Leveraging Concepts in Open Access Publications

Abstract : This paper addresses the integration of a Named Entity Recognition and Disambiguation (NERD) service within a group of open access (OA) publishing digital platforms and considers its potential impact on both research and scholarly publishing. The software powering this service, called entity-fishing, was initially developed by Inria in the context of the EU FP7 project CENDARI and provides automatic entity recognition and disambiguation using the Wikipedia and Wikidata data sets. The application is distributed with an open-source licence, and it has been deployed as a web service in DARIAH’s infrastructure hosted by the French HumaNum. In the paper, we focus on the specific issues related to its integration on five OA platforms specialized in the publication of scholarly monographs in the social sciences and humanities (SSH), as part of the work carried out within the EU H2020 project HIRMEOS (High Integration of Research Monographs in the European Open Science infrastructure). In the first section, we give a brief overview of the current status and evolution of OA publications, considering specifically the challenges that OA monographs are encountering. In the second part, we show how the HIRMEOS project aims to face these challenges by optimizing five OA digital platforms for the publication of monographs from the SSH and ensuring their interoperability. In sections three and four we give a comprehensive description of the entity-fishing service, focusing on its concrete applications in real use cases together with some further possible ideas on how to exploit the annotations generated. We show that entity-fishing annotations can improve both research and publishing process. In the last chapter, we briefly present further possible application scenarios that could be made available through infrastructural projects.

ARL, Wikimedia, and Linked Open Data: Draft White Paper Open for Comments through November 30 | Association of Research Libraries® | ARL®

“In June 2018, the Association of Research Libraries (ARL) charged a task force to look at Wikidata. The task force emerged from several years of discussion between ARL and the Wikimedia Foundation on where the two communities can effectively collaborate. The focus on Wikidata and Wikibase came from two points of alignment in particular: interest in linked open data for both library discovery systems and Wikipedia, and advancing a diversity and inclusion agenda in the cultures of both libraries and Wikimedia….”

The rise of Wikidata as a linked data source – Hanging Together

“As I analyze the responses to the OCLC Research 2018 International Linked Data Survey for Implementers, I’m looking out for significant differences with the responses to the previous, 2015 survey. One change that jumped out at me was the surge of using Wikidata as a linked data source consumed by linked data projects or services.”

Wikibase — Home

Wikibase Repository is a MediaWiki extension that lets you store and manage structured, non-relational data in a central, collaboratively managed repository.

Wikibase Client is a MediaWiki extension that lets you retrieve and embed structured data from a central repository into your wiki.
 
Query Service that allows you to query the contents of a Wikibase installation using SPARQL
 
Wikibase is also a set of reusable components that provide a foundation for tasks in the same domain….
 
Wikibase provides an all-purpose data model that takes knowledge diversity, sources and multilingual usage seriously.
 
Wikibase was developed for and is used by Wikidata, the free knowledge base and Wikipedia, the encyclopedia that anyone can edit.
 
Wikibase uses a component based software design that allows reuse without dictating which framework you should use….”