The table below summarizes the services and technologies provided by BlueBRIDGE. You can equip your Virtual Research Environment (Click here for more information on VREs) with one or more of the services/technologies listed below.

Name Description/Link
Data harmonization The Data Harmonization facility supports the semi-automatic harmonization of time series with respect to code lists and controlled vocabularies. It provides a suite for human curators that can define tailored template for harmonizing series of time series. 
Data Miner

DataMiner Manager[1] is a computational engine for performing data analytics operations. Specifically, it offers a unique access to perform data analytics on heterogeneous data, which may reside either at client side, in the form of comma-separated values files, or be remotely hosted, possibly in a database.

[1] If you need to run an algorithm or a model on the infrastructure you need Data Miner
Data Publication  Species distribution maps generation; Production of indicators; Facilities for creating and managing enhanced documents; generation of standard ISO 10139 metadata for geospatial datasets.

Facilities for performing data mining tasks on tabular and computer science data

Feed Forward Neural Network Regressor, Feed Forward Neural Network Trainer, Dbscan, Kmeans, Lof, Xmeans, WEB App Publisher, Quality Analysis, Generic Charts, Stat Val. (click here to see the description of each algorithm)

Examples of usage in existing VREs: The Tabular Data Lab VRE

Published examples:

Candela, Leonardo, et al. "Species distribution modeling in the cloud." Concurrency and Computation: Practice and Experience (2013).

Coro, Gianpaolo, et al. "Parallelizing the execution of native data mining algorithms for computational biology." Concurrency and Computation: Practice and Experience 27.17 (2015): 4630-4644.

Facilities for species occurrence and geospatial datasets processing 

Time Series Analysis, Time Geo Chart, XYExtractor, ZExtraction, Raster Data Publisher, ESRI-GRID Extraction, Maps Comparison. (click here to see the description of each algorithm)

Examples of usage in existing VREs: The Scalable Data Mining VRE

Published examples:

Coro, Gianpaolo, Pasquale Pagano, and Anton Ellenbroek. "Comparing heterogeneous distribution maps for marine species." GIScience & Remote Sensing 51.5 (2014): 593-611.

Coro, Gianpaolo, et al. "Automatic classification of climate change effects on marine species distributions in 2050 using the AquaMaps model." Environmental and ecological statistics 23.1 (2016): 155-180.

Facilities for  supporting decision making and strategic investment analysis and doing better planning in the aquaculture domain

Mpa Intersect V2 (click here to see the algorithm's description)

Examples of usage in existing VREs: Protected Area Impact Maps VRE, Aquaculture Atlas Generation VRE

Facilities for the development of optimized feeding and growth models

Simulfishkpis (click here to see the algorithm's description)

Examples of usage in existing VREs: Performance and Evaluation in Aquaculture VRE

Facilities for the management and supervision of ecosystems

Absence Cells from AquaMaps, HRS, Absence Generation from Obis, Estimate Monthly Fishing Effort, Ecopath with Ecosim, Estimate Fishing Activity, SEADATANET Interpolator, Species Maps from  Points, BiOnym, Whole Steps Vpa Iccat Bft E. (click here to see the description of each algorithm)

Examples of usage in existing VREs: The Biodiversity Lab VRE

Published examples:

Coro, Gianpaolo, et al. "Improving data quality to build a robust distribution model for Architeuthis dux." Ecological Modelling 305 (2015): 29-39.

Coro, Gianpaolo, Luigi Fortunati, and Pasquale Pagano. "Deriving fishing monthly effort and caught species from vessel trajectories." OCEANS-Bergen, 2013 MTS/IEEE. IEEE, 2013.
Performance evaluation in aquaculture Techno economic investment analysis and what if analysis - Click here for more information.
Relational Database Relational Database with transactional replication.
RStudio RStudio makes R easier to use. It includes a code editor, debugging & visualization tools.
SmartGears Framework SmartGears framework is to make your Tomcat based application runnable on the infrastructure. It manages on behalf of the application authentication, authorization, accounting, monitoring, and alerting. 
Social Framework All applications running on the infrastructure are make accessible through a portal. It includes facilities for the management of users, for communicating with users via posts and notifications, for managing access policies, etc. 
Spatial Data Infrastructure

The Spatial Data Infrastructure includes:

  • Geoserver cluster to manage vector data accessible via OGC WMS and WFS protocols;
  • Geonetwork to manage spatial spatially referenced metadata accessible via OGC CSW protocol;
  • Thedds Data Service cluster to manage NetCDF, OpenDAP, and HDF5 datasets accessible via OPeNDAP protocol.
Storage Infrastructure The Storage infrastructure supports storage of files organized in directories. Policies can be associated with directories by selecting private to a single user, restricted access to specified users, shared with all users of the VRE.