Virtual Research Environments: e-Infrastructures beyond Digital Libraries Pasquale Pagano CNR-ISTI RCDL08 Conference Information Model Mapping and Resource Integration Friday 10 October, Dubna, Russia

2 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 #1 #2 * 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 user’s views * DELOS Reference Model for Digital Libraries

5 The evolution Virtual Research Environments many virtual organizations Repository + Catalogue + Search service few large institutions 1996 consumer Digital Library few small institutions 2001 consumer 2006 consumer and resource provider Digital Library Management System many small institutions 2003 consumer and data provider

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 Highly dynamic, created and dismissed on-demand Based on specialised tools which support the generation of new knowledge M26 0 0,2 0,4 0,6 0,8 1 1,2 Informaion Service Broker & Matchmaker Keeper DVOS VDL Generator Content Management Wrapper & Monitor Content Security Metadata Broker Annotation Metadata Management Data Fusion CSDS Personalization Index Service Search Service Feature Extraction Service Process Design & Verification Process Execution & Reliability Process Optimization Arte Portal ImpECt Portal PrototypeAvailableBuild Operating on new information objects

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 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 simulation Speech recognition Feature extraction 3D processing ConsumersProviders VRE-A VRE-B gCube empowered e-Infrastructure Middleware Digital Library services DESIGNER ADMIN VRE generator E-Infrastructure

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 gCube e-Infrastructure Managing Data Import DS import MR VRE 2VRE 3VRE 4VRE 1 VRE 5 DS

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 REGIONAL LEVEL FAO RFBs Catch stats GLOBAL LEVEL Catch stats Reference system Reference system GIS areas - sp Mapping rules harmonisation of hererogeneous sources standard reporting format ICIS VRE to respond to institutional needs Fishery Fishery agencies Biodiversity Data standardisation: harmonisation of heterogeneous sourcesData queriesData import end user query tools

18 ICIS VRE to respond to institutional needs Data processing: reallocation rules

19 REGIONAL LEVEL FAO RFBs Catch stats GLOBAL LEVEL Catch stats end user Reference system Reference system GIS areas - sp Mapping rules harmonisation of hererogeneous sources reallocation rules ICIS VRE to respond to institutional needs Fishery Biodiversity Products dissemination: maps - tables

20 REGIONAL LEVEL FAO RFBs Catch stats GLOBAL LEVEL Catch stats end user Reference system Reference system GIS areas - sp Mapping rules harmonisation of hererogeneous sources reallocation rules ICIS VRE to respond to institutional needs Fishery Biodiversity

21 WFC REGIONAL LEVEL Catch stats GLOBAL LEVEL Catch stats Reference system Reference system fishbase DB NOAA OBIS Satellite oceanographic Species occurrence Aquamap GIS areas - sp peer review editing Expert Mapping rules end user ICIS VRE to respond to institutional needs Fishery Biodiversity reallocation rules FAO RFBs

22  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

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 daily + TB data sets + services eogrid.esrin.esa.int environmental data / reports ES Thesaurus ~30000 objects idn.ceos.org ~4700 global data set available 850 access in last week Key community portal Reference doc Metadata, services daily data sets available products 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  > 60 WSs, >50 independent libraries, and >30 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

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30 gCube today  gCube Software Documentation  infrastructures.eu/ infrastructures.eu/  gCube Core Software Documentation   gCube System web site 