1. PIDs in EUDAT Webinar, 15 Februari 2013
Mark van de Sanden
EUDAT WP leader
SARA, The Netherlands

2. Collaborative Data Infrastructure -A framework for the future? -
Data Curation
Trust
User functionalities, data capture & transfer, virtual research environments
Data
Generators
Users
Data discovery & navigation, workflow generation, annotation, interpretability
Community Support Services
Persistent storage, identification, authenticity, workflow execution, mining
Common Data Services

4. Consortium

5. Five research communities on Board
EPOS: European Plate Observatory System
CLARIN: Common Language Resources and Technology Infrastructure
ENES: Service for Climate Modelling in Europe
LifeWatch: Biodoversity Data and Observatories
VPH: The Virtual Physiological Human
All share common challenges:
Reference models and architectures
Persistent data identifiers
Metadata management
Distributed data sources
Data interoperability
Project partners represent the data scientists in these consortia. EPOS – data and observatories for earthquakes, volcanoes, tectonics – based on sensor data. CLARIN – making language resources and technology usable ENES – simulations of the climate system using HPC Lifewatch – biodiversity research VPH – biomedical modelling and simulation of the human body

6. Communities ↔ Data Centers
Requirements, service cases
Technology appraisal & matching
Service provision

7. First EUDAT Services Metadata Catalogue AAI Data Staging
Aggregated EUDAT metadata domain.
Data inventory
Network of trust among authentication and authorization actors
Data Staging
Safe Replication
Simple Store
Dynamic replication to HPC workspace for processing
Data curation and access optimization
Researcher data store (simple upload, share and access)

8. First EUDAT Services Data Staging Safe Replication Simple Store AAI
Metadata Catalogue
Dynamic replication to HPC workspace for processing
Data curation and access optimization
Researcher data store (simple upload, share and access)
Aggregated EUDAT metadata domain.
Data inventory
Network of trust among authentication and authorization actors
Metadata
Data
PID

9. Scientific Data Pyramid

10. Long tail of data
These type of services targets small research groups, homeless and citizen scientists
Register data that it can be referenced

11. domain of globally referable data
Data Life Cycle
Data Stage-Out
EUDAT
acquisition
generation
description
data
enrichment
processing
reduction
analysis
domain of globally referable data
temporary
data
referable data
publication
global
registration
citable
registration
Safe Replication
Data Stage-In
preservation
EPIC PID

12. Use Case: CLARIN – Safe Replication
EPIC PID registry

13. EPIC Consortium Make data reference able and findable
Provide a sustainable service for storing and maintaining large volumes of PIDs
Consists of 4 partners: GWDG, DKRZ, CSC and SARA
Service based on the Handle service with an EPIC extension for easy management
Handle service provides replication of PIDs and global search and across PID domain (Handle, DataCite and EPIC)

14. EPIC Service EPIC stores more then 5.5M DO
Find hdl:11100/ e e41f13eb41b2
EPIC stores more then 5.5M DO
EPOS communities registered >500k DO in the last few months
Data User
Data Manager
Manage 11100/xxx-……..-xxxx

15. Questions