Presentation from a joint webinar FREYA and OpenAIRE: New developments in the field of Persistent Identifiers by Dr. Amir Aryani, Director, Research Graph Foundation

1. Role of PIDs in connecting scholarly works
Dr. Amir Aryani
Director, Research Graph Foundation
https://orcid.org/0000-0002-4259-9774
1

2. Agenda
• Background: DDRI / Research Graph
• Augmenting the graph of scholarly works using PID
• PID Graph
2

3. Challenge of finding related datasets
Similar datasets
in other
repositories?
?
3
Background

4. 4
Initiated from the
Data Description Registry Interoperability Working Group
Goal: enabling cross-platform discovery between “Research Data Infrastructures”
Research Data Alliance
https://www.rd-alliance.org/groups/data-description-registry-interoperability.html 4
Background

5. Background
https://researchdata.ands.org.au/idmm-immunome-
database-for-marsupials-and-monotremes/11139

6. Background
https://researchdata.ands.org.au/idmm-immunome-
database-for-marsupials-and-monotremes/11139

7. Background
Show 105 more
publications

8. Background
http://dx.doi.org/10.1371/journal.pone.0079092
One of the 105 articles …

9. doi:10.5061/dryad.4qq0v
Authors: Wong ESW, Nichol
S, Warren WC, Belov K
Dryad Dataset
http://datadryad.org/resource/doi:10.5061/dryad.4qq0v
Background

10. Background
Dataset
Researcher Publication
Dataset
We found another dataset from the same author…

11. ResearchDataSwitchboard
Background

12. 12
D1 − [: citedBy] → P1 ← [: citedBy] − D2
D1 − [: fundedBy] → G1 ← [: fundedBy] − D2
D1 − [: createdBy] → R1 ← [: createdBy] − D2

13. 13
In a limited graph cluster (~4 million
nodes)
• 70.6% publica>ons have DOI
• 46% datasets have DOI
Role of DOI
https://www.nature.com/articles/sdata201899

14. Augment API
14

15. 15

16. Peter Oke
1
2
3
1. NCI Original Record: Dr. Peter
Oke has multiple datasets in
NCI Geonetwork Catalogue
2. Augmented Graph: The
Augment API linked this record
to the related ORCID profile.
3. External Records: All the
publication from ORCID profile
has been linked to the new
record in the NCI graph.
16

17. Finding connection to a dataset
Dataset Researcher
RelatedTo
17

18. Finding connection to a dataset
Dataset Researcher
ORCID: 0000-1111-0000-1111
Researcher
knownAs
Publication
RelatedTo
P
P
18

19. Finding connection to a dataset
D R
knownAs
R P
P
P
Dataset Publication
19

20. 1. ETL: Transform Geonetwork repository to a Neo4j
Graph DB
2. Augment: Use Research Graph Service (in
amazon cloud) to augment the NCI graph with
ORCID and other repositories.
3. Visualisation: Creating optimised GraphML from
the Augmented Neo4j
20

21. NCI Original Graph NCI Augmented Graph

22. Lessons Learned
22

23. 23
L1: Power of Trusted Persistent Identifiers
• Persistent identifiers (PIDs) saves money
• Disambiguation without PIDs is expensive and inefficient
• Trusted PIDs creates trusted connections
• Without PIDs, we need to rely on AI to map relationships
between scholarly works. This is usually require using
probabilistic models with accuracy < 100%.

24. 24
Sailing the Data Ocean
Working with scholarly
communication is traversing
Dynamic Big Data
We need
• fast,
• trusted, and
• sustainable services.
L2:

25. 25
L3:
We need to connect instead of collect

26. PID Graph
26

27. PID Graph
The PID Graph is a network of connections between PIDs available in the form of a set of
federated RESTful JSON APIs.
Applications
1.Disciplinary applications
Integrate mature PID Graph functionality in disciplinary contexts, i.e. trusted author-article-data linking and software identification
and citation workflows.
2.European Open Science Cloud applications
Connect European Open Science Cloud demonstrators to the PID Graph: Build the required knowledge-based resources that
enable European Open Science Cloud stakeholders to exploit and contribute to the PID Graph.
3.Graph visualisation
Exploiting the PID Graph API to create an informative graph visualisation and exploration tool. The tool will show the research
connections for a research enterprise such as the citation network for a data repository, institution, or funder.
27

28. Examples
• Track the citation of a dataset across all versions
• D{1.1, 1.2, 1.3} − [: citedBy] → {P1 , P2 , P3 , P1}
• Impact of funding
• G1 ← [: fundedBy] − {D1 , P1 , P2 , P3 , … }
• More effective linking of data to publications
• As a researcher I want (easy ways) to (more effectively) link all data to
publications. As a reader I want to be able to easily find all data related to a
publication.
28

29. 29
User stories (Use cases)
• What API?
• Potential users?
• How complicated to implement
and expensive to operate?

30. What next?
30
Research Data Graph BoF
RDA’s 13th Plenary Meeting (P13),
April 2-4, Philadelphia
Project FREYA
https://www.project-freya.eu
Research Graph
https://www.researchgraph.org
Contact info:
amir.aryani@researchgraph.org