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Virtual Research Environments: eInfrastructures beyond Digital Libraries

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collections of raw data, content, and metadata ... DESIGNER. ADMIN. VRE generator. E-Infrastructure. Managing Data Source Heterogeneity. Mapping Rules ... – PowerPoint PPT presentation

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Title: Virtual Research Environments: eInfrastructures beyond Digital Libraries


1
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 Pasquale.pagano_at_isti.cnr.
it
www.d4science.org
2
DELOS Grand 10-Year Vision
1
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
2
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
DELOS Network of Excellence on Digital
Libraries
3
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
4
The users views
DELOS Reference Model for Digital Libraries
5
The evolution
Virtual Research Environments
Digital Library Management System
Digital Library
Repository Catalogue Search service
many virtual organizations
few large institutions
few small institutions
many small institutions
6
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

7
Virtual Research Environments characteristics
8
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

9
D4Science vision
  • D4Science vision
  • calls 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 is
  • a 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)

10
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

11
gCube empowered e-Infrastructure
E-Infrastructure
Consumers
Providers
VRE-A
Middleware

Digital Library services

VRE generator
VRE-B
12
Managing Data Source Heterogeneity
Mapping Rules MR
13
Bridging Data Sources
Hosted on the e-infrastructure
Data Sources are interfaced through .. The
bridges are managed by .. .. the e-infrastructure
14
Managing Data Import
DS
DS
DS
import
gCube e-Infrastructure
VRE 2
VRE 3
VRE 4
VRE 1
VRE 5
MR
MR
MR
15
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
16
Integrated fisheries Capture Information System
- ICIS VRE
  • Courtesy by
  • Marc Taconet
  • FAO

17
ICIS VRE to respond to institutional needs
Data standardisation harmonisation of
heterogeneous sources
Data queries
Data import
GLOBAL LEVEL
GIS areas - sp
Catch stats
Reference system
FAO
Catch stats
Reference system
RFBs
REGIONAL LEVEL
Biodiversity
Fishery
Fishery agencies
Fishery agencies
Fishery agencies
18
ICIS VRE to respond to institutional needs
Data processing reallocation rules
19
ICIS VRE to respond to institutional needs
Products dissemination maps - tables
end user
GLOBAL LEVEL
reallocation rules
GIS areas - sp
Catch stats
Reference system
FAO
Catch stats
Reference system
RFBs
REGIONAL LEVEL
Biodiversity
Fishery
20
ICIS VRE to respond to institutional needs
end user
GLOBAL LEVEL
reallocation rules
GIS areas - sp
Catch stats
Reference system
FAO
Catch stats
Reference system
RFBs
REGIONAL LEVEL
Biodiversity
Fishery
21
ICIS VRE to respond to institutional needs
end user
GLOBAL LEVEL
Aquamap
fishbase DB
GIS areas - sp
Catch stats
Reference system
FAO
Satellite oceanographic
WFC
Mapping rules
Species occurrence
NOAA
OBIS
Catch stats
Reference system
RFBs
REGIONAL LEVEL
Biodiversity
Fishery
22
ICIS a response to institutional needs the
Vision
  • 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

23
chlorophyll and vegetation distribution VREs
  • Courtesy by
  • Luigi Fusco
  • ESA

24
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.

25
VREs data sources
26
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.

27
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
  • gt 60 WSs, gt50 independent libraries, and gt30
    portlets
  • most components widely tested and certified
  • Public and Stable Release (November 2008)?

28
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

29
  • http//www.gcube-system.org/

http//www.d4science.org/
30
gCube today
  • gCube Software Documentation
  • https//technical.wiki.d4science.research-infrastr
    uctures.eu/
  • gCube Core Software Documentation 
  • https//wiki.gcore.research-infrastructures.eu/
  • gCube System web site
  • http//www.gcube-system.org
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