containing occurrence points for a set of species and a list of environmental layer, taken either from the e-infrastructure GeoNetwork (through the GeoExplorer application) or from direct HTTP links. Produces one table reporting the set of environmental values associated to the occurrence points.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED_TABLE">FIGIS_SPATIAL_REALLOCATION_SIMPLIFIED_TABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="ZEXTRACTION_TABLE">ZEXTRACTION_TABLE</div>
 |-
 || Description
-||The Spatial Reallocaton algorithm allows to estimate statistics for other areas from those where they were reported. The algorithm is based on spatial disaggregation technics and provides at now an area-weighted reallocation. This simplified algorithm is specifically targeting users from the FAO Fisheries and Aquaculture department, aims to facilitate its execution by doing abstraction of the intersections to provide.
+||An algorithm to extract a time series of values associated to a table containing geospatial information. The algorithm analyses the time series and automatically searches for hidden periodicities. It produces one chart of the time series, one table containing the time series values and possibly the spectrogram.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_A_N_N_DISTRIBUTION">FEED_FORWARD_A_N_N_DISTRIBUTION</div>
+! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_COUNTRY_DISTRIBUTION">EGIP_ENERGY_COUNTRY_DISTRIBUTION</div>
 |-
 || Description
-||A Bayesian method using a Feed Forward Neural Network to simulate a function from the features space (R^n) to R. A modeling algorithm that relies on Neural Networks to simulate a real valued function. It accepts as input a table containing the training dataset and some parameters affecting the algorithm behaviour such as the number of neurons, the learning threshold and the maximum number of iterations.
+||An algorithm reporting the energy produced by the countries contributing to EGIP
 |-
-! colspan=2 bgcolor=lightgrey | <div id="POLYGONS_TO_MAP">POLYGONS_TO_MAP</div>
+! colspan=2 bgcolor=lightgrey | <div id="SPECIES_OBSERVATION_MEOW_AREA_PER_YEAR">SPECIES_OBSERVATION_MEOW_AREA_PER_YEAR</div>
 |-
 || Description
-||A transducer algorithm to produce a GIS map of filled polygons associated to x,y coordinates and a certain resolution. A maximum of 259000 is allowed
+||Algorithm returning most observed species in a specific years range (data collected from OBIS database).
+|-
+! colspan=2 bgcolor=lightgrey | <div id="EGIP_ENERGY_AGGREGATED_DISTRIBUTION">EGIP_ENERGY_AGGREGATED_DISTRIBUTION</div>
+|-
+|| Description
+||An algorithm reporting the aggregated energy in a time range produced by the countries contributing to EGIP
 |-
@@ Line 469: / Line 492: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="COMPUTE_FISHERIES_INDICATORS_FROM_OWN_FORMATTED_DATASET">COMPUTE_FISHERIES_INDICATORS_FROM_OWN_FORMATTED_DATASET</div>
+! colspan=2 bgcolor=lightgrey | <div id="GEO_CHART">GEO_CHART</div>
 |-
 || Description
-||Compute some fisheries indicators (plots and maps) from a dataset that you have previously formatted and imported through the algorithm Import Fisheries Formatted Dataset. The codes to use for the filters in this algorithm must be the input dataset ones.
+||An algorithm producing a charts that displays quantities as colors of countries. The color indicates the sum of the values recorded in a country.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_MODEL_ONE_BY_ONE">ICHTHYOP_MODEL_ONE_BY_ONE</div>
+! colspan=2 bgcolor=lightgrey | <div id="GLOBAL_CATCHES">GLOBAL_CATCHES</div>
 |-
 || Description
-||This R code packages some extraction to get observed trajectories from data sources (FADs or Drifters) and the execution of Ichthyop driven by OSCAR data to confront simulation with these observatios. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
+||The output is a plot of the catches given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_MODEL_ONE_BY_ONE">ICHTHYOP_MODEL_ONE_BY_ONE</div>
+! colspan=2 bgcolor=lightgrey | <div id="CSQUARE_COLUMN_CREATOR">CSQUARE_COLUMN_CREATOR</div>
 |-
 || Description
-||This R code packages some extraction to get observed trajectories from data sources (FADs or Drifters) and the execution of Ichthyop driven by OSCAR data to confront simulation with these observatios. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
+||An algorithm that adds a column containing the CSquare codes associated to longitude and latitude columns.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TAXONOMY_OBSERVATIONS_TREND_PER_YEAR">TAXONOMY_OBSERVATIONS_TREND_PER_YEAR</div>
+! colspan=2 bgcolor=lightgrey | <div id="FAOMSY">FAOMSY</div>
 |-
 || Description
-||Algorithm returning most observations taxonomy trend in a specific years range (with respect to the OBIS database)
+||An algorithm to be used by Fisheries managers for stock assessment. Estimates the Maximum Sustainable Yield (MSY) of a stock, based on a catch trend. The algorithm has been developed by the Resource Use and Conservation Division of the FAO Fisheries and Aquaculture Department (contact: Yimin Ye, yimin.ye@fao.org). It is applicable to a CSV file containing metadata and catch statistics for a set of marine species and produces MSY estimates for each species. The CSV must follow a FAO-defined format (e.g. http://goo.gl/g6YtVx). The output is made up of two (optional) files: one for sucessfully processed species and another one for species that could not be processed because data were not sufficient to estimate MSY.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="OCCURRENCES_INTERSECTOR">OCCURRENCES_INTERSECTOR</div>
+! colspan=2 bgcolor=lightgrey | <div id="PROJECTIONS_REPORT_VPA_ICCAT_BFT_E">PROJECTIONS_REPORT_VPA_ICCAT_BFT_E</div>
 |-
 || Description
-||A transducer algorithm that produces a table of species occurrence points that are contained in both the two starting tables where points equivalence is identified via user defined comparison thresholds. Works with up to 10000 points per table. Between two ocurrence sets, it keeps the elements of the Right Set that are similar to elements in the Left Set.
+||Projections_report: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
-! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_ANN">FEED_FORWARD_ANN</div>
+! colspan=2 bgcolor=lightgrey | <div id="FAO_OCEAN_AREA_COLUMN_CREATOR">FAO_OCEAN_AREA_COLUMN_CREATOR</div>
 |-
 || Description
-||A method to train a generic Feed Forward Artifical Neural Network in order to simulate a function from the features space (R^n) to R. Uses the Back-propagation method. Produces a trained neural network in the form of a compiled file which can be used in the FEED FORWARD NEURAL NETWORK DISTRIBUTION algorithm.
+||An algorithm that adds a column containing the FAO Ocean Area codes associated to longitude and latitude columns.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GETTABLEDETAILS">GETTABLEDETAILS</div>
+! colspan=2 bgcolor=lightgrey | <div id="WTG">WTG</div>
 |-
 || Description
-||Algorithm that allows to view table details of a chosen database
+||An algorithm to process Eiscat sites data
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LISTDBNAMES">LISTDBNAMES</div>
+! colspan=2 bgcolor=lightgrey | <div id="ABSENCE_GENERATION_FROM_OBIS">ABSENCE_GENERATION_FROM_OBIS</div>
 |-
 || Description
-||Algorithm that allows to view the available database resources names in the Infrastructure
+||An algorithm to estimate absence records from survey data in OBIS. Based on the work in Coro, G., Magliozzi, C., Berghe, E. V., Bailly, N., Ellenbroek, A., &amp; Pagano, P. (2016). Estimating absence locations of marine species from data of scientific surveys in OBIS. Ecological Modelling, 323, 61-76.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LISTDBSCHEMA">LISTDBSCHEMA</div>
+! colspan=2 bgcolor=lightgrey | <div id="TUNA_ATLAS_DATA_ACCESS">TUNA_ATLAS_DATA_ACCESS</div>
 |-
 || Description
-||Algorithm that allows to view the schema names of a chosen database for which the type is Postgres
+||This R code enables users to adapt a SQL query to get data from Sardara database storing global
 |-
-! colspan=2 bgcolor=lightgrey | <div id="MPA_INTERSECT_V2">MPA_INTERSECT_V2</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_FLAGS_SIMPLIFIED_VERSION">CATCHES_BY_FLAGS_SIMPLIFIED_VERSION</div>
 |-
 || Description
-||An algorithm to compute areas of geomorphic features in an EEZ or ECOREGION area and in its intersecting Marine Protected Areas (MPAs)
+||The output is a plot of the catches by flags given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ESTIMATE_MONTHLY_FISHING_EFFORT">ESTIMATE_MONTHLY_FISHING_EFFORT</div>
+! colspan=2 bgcolor=lightgrey | <div id="TIME_SERIES_CHARTS">TIME_SERIES_CHARTS</div>
 |-
 || Description
-||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
+||An algorithm producing time series charts of attributes vs. quantities. Charts are displayed per quantity column and superposing quantities are summed.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="WEB_APP_PUBLISHER">WEB_APP_PUBLISHER</div>
+! colspan=2 bgcolor=lightgrey | <div id="RASTER_DATA_PUBLISHER">RASTER_DATA_PUBLISHER</div>
 |-
 || Description
-||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.
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="STAT_VAL">STAT_VAL</div>
+! colspan=2 bgcolor=lightgrey | <div id="SIMULFISHKPIS">SIMULFISHKPIS</div>
 |-
 || Description
-||statistical validation of BIPARTITE WEIGHTED network
+||Create 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. Updated version on 30.08.2016
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_AGGREGATED_FOLLOWING_A_SELECT_VARIABLE">CATCHES_AGGREGATED_FOLLOWING_A_SELECT_VARIABLE</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_TYPE_OF_SCHOOL">CATCHES_BY_TYPE_OF_SCHOOL</div>
 |-
 || Description
-||The outputs are temporal and spatial distribution of the catches aggregated gollowing a selected variable and given the filters applied by the user
+||The output is a plot of the catches by type of school given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GENETICALGORITHM">GENETICALGORITHM</div>
+! colspan=2 bgcolor=lightgrey | <div id="ESTIMATE_MONTHLY_FISHING_EFFORT">ESTIMATE_MONTHLY_FISHING_EFFORT</div>
 |-
 || Description
-||Genetic Algorithm
+||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
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_TYPE_OF_SCHOOL">CATCHES_BY_TYPE_OF_SCHOOL</div>
+! colspan=2 bgcolor=lightgrey | <div id="ECOPATH_WITH_ECOSIM">ECOPATH_WITH_ECOSIM</div>
 |-
 || Description
-||The output is a plot of the catches by type of school given the filters applied by the user
+||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., &amp; Walters, C. J. (2004). Ecopath with Ecosim: methods, capabilities and limitations. Ecological modelling, 172(2), 109-139.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_GEAR_SIMPLIFIED_VERSION">CATCHES_BY_GEAR_SIMPLIFIED_VERSION</div>
+! colspan=2 bgcolor=lightgrey | <div id="GRID_CWP_TO_COORDINATES">GRID_CWP_TO_COORDINATES</div>
 |-
 || Description
-||The output is a plot of the catches by gear given the filters applied by the user
+||An algorithm that adds longitude, latitude and resolution columns analysing a column containing FAO Ocean Area codes (CWP format).
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TRAJECTORY_BUILDER">TRAJECTORY_BUILDER</div>
+! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_MODEL_MULTIPLE_RUNS">ICHTHYOP_MODEL_MULTIPLE_RUNS</div>
 |-
 || Description
-||A module to build trajectories from raw GPS observation using several constraints.
+||This R code enables to extract multiple observed trajectories from data sources (FADs or Drifters) and to run (for each trajectory) an execution of Ichthyop driven by OSCAR data oin order to confront simulation with these observations. netCDF outputs are transformed into maps to be visualized with Qgis. Ichthyop is a free Java tool designed to study the effects of physical and biological factors on ichthyoplankton dynamics
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CCAMLR_EXPORTER_TOOL">CCAMLR_EXPORTER_TOOL</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION">CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION</div>
 |-
 || Description
-||Functions to generates json data and graphs based on CCMLAR input data
+||The outputs are temporal and spatial distribution of the catches aggregated following a selected variable and given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="STEP_1___VPA_ICCAT_BFT_E_RETROS">STEP_1___VPA_ICCAT_BFT_E_RETROS</div>
+! colspan=2 bgcolor=lightgrey | <div id="ESTIMATE_FISHING_ACTIVITY">ESTIMATE_FISHING_ACTIVITY</div>
 |-
 || Description
-||STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||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
 |-
-! colspan=2 bgcolor=lightgrey | <div id="STEP_2__VPA_ICCAT_BFT_E_VISUALISATION">STEP_2__VPA_ICCAT_BFT_E_VISUALISATION</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_NEURAL_NETWORK_DEEP_REGRESSOR">FEED_FORWARD_NEURAL_NETWORK_DEEP_REGRESSOR</div>
 |-
 || Description
-||ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||The algorithm simulates a real-valued vector function using a set of interconnected trained Feed Forward Artificial Neural Network and returns a table containing the function actual inputs and the predicted outputs
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SIMULFISHKPIS">SIMULFISHKPIS</div>
+! colspan=2 bgcolor=lightgrey | <div id="IMPORT_FISHERIES_FORMATTED_DATASET___QUICK_IMPORT">IMPORT_FISHERIES_FORMATTED_DATASET___QUICK_IMPORT</div>
 |-
 || Description
-||Create 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. Updated version on 30.08.2016
+||Import into the global database a dataframe that has previously been formatted to the standard database format. After the import you will be able to compute the fisheries indicators (e.g. the algorithm Compute fisheries indicators from own formatted dataset) using your data.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="TUNA_ATLAS_DATA_ACCESS">TUNA_ATLAS_DATA_ACCESS</div>
+! colspan=2 bgcolor=lightgrey | <div id="COMPUTE_FISHERIES_INDICATORS_FROM_OWN_FORMATTED_DATASET">COMPUTE_FISHERIES_INDICATORS_FROM_OWN_FORMATTED_DATASET</div>
 |-
 || Description
-||This R code enables users to adapt a SQL query to get data from Sardara database storing global
+||Compute some fisheries indicators (plots and maps) from a dataset that you have previously formatted and imported through the algorithm Import Fisheries Formatted Dataset. The codes to use for the filters in this algorithm must be the input dataset ones.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SHAPEFILE_PUBLISHER">SHAPEFILE_PUBLISHER</div>
+! colspan=2 bgcolor=lightgrey | <div id="CSQUARES_TO_COORDINATES">CSQUARES_TO_COORDINATES</div>
 |-
 || Description
-||An algorithm to publish shapefiles under WMS and WFS standards in the e-Infrastructure. The produced WMS, WFS links are reported as output of this process. The map will be available in the VRE for consultation.
+||An algorithm that adds longitude, latitude and resolution columns analysing a column containing c-square codes.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="MPA_INTERSECT">MPA_INTERSECT</div>
+! colspan=2 bgcolor=lightgrey | <div id="ESRI_GRID_EXTRACTION">ESRI_GRID_EXTRACTION</div>
 |-
 || Description
-||An algorithm to intersect MPA polygons with WFS spatial data layers
+||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 ESRI GRID ASCII file containing the values associated to the selected bounding box.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="KMEANS">KMEANS</div>
+! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_NETCDF_OUTPUT_TO_SHAPEFILE">ICHTHYOP_NETCDF_OUTPUT_TO_SHAPEFILE</div>
 |-
 || Description
-||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.
+||This code turns trajectories of ichthyop model outputs delivered with netCDF into a shapefile
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_SPECIES_SIMPLIFIED_VERSION">CATCHES_BY_SPECIES_SIMPLIFIED_VERSION</div>
+! colspan=2 bgcolor=lightgrey | <div id="SEADATANET_INTERPOLATOR">SEADATANET_INTERPOLATOR</div>
 |-
 || Description
-||The output is a plot of the catches by species given the filters applied by the user
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TRAIN_NO_VALIDATION">QUICK_RANK_TRAIN_NO_VALIDATION</div>
+! colspan=2 bgcolor=lightgrey | <div id="WEB_APP_PUBLISHER">WEB_APP_PUBLISHER</div>
 |-
 || Description
-||QuickRank algorithm suite for training with no validation file
+||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.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GLOBAL_CATCHES">GLOBAL_CATCHES</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_GEAR_SIMPLIFIED_VERSION">CATCHES_BY_GEAR_SIMPLIFIED_VERSION</div>
 |-
 || Description
-||The output is a plot of the catches given the filters applied by the user
+||The output is a plot of the catches by gear given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ECOPATH_WITH_ECOSIM">ECOPATH_WITH_ECOSIM</div>
+! colspan=2 bgcolor=lightgrey | <div id="MPA_INTERSECT_V2">MPA_INTERSECT_V2</div>
 |-
 || Description
-||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., &amp; Walters, C. J. (2004). Ecopath with Ecosim: methods, capabilities and limitations. Ecological modelling, 172(2), 109-139.
+||An algorithm to compute areas of geomorphic features in an EEZ or ECOREGION area and in its intersecting Marine Protected Areas (MPAs)
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ABSENCE_GENERATION_FROM_OBIS">ABSENCE_GENERATION_FROM_OBIS</div>
+! colspan=2 bgcolor=lightgrey | <div id="TRAJECTORY_BUILDER">TRAJECTORY_BUILDER</div>
 |-
 || Description
-||An algorithm to estimate absence records from survey data in OBIS. Based on the work in Coro, G., Magliozzi, C., Berghe, E. V., Bailly, N., Ellenbroek, A., &amp; Pagano, P. (2016). Estimating absence locations of marine species from data of scientific surveys in OBIS. Ecological Modelling, 323, 61-76.
+||A module to build trajectories from raw GPS observation using several constraints.
 |-
-! colspan=2 bgcolor=lightgrey | <div id="WHOLE_STEPS_VPA_ICCAT_BFT_E">WHOLE_STEPS_VPA_ICCAT_BFT_E</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_AGGREGATED_FOLLOWING_A_SELECT_VARIABLE">CATCHES_AGGREGATED_FOLLOWING_A_SELECT_VARIABLE</div>
 |-
 || Description
-||Whole Steps: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||The outputs are temporal and spatial distribution of the catches aggregated gollowing a selected variable and given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="GENERIC_WORKER">GENERIC_WORKER</div>
+! colspan=2 bgcolor=lightgrey | <div id="CCAMLR_EXPORTER_TOOL">CCAMLR_EXPORTER_TOOL</div>
 |-
 || Description
-||An algorithm that executes another other algorithm
+||Functions to generates json data and graphs based on CCMLAR input data
 |-
-! colspan=2 bgcolor=lightgrey | <div id="RASTER_DATA_PUBLISHER">RASTER_DATA_PUBLISHER</div>
+! colspan=2 bgcolor=lightgrey | <div id="STAT_VAL">STAT_VAL</div>
 |-
 || Description
-||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.
+||statistical validation of BIPARTITE WEIGHTED network
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_GEARS">CATCHES_BY_GEARS</div>
+! colspan=2 bgcolor=lightgrey | <div id="NCOUTPUTS2CSV_VPA_ICCAT_BFT_E">NCOUTPUTS2CSV_VPA_ICCAT_BFT_E</div>
 |-
 || Description
-||The output is a plot of the catches by gears for tuna fisheries given the filters applied by the user
+||ncOutputs2csv: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_FLAGS">CATCHES_BY_FLAGS</div>
+! colspan=2 bgcolor=lightgrey | <div id="READWFS">READWFS</div>
 |-
 || Description
-||The output is a plot of the catches by flags given the filters applied by the user
+||Read WFS requests and export attributes
+|-
+! colspan=2 bgcolor=lightgrey | <div id="PARALLELIZED_STEP1_VPA_ICCAT_BFT_E_RETROS">PARALLELIZED_STEP1_VPA_ICCAT_BFT_E_RETROS</div>
+|-
+|| Description
+||STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
@@ Line 691: / Line 720: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="READWFS">READWFS</div>
+! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TRAIN">QUICK_RANK_TRAIN</div>
 |-
 || Description
-||Read WFS requests and export attributes
+||QuickRank algorithm suite for training
 |-
-! colspan=2 bgcolor=lightgrey | <div id="PARALLELIZED_STEP1_VPA_ICCAT_BFT_E_RETROS">PARALLELIZED_STEP1_VPA_ICCAT_BFT_E_RETROS</div>
+! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TRAIN_NO_VALIDATION">QUICK_RANK_TRAIN_NO_VALIDATION</div>
 |-
 || Description
-||STEP 1: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||QuickRank algorithm suite for training with no validation file
+|-
+! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TEST">QUICK_RANK_TEST</div>
+|-
+|| Description
+||QuickRank algorithm suite for test
 |-
@@ Line 709: / Line 744: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="ICHTHYOP_NETCDF_OUTPUT_TO_SHAPEFILE">ICHTHYOP_NETCDF_OUTPUT_TO_SHAPEFILE</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_NEURAL_NETWORK_REGRESSOR">FEED_FORWARD_NEURAL_NETWORK_REGRESSOR</div>
 |-
 || Description
-||This code turns trajectories of ichthyop model outputs delivered with netCDF into a shapefile
+||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
 |-
-! colspan=2 bgcolor=lightgrey | <div id="VPA_ICCAT_BFT_E_REPORT">VPA_ICCAT_BFT_E_REPORT</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_FLAGS">CATCHES_BY_FLAGS</div>
+|-
+|| Description
+||The output is a plot of the catches by flags given the filters applied by the user
+|-
+! colspan=2 bgcolor=lightgrey | <div id="STEP_2__VPA_ICCAT_BFT_E_VISUALISATION">STEP_2__VPA_ICCAT_BFT_E_VISUALISATION</div>
 |-
 || Description
@@ Line 721: / Line 762: @@
 |-
-! colspan=2 bgcolor=lightgrey | <div id="XMEANS">XMEANS</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_GEARS">CATCHES_BY_GEARS</div>
 |-
 || Description
-||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.
+||The output is a plot of the catches by gears for tuna fisheries given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="KNITR_COMPILER">KNITR_COMPILER</div>
+! colspan=2 bgcolor=lightgrey | <div id="STEP_3___VPA_ICCAT_BFT_E_PROJECTION">STEP_3___VPA_ICCAT_BFT_E_PROJECTION</div>
 |-
 || Description
-||An algorithm to compile Knitr documents. Developed by IRD (reference Julien Bard, julien.barde@ird.fr)
+||STEP 3: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
-! colspan=2 bgcolor=lightgrey | <div id="SEADATANET_INTERPOLATOR">SEADATANET_INTERPOLATOR</div>
+! colspan=2 bgcolor=lightgrey | <div id="CMSY_2">CMSY_2</div>
 |-
 || Description
-||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.
+||The CMSY method for data-limited stock assessment. Described in Froese, R., Demirel, N., Coro, G., Kleisner, K. M., Winker, H. (2016). Estimating fisheries reference points from catch and resilience. Fish and Fisheries. Paper link: http://onlinelibrary.wiley.com/doi/10.1111/faf.12190/  Full Instructions and code: https://github.com/SISTA16/cmsy
 |-
-! colspan=2 bgcolor=lightgrey | <div id="LOF">LOF</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_NEURAL_NETWORK_TRAINER">FEED_FORWARD_NEURAL_NETWORK_TRAINER</div>
 |-
 || Description
-||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.
+||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
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-! colspan=2 bgcolor=lightgrey | <div id="ESTIMATE_FISHING_ACTIVITY">ESTIMATE_FISHING_ACTIVITY</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_SPECIES_SIMPLIFIED_VERSION">CATCHES_BY_SPECIES_SIMPLIFIED_VERSION</div>
 |-
 || Description
-||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
+||The output is a plot of the catches by species given the filters applied by the user
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-! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TRAIN">QUICK_RANK_TRAIN</div>
+! colspan=2 bgcolor=lightgrey | <div id="SHARK_ABUNDANCY">SHARK_ABUNDANCY</div>
 |-
 || Description
-||QuickRank algorithm suite for training
+||SHARK Abundancy simple computation
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_FLAGS_SIMPLIFIED_VERSION">CATCHES_BY_FLAGS_SIMPLIFIED_VERSION</div>
+! colspan=2 bgcolor=lightgrey | <div id="TUNA_ATLAS_INDICATOR_1__SPECIES_BY_OCEAN_">TUNA_ATLAS_INDICATOR_1__SPECIES_BY_OCEAN_</div>
 |-
 || Description
-||The output is a plot of the catches by flags given the filters applied by the user
+||This visualization shows a time serie of Tuna Catches per species per ocean by using multiple interactive visualization libraries
 |-
-! colspan=2 bgcolor=lightgrey | <div id="IMPORT_FISHERIES_FORMATTED_DATASET___QUICK_IMPORT">IMPORT_FISHERIES_FORMATTED_DATASET___QUICK_IMPORT</div>
+! colspan=2 bgcolor=lightgrey | <div id="ENSEMBLE_MODEL">ENSEMBLE_MODEL</div>
 |-
 || Description
-||Import into the global database a dataframe that has previously been formatted to the standard database format. After the import you will be able to compute the fisheries indicators (e.g. the algorithm Compute fisheries indicators from own formatted dataset) using your data.
+||Implementation of an ensemble model approach to support advice and management in fisheries. Implementation on Thorpe et al. (2015). Evaluation and management implications of uncertainty in a multispecies size structured model of population and community responses to fishing. Methods in Ecology and Evolution, 6(1), 49-58.
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-! colspan=2 bgcolor=lightgrey | <div id="QUICK_RANK_TEST">QUICK_RANK_TEST</div>
+! colspan=2 bgcolor=lightgrey | <div id="FEED_FORWARD_NEURAL_NETWORK_CLOUD_REGRESSOR">FEED_FORWARD_NEURAL_NETWORK_CLOUD_REGRESSOR</div>
 |-
 || Description
-||QuickRank algorithm suite for test
+||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
 |-
-! colspan=2 bgcolor=lightgrey | <div id="PROJECTIONS_REPORT_VPA_ICCAT_BFT_E">PROJECTIONS_REPORT_VPA_ICCAT_BFT_E</div>
+! colspan=2 bgcolor=lightgrey | <div id="CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION_V2">CATCHES_AGGREGATED_FOLLOWING_A_SELECTED_DIMENSION_V2</div>
 |-
 || Description
-||Projections_report: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
+||The outputs are temporal and spatial distribution of the catches aggregated following a selected variable and given the filters applied by the user
 |-
-! colspan=2 bgcolor=lightgrey | <div id="CATCHES_BY_SPECIES">CATCHES_BY_SPECIES</div>
+! colspan=2 bgcolor=lightgrey | <div id="WHOLE_STEPS_VPA_ICCAT_BFT_E">WHOLE_STEPS_VPA_ICCAT_BFT_E</div>
 |-
 || Description
-||The output is a plot of the catches by species given the filters applied by the user
+||Whole Steps: ICCAT (Eastern) Bluefin Tuna Stock Assessment. This set of R and Fortran code have been provided by ICCAT and IFremer to execute the whole Stock assessment workflow online integration has been done with the help (mediation) of CNR and IRD
 |-
 |}