Virtual Research Environments: e-Infrastructures 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@isti.cnr.it www.d4science.org

2. DELOS: Grand 10-Year Vision #1 Digital Libraries should enableany citizen to access allhuman knowledge anytimeandanywhere, 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 communicationconduitsfor the future, a common vehicle by which everyone willaccess,discuss, evaluate, and enhanceinformationof 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 user’s views * DELOS Reference Model for Digital Libraries

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

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 madeavailable for other usages inside and outside the VRE

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

8. On-demand information objects • afixed 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, dynamicallydeployed, 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. 3D processing simulation Featureextraction Speech recognition gCube empowered e-Infrastructure E-Infrastructure Consumers Providers VRE-A VRE-A Middleware Digital Library services VRE generator DESIGNER VRE-B ADMIN VRE-B

12. Managing Data Source Heterogeneity Mapping Rules MR

13. Bridging Data Sources Data Sources are interfaced through .. The bridges are managed by .. .. the e-infrastructure Hosted on the e-infrastructure

14. Managing Data Import DS DS DS import gCube e-Infrastructure VRE 2 VRE 1 VRE 3 VRE 5 VRE 4 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. Courtesy by Marc Taconet FAO Integrated fisheries Capture Information System -ICIS VRE

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

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

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

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

21. reallocation rules peer reviewediting Expert ICIS VRE to respond to institutional needs end user GLOBAL LEVEL Aquamap fishbase DB GIS areas - sp Reference system Catch stats FAO Satellite oceanographic WFC Mapping rules Species occurrence NOAA OBIS Catch stats Reference system RFBs REGIONALLEVEL 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. Courtesy by Luigi Fusco ESA chlorophyll and vegetationdistributionVREs

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 data sets available ~4700 global data set available Key community portal www.medspiration.org/ products Reference doc Metadata, services www.fao.org/geonetwork www.gmes.info www.eoportal.org daily + TB data sets + services 850 access in last week ES Thesaurus ~30000 objects environmental data / reports idn.ceos.org eogrid.esrin.esa.int www.eea.eu.int 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

29. http://www.gcube-system.org/ http://www.d4science.org/

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