Creating Structured Linked Data to Generate Scholarly Profiles: A Pilot Project using Wikidata and Scholia

Authors : Mairelys Lemus-Rojas, Jere D. Odell


Wikidata, a knowledge base for structured linked data, provides an open platform for curating scholarly communication data. Because all elements in a Wikidata entry are linked to defining elements and metadata, other web systems can harvest and display the data in meaningful ways.

Thus, Wikidata has the capacity to serve as the data source for faculty profiles. Scholia is an example of how third-party tools can leverage the power of Wikidata to provisde faculty profiles and bibliographic, data-driven visualizations.


In this article, we share our methods for contributing to Wikidata and displaying the data with Scholia.

We deployed these methods as part of a pilot project in which we contributed data about a small but unique school on the Indiana University-Purdue University Indianapolis (IUPUI) campus, the IU Lilly Family School of Philanthropy.


Following the completion of our pilot project, we aim to find additional methods for contributing large data collections to Wikidata. Specifically, we seek to contribute scholarly communication data that the library already maintains in other systems.

We are also facilitating Wikidata edit-a-thons to increase the library’s familiarity with the knowledge base and our capacity to contribute to the site.

URL : Creating Structured Linked Data to Generate Scholarly Profiles: A Pilot Project using Wikidata and Scholia


Wikidata as a semantic framework for the Gene Wiki initiative

Open biological data are distributed over many resources making them challenging to integrate, to update and to disseminate quickly. Wikidata is a growing, open community database which can serve this purpose and also provides tight integration with Wikipedia.

In order to improve the state of biological data, facilitate data management and dissemination, we imported all human and mouse genes, and all human and mouse proteins into Wikidata.

In total, 59 721 human genes and 73 355 mouse genes have been imported from NCBI and 27 306 human proteins and 16 728 mouse proteins have been imported from the Swissprot subset of UniProt. As Wikidata is open and can be edited by anybody, our corpus of imported data serves as the starting point for integration of further data by scientists, the Wikidata community and citizen scientists alike.

The first use case for these data is to populate Wikipedia Gene Wiki infoboxes directly from Wikidata with the data integrated above. This enables immediate updates of the Gene Wiki infoboxes as soon as the data in Wikidata are modified.

Although Gene Wiki pages are currently only on the English language version of Wikipedia, the multilingual nature of Wikidata allows for usage of the data we imported in all 280 different language Wikipedias.

Apart from the Gene Wiki infobox use case, a SPARQL endpoint and exporting functionality to several standard formats (e.g. JSON, XML) enable use of the data by scientists.

In summary, we created a fully open and extensible data resource for human and mouse molecular biology and biochemistry data. This resource enriches all the Wikipedias with structured information and serves as a new linking hub for the biological semantic web.

URL : Wikidata as a semantic framework for the Gene Wiki initiative

DOI : 10.1093/database/baw015

Enabling Open Science: Wikidata for Research

Wiki4R will create an innovative virtual research environment (VRE) for Open Science at scale, engaging both professional researchers and citizen data scientists in new and potentially transformative forms of collaboration. It is based on the realizations that (1) the structured parts of the Web itself can be regarded as a VRE, (2) such environments depend on communities, (3) closed environments are limited in their capacity to nurture thriving communities.

Wiki4R will therefore integrate Wikidata, the multilingual semantic backbone behind Wikipedia, into existing research processes to enable transdisciplinary research and reduce fragmentation of research in and outside Europe. By establishing a central shared information node, research data can be linked and annotated into knowledge. Despite occasional uses of Wikipedia or Wikidata in research, significant barriers to broader adoption in the sciences or digital humanities exist, including lack of integration into existing research processes and inadequate handling of provenances.

The proposed actions include providing best practices and tools for semantic mapping, adoption of citation and author identifiers, interoperability layers for integration with existing research environments, and the development of policies for information quality and interchange. The effectiveness of the actions will be tested in pilot use cases.

Unforeseen barriers will be investigated and documented. We will promote the adoption of Wiki4R by making it easy to use and integrate, demonstrate the applicability in selected research domains, and provide diverse training opportunities.

Wiki4R leverages the expertise gained in Europe through the Wikidata and DBpedia projects to further strengthen the established virtual community of 14000 people. As a result of increased interaction between professional science and citizens, it will provide an improved basis for Responsible Research and Innovation and Open Science in the European Research Area.

URL : Enabling Open Science: Wikidata for Research

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Wikidata through the Eyes of DBpedia

“DBpedia is one of the first and most prominent nodes of the Linked Open Data cloud. It provides structured data for more than 100 Wikipedia language editions as well as Wikimedia Commons, has a mature ontology and a stable and thorough Linked Data publishing lifecycle. Wikidata, on the other hand, has recently emerged as a user curated source for structured information which is included in Wikipedia.

In this paper, we present how Wikidata is incorporated in the DBpedia ecosystem. Enriching DBpedia with structured information from Wikidata provides added value for a number of usage scenarios. We outline those scenarios and describe the structure and conversion process of the DBpediaWikidata dataset.”

URL : Wikidata through the Eyes of DBpedia

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