Difference between revisions of "Catalogue:Services"

Revision as of 15:00, 10 July 2013

iMarine inherited its software stack (gCube) from 2 previous EU projects, D4ScienceAn e-Infrastructure operated by the D4Science.org initiative. and D4ScienceAn e-Infrastructure operated by the D4Science.org initiative. II. The software has been further extended during the iMarine project in order to enhance the foundation and build Marine Applications on top of it concentrating the effort in 3 main functionalities areas :

• Core Facilities : dedicated to provide its users with a range of services for the operation and management of the whole infrastructure. They are detailed in this section
• Data Management Facilities  : dedicated to provide its users with a rich array of services for the management of data in the context of the whole infrastructure.
• Data Consumption Facilities  : dedicated to provide its users with a rich array of services for the exploitation of data in the context of the whole infrastructure

Data Management Facilities

Data Consumption Facilities

The Data Consumption facilities can be further categorized in 5 different areas

Data Retrieval

gCube provides Information Retrieval facilities over large heterogeneous environments. Sources of information that use different technologies, data representation and semantics can be integrated and exploited by gCube's Data Retrieval framework. The architecture and mechanisms provided by the framework ensure flexibility, scalability, high performance and availability. The gCube Data Retrieval Framework aims at hiding the complexity of the underlying environment by:

• providing a declarative approach for querying the hosted information
• scaling to the number of hosted information sources
• Integrating dynamically external sources of information

Data Manipulation

gCube provides Data Manipulation Facilities responsible for transforming content and metadata among different formats and specifications. The architecture and mechanisms provided by the framework satisfy the requirements for arbitrary transformation or homogenization of content and metadata. Its features are useful for:

• information retrieval
• information presentation
• processing and exporting

Transformations can be performed offline and on demand on a single object or on a group of objects.

Data Mining

Data Mining facilities include a set of features, services and methods for performing data processing and mining on biological information sets. These features face several aspects of biological data processing ranging from ecological modeling to niche modeling experiments. Algorithms are executed in parallel and possibly distributed fashion using working nodes. Furthermore, Services performing Data Mining operations are deployed according to a distributed architecture, in order to balance the load of those procedures requiring local resources.

Data Visualization

Data Visualisation facilities include a set of features, software and methods for performing visualisation of data. Data Visualisation is particularly meant for geo-spatial data, which is a kind of information that naturally lends to visualisation. Data are reproduced on interactive maps and can be explored by means of several inspection tools. The adopted paradigm for maps visualisation needs to query a central GeoNetwork instance that indexes several geo-spatial data sources.

! Semantic Data Anaylisys

This task aims to deliver a set of libraries and services to bridge the gap between communities and link distributed data across community boundaries. The introduction of the Semantic Web and the publication of expressive metadata in a shared knowledge framework enable the deployment of services that can intelligently use Web resources