EUDAT

PIDs in EUDAT

Webinar, 15 Februari 2013

Mark van de Sanden

EUDAT WP leader

SARA, The Netherlands

Tru

st

Data

Cu

rati

on

Common Data Services

Users

User functionalities, data capture & transfer, virtual research environments

Persistent storage, identification, authenticity, workflow execution, mining

Data Generators

Community Support Services

Data discovery & navigation, workflow generation, annotation, interpretability

Collaborative Data Infrastructure -A framework for the future? -

3

Consortium

4

• 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

Five research communities on Board

5

Communities ↔ Data Centers

Data Staging Safe Replication Simple Store

AAIMetadata 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

First EUDAT Services

First EUDAT Services

MetadataDataPID

Data Staging Safe Replication Simple Store

AAIMetadata 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

Scientific Data Pyramid

Long tail of data

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

domain of globally referable data

temporarydata

preservation

registration

referabledata

EPIC PID

acquisitiongenerationdescription

data

enrichmentprocessingreductionanalysis

citable

Data Stage-Out

publication

Safe Replication

global registration

Data S

tage

-In

Data Life Cycle

Use Case: CLARIN – Safe Replication

EPIC PID registry

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)

EPIC Service

• EPIC stores more then 5.5M DO• EPOS communities registered >500k DO in the last few months

Find hdl:11100/00335742-6026-11e2-9724-e41f13eb41b2

Data User

Data Manager

Manage 11100/xxx-……..-xxxx

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Questions