In this presentation, we describe a pilot project that provides Research Graph records to external web services using JSON-LD. The Research Graph database contains a largescale graph that links research datasets (i.e., data used to support research) to funding records (i.e. grants), publications and researcher records such as ORCID profiles. This database was derived from the work of the Research Data Alliance Working Group on Data Description Registry Interoperability (DDRI), and curated using the Research Data Switchboard open source software. By being available in Linked Data format, the Research Graph database is more accessible to third-party web services over the Internet, which thus opens the opportunity to connect to the rest of the world in the semantic format. The primary purpose of this pilot project is to evaluate the feasibility of converting registry objects in Research Graph to JSON-LD by accessing widely used vocabularies published at Schema.org. In this paper, we provide examples of publications, datasets and grants from international research institutions such as CERN INSPIREHEP, National Computational Infrastructure (NCI) in Australia, and Australian Research Council (ARC). Furthermore, we show how these Research Graph records are made semantically available as Linked Data through using Schema.org. The mapping between Research Graph schema and Schema.org is available on GitHub repository. We also discuss the potential need for an extension to Schema.org vocabulary for scholarly communication.

1. Research Graph in JSON-LD using Schema.org
Jingbo Wang, Amir Aryani
Lesley Wyborn, Ben Evans
4th BigScholar Workshop
2017, Perth, Australia

2. nci.org.au© National Computational
Infrastructure 2017
Outline
• Background of Research Graph
• Why JSON-LD and Schema.org?
• Examples
• Potential extension to Schema.org

3. nci.org.au© National Computational
Infrastructure 2017
Each individual catalogue record describes a linear relationship among
entities:
Current research record status
Researcher A
use
Data 1
Supported
by
Grant a Paper I, II
Generate
Researcher B Data 1
Supported
by
Grant b Paper II, III
use Generate
Researcher B Data 2
Supported
by
Grant b Paper IV
use Generate

4. nci.org.au© National Computational
Infrastructure 2017
Relational database is converted and presented in graph database:
Graph database structure
Researcher A
use
Supported
by
Grant a Paper I
Generate
Researcher B
Data 1
Supported
by
Grant b Paper IIIuse
Generate
Data 2
Supported
by
Paper IV
use Generate
Paper IIGenerate

5. nci.org.au© National Computational
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Dataset A, paper I and II are
connected to paper III and
dataset B through a researcher.
Research Graph database overview - Connections

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Infrastructure 2017
Research Graph
● What related datasets has been published by an author?
● What are the related publications to a dataset?
● What is the research portfolio of the authors related to a
publication?
● What research projects are related to a dataset?
Question: What other researchers or research
activities are connected to my research?”

7. nci.org.au© National Computational
Infrastructure 2017
Data Description Registry Interoperability (DDRI) WG
Goal: Enabling Cross-platform Discovery between
research data infrastructures
https://www.rd-alliance.org/groups/data-description-registry-interoperability.html

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Infrastructure 2017
Building Research Graph using Switchboard

9. nci.org.au© National Computational
Infrastructure 2017
Reasoning
1. Research Graph is a tool to joining the dots (researcher,
publication, dataset, grant)
2. The database info can be exported as XML
3. Linked Data advantages , such as semantic web enabled,
increase discoverability etc.
4. JSON format is flexible, commonly used, JSON-LD is easy to
build on top of JSON
5. Use controlled vocabulary to enhance the interoperability of
Research Graph
6. Schema.org is adopted
7. Limitation were addressed

10. nci.org.au© National Computational
Infrastructure 2017
Research Graph model
Four node types:
1.Researcher
2.Dataset
3.Publication
4.Grant

11. nci.org.au© National Computational
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Node examples in JSON

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Vocabulary mapping using Schema.org
Source: https://github.com/researchgraph/Schema/tree/master/json-ld

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Infrastructure 2017
{"@context": {
"@vocab":"http://schema.org/",
"source":"http://schema.org/publisher",
"doi": {"@id":"http://schema.org/sameAs",
"@type": "@id" },
},
“source": "National Computational Infrastructure",
"doi": "http://dx.doi.org/10.5072/29/5874605e6b57f",
}
Mapping example in JSON-LD
Codes can be tested at http://json-ld.org/playground/

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A dataset record in
JSON-LD - part I

15. nci.org.au© National Computational
Infrastructure 2017
A dataset record in JSON-LD - part II

16. nci.org.au© National Computational
Infrastructure 2017
Schema.org extension recommendation
We have managed to successfully map
• Publication --> Schema.org/ScholarlyArticle
• Researcher --> Schema.org/Person
• Dataset --> Schema.org/Dataset
However, the closest that we find to grant is Schema.org/Action.
This is not an exact match, and it is ambiguous. Therefore we
suggest adding a new type to Schema.org for the Research Grants
or Research Projects.
The following properties are hard to find a good match:
ORCID, Scopus_ID, eScopus_ID, Grant_ID

17. nci.org.au© National Computational
Infrastructure 2017
Summary
• Research Graph create a distributed graph that links research
information across research institutions using the open source
software developed by DDRI WG in Research Data Alliance.
• We provide Linked Data format to increase its interoperability
• Schema.org has been very helpful to build JSON-LD format

18. nci.org.au© National Computational
Infrastructure 2017
Project started in 2015 and now we collaborators in Australia,
Europe and Asia http://www.researchgraph.org/collaborators/
Please contact:
Amir Aryani Amir.Aryani@ands.org.au
Jingbo Wang Jingbo.Wang@anu.edu.au
Thank you!