An ORCID based synchronization framework for

a national CRIS ecosystemJoão Mendes Moreira, Alcino Cunha, Nuno Macedo

Our problem

• Research outcomes scattered through various services and data formats

• Heavy burden on researchers and managers

• Inconsistent information and impact assessment

2

Our goal

• Input once, reuse often!

• Automatic synchronization between services

3

PTCRIS in context

4

PTCRIS in context

CV

4

PTCRIS in context

CV

OA aggregator

4

PTCRIS in context

CV

OA aggregatorDSpace

4

PTCRIS in context

CV

OA aggregatorDSpace

OJS

4

PTCRIS in context

CV

OA aggregatorDSpace

OJS

4

PTCRIS in context

ORCID

CV

OA aggregatorDSpace

OJS

4

PTCRIS in context

ORCID

CVResearcher

ID

OA aggregatorDSpace

OJS

4

PTCRIS in context

ORCID

CVResearcher

ID

OA aggregatorDSpace

OJS

Scopus

4

PTCRIS in context

ORCID

CVResearcher

ID

OA aggregatorDSpace

OJS

Scopus

4

A non solution

ORCID

CVResearcher

ID

OA aggregator

DSpace

OJSScopus

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A non solution

ORCID

CVResearcher

ID

OA aggregator

DSpace

OJSScopus

5

A non solution

• Many synchronization procedures per service

• Implementation and maintainability nightmare

• No clear flow to achieve global consistency

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Our solution

ORCID

CVResearcher

ID

OA aggregator

DSpace

OJSScopus

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Our solution

ORCID

CVResearcher

ID

OA aggregator

DSpace

OJSScopus

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Our solution

• One synchronization procedure per service

• Easier to implement and maintain

• Clear flow to achieve global consistency

8

Why ORCID?

• High coverage of predefined requirements

• High interoperability with external sources

• High coverage of the national research community

• Sustainable and open source

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Modular synchronization

ORCID

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Modular synchronization

ORCID

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Modular synchronization

• IMPORT: harvest research outputs from ORCID

• EXPORT: feed research outputs to ORCID

ORCID

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Main challenges• Mismatch between data models

• ORCID may contain several versions of the same output

• They are grouped together based on UIDs

• (Fast evolving) API still does not reflect this data model

• Inconsistent, sometimes incorrect, meta-data

• (Still) no clear mechanism to determine the user preferred version

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Design methodology

• Focus on the what before the how

• What is the desired notion of consistency between each service and ORCID?

• How can a synchronization procedure be implemented to enforce such consistency?

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Design methodology• Use formal analysis methods and tools

• To verify desirable properties of all artifacts

• To generate scenarios for validation and testing

• “The first principle is that you must not fool yourself, and you are the easiest person to fool” Richard Feynman

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Scenarios

Article1 doi0 handle0

Paper1 doi1 eid1 handle1

Work1 USERdoi0

Work2 SCOPUS

doi1 eid1

Work3 USER

eid1 handle1

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Scenarios

Article1 doi0 handle0

Work1 USERdoi0

Work2 SCOPUS

doi1 eid1

Work3 USER

eid1 handle1

Paper1 doi1 eid1 handle1

doi0

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Scenarios

Article1 doi0 handle0

Work1 USERdoi0

Work2 SCOPUS

doi1 eid1

Work3 USER

eid1 handle1

Paper1 doi1 eid1 handle1

doi0

Work4 PTCRIS

doi1 eid1 handle1 doi0

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Scenarios

Work1 USERdoi0

Work2 SCOPUS

doi1 eid1

Work3 USER

eid1 handle1

Paper1 doi1 eid1 handle1

doi0

Work4 PTCRIS

doi1 eid1 handle1 doi0

Article1 doi0 handle0

doi1 eid1 handle1

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Prototype

• Demoed at the FCCN community annual meeting in February 2015

• Show compelling and real use cases

• Four PTCRIS services involved: CV, OA aggregator, DSpace, and OJS

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Prototype

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What’s next?• We expect to have certified implementations of this

specification in DeGóis (CV), RCAAP (OA aggregator), SARI (DSpace), and two local CRIS systems by the end of 2015

• Upgrade the specification to ORCID API 2.0

• Provide synchronization as a service?

• Automatic (model-based) testing from scenarios?

• H2020 proposal around this topic?

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