virtual research environments: e-infrastructures beyond digital libraries
DESCRIPTION
RCDL08 Conference Information Model Mapping and Resource Integration Friday 10 October, Dubna, Russia. Virtual Research Environments: e-Infrastructures beyond Digital Libraries. Pasquale Pagano CNR-ISTI [email protected]. www.d4science.org. DELOS: Grand 10-Year Vision. #1. - PowerPoint PPT PresentationTRANSCRIPT
Virtual Research Environments: e-Infrastructures beyond Digital Libraries
Pasquale [email protected]
RCDL08 Conference
Information Model Mapping and Resource Integration
Friday 10 October, Dubna, Russia
www.d4science.org
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www.d4science.eu
Digital Libraries should enable any citizen to access all human knowledge anytime and anywhere, in a friendly, multi-modal, efficient, and effective way, by overcoming barriers of distance, language, and culture and by using multiple Internet-connected devices
DELOS: Grand 10-Year Vision
The potential exists for digital libraries to become the universal knowledge repositories and communication conduits for the future, a common vehicle by which everyone will access, discuss, evaluate, and enhance information of all forms
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* DELOS: Network of Excellence on Digital Libraries
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DELOS: Digital Library
A (potentially virtual) organization that comprehensively collects, manages, and preserves for the long term rich digital content and offers to its user communities specialized functionality on that content, of measurable quality, and according to prescribed policies
* DELOS Reference Model for Digital Libraries
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The user’s views
* DELOS Reference Model for Digital Libraries
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The evolution
Virtual Research Environments
many virtual organizations
Repository +Catalogue +Search service
few large institutions
1996consumer
Digital Library
few small institutions
2001 consumer
2006 consumer and resource provider
Digital Library Management System
many small institutions
2003 consumer and data provider
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Virtual Research Environments (VRE): beyond DL
• Distributed frameworks for carrying out cooperative activities like “in silico experiments”, data analysis and processing, production of new knowledge using specialized tools
• Largely based on retrieval and access of always updated knowledge from diverse heterogeneous content sources
• Produce knowledge that is preserved and made available for other usages inside and outside the VRE
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Virtual Research Environments: characteristics
Highly dynamic, created and dismissed on-demand
Based on specialised tools which support the generation of new knowledge
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Con
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Bro
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An
nota
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Meta
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Man
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Data
Fu
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CS
DS
Pers
on
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Ind
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Searc
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Featu
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xtr
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Serv
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Pro
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Veri
ficati
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Pro
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xecu
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& R
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Pro
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Art
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Imp
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PrototypeAvailableBuild
Operating on new information objects
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On-demand information objects
• a fixed text
• a pollution map
• a table summarizing data
from millions of observed satellite measures
• a graph reporting an analytical trend of certain information extracted from a great amount of observed data
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D4Science vision
D4Science visioncalls for the realization of scientific e-Infrastructures that will remove technical concerns from the minds of scientists, hide all related complexities from their perception, and enable users to focus on their science and collaborate on common research challenges
gCube isa framework to manage distributed e-infrastructures where it is possible to define, host, and maintain dynamic virtual environments capable to satisfy the collaboration needs of distributed Virtual Organizations (VOs)
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gCube Resources
VRE applications are designed, dynamically deployed, and operated as a set of cooperating resources:
computing, storage middleware VRE services
content and storage management, discovery and access, … applications
mostly provided by the VOs collections of raw data, content, and metadata
enriched with schemas, mapping rules, transformation programs, relationships, …
processes defined to manage such resources
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ConsumersConsumers ProvidersProvidersVRE-A
VRE-B
gCube empowered e-Infrastructure
Mid
dle
ware
M
idd
lew
are
Dig
ital Lib
rary
serv
ices
Dig
ital Lib
rary
serv
ices
DESIGNER
ADMIN VR
E g
en
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tor
VR
E g
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tor
E-InfrastructureE-Infrastructure
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Managing Data Source Heterogeneity
Mapping Rules MR
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Bridging Data Sources
Hosted on the e-infrastructure
Data Sources are interfaced through ..The bridges are managed by ..
.. the e-infrastructure
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gCube e-Infrastructure
Managing Data Import
DS import
MR MR MR
VRE 2 VRE 3 VRE 4VRE 1 VRE 5
DS DS
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Offering a Collaboration Environment
gCube VREs provide access to a workspace where users can
share: Private data Data process results Annotation Process definition Derived data
collaborate to define new processes, tune applications and processes compare execution results
opens unique opportunities for virtual collaborations
Contain both objects owned by the workspace owner and objects the workspace owner has been allowed to see, e.g. group objects;
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INTEGRATED FISHERIES CAPTURE INFORMATION SYSTEM -
ICIS VRE
Courtesy by
Marc Taconet FAO
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REGIONAL LEVEL
FAO
RFBsCatch stats
GLOBAL LEVEL
Catch stats
Reference system
Reference system
GISareas - sp
Mapping rules
harmonisation of hererogeneous sources
standard reporting
format
ICIS VRE to respond to institutional needs
Fishery Biodiversity
Data standardisation: harmonisation of heterogeneous sourcesData queriesData importend user
query tools
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ICIS VRE to respond to institutional needs
Data processing: reallocation rules
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REGIONAL LEVEL
FAO
RFBsCatch stats
GLOBAL LEVEL
Catch stats
end user
Reference system
Reference system
GISareas - sp
reallocation rules
ICIS VRE to respond to institutional needs
Fishery Biodiversity
Products dissemination: maps - tables
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REGIONAL LEVEL
FAO
RFBsCatch stats
GLOBAL LEVEL
Catch stats
end user
Reference system
Reference system
GISareas - sp
reallocation rules
ICIS VRE to respond to institutional needs
Fishery Biodiversity
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WFC
REGIONAL LEVEL
Catch stats
GLOBAL LEVEL
Catch stats
Reference system
Reference system
fishbase DB
NOAA
OBIS
Satelliteoceanographic
Species occurrence
Aquamap
GISareas - sp
peer reviewediting
Expert
Mapping rules
end user
ICIS VRE to respond to institutional needs
Fishery Biodiversity
reallocation rules
FAO
RFBs
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Through a VRE it is possible to facilitate ... the dissemination through tables or maps of credible estimates of
catch data, according to users’ choice of spatial resolution, based on best available statistic sources and with transparent algorithms.
the comparison of catch statistics among various sources.
By exploiting ... semi-automated import of distributed data sources harmonization of heterogeneous sources implementation of re-allocation rules intensive data processing support for query, output and annotation. easy updating and feedback processes
ICIS – a response to institutional needs
the Vision
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CHLOROPHYLL AND VEGETATION DISTRIBUTION
VRES
Courtesy by
Luigi FuscoESA
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VREs: to enhance current procedures
• VREs integrated environment put at disposal a functionality set which is not today available in Earth Science to support and perform research activities: examples are
the ability to process information on-demand ingesting the results,
to set-up further VREs opening to colleague (and project partners) users,
to perform customized collection of information, to store user actions and exploit them for further use, to aggregate relevant information into ad-hoc information
sources and keeping them updated.
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daily + TB datasets + services
eogrid.esrin.esa.int
environmental data / reports
www.eea.eu.int
ES Thesaurus ~30000 objects
idn.ceos.org
~4700 global data set available
850 access in last week
www.fao.org/geonetwork Key community portal
www.gmes.info
Reference docMetadata, services
www.eoportal.org
daily data sets available
www.medspiration.org/
products
VREs data sources
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VREs: to enhance current procedures
• Currently these steps are carried on manually, on different technologies and systems delaying the delivery of research results.
• The planned VREs offer a dynamic set up and utilization of Virtual DL which are created for the specific scope defined by the users.
• The focus, once again, is not in the processing but in the dynamic allocation of resources.
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gCube today
• gCube is compliant with consolidated and emerging standards.
• gCube offers an open family of frameworks that can be easily customised
• gCube is a working horizontal solution composed by more than 200 software components
> 60 WSs, >50 independent libraries, and >30 portlets
most components widely tested and certified Public and Stable Release (November 2008)
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VRE Advantages
• gCube technology creates new opportunities to change the VRE development model used by distributed and dynamic organisations and communities
• Using gCube empowered infrastructures, the organisations and communities are able to setup their own environment:
When and for the time they need it
Accessing to and handling of distributed multi-focused data and services
Profiting from a shared storage and computational set of resources
Sharing data and services in a collaborative and efficient way
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http://www.gcube-system.org/ http://www.d4science.org/
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gCube today
gCube Software Documentationhttps://technical.wiki.d4science.research-infrastructures.eu/
gCube Core Software Documentation https://wiki.gcore.research-infrastructures.eu/
gCube System web sitehttp://www.gcube-system.org