IOS Press Launches Linked Data Portal

IOS Press is pleased to announce the beta launch of its Linked Data Portal: LD Connect. LD Connect contains linked metadata of all IOS Press books and journals. Making machine-readable metadata publicly available via this new platform opens up a wide range of opportunities.

Dr Einar Fredriksson, Founder and Director of IOS Press: “As a science publishing house operating in an era of digital transformation, we felt it was imperative for us to apply best practices to all aspects of our workflow. The potential of linked data is not lost on us. By offering our datasets in machine-readable form to third parties and semantic tools, we hope to contribute in a meaningful way to scientific progress.”

The un-siloing of data leads to improved retrieval, accessibility, reusability, and interoperability. Structured data can be searched, shared, reused, data mined, and linked to other data sources. Contextual relations between authors, institutions, and research areas can be made visible. Downstream applications such as abstracting and indexing databases can use the data portal to ensure their own datastores are always up to date with latest research published by IOS Press. Furthermore, authors who publish their work with IOS Press can do so under the assurance that their work is disseminated through both human and and machine accessible channels and following web-friendly standards.

LD Connect currently contains millions of triples, i.e., individual statements and maps connections between metadata of journal articles, book chapters, authors, affiliations, keywords, and other biographic metadata to provide a complete ecosystem of the IOS Press scholarly relationships. New data is continuously added and new data points will also be added to further enrich the portal. Tools that visualise the data for human consumption as well as tools for knowledge mining are currently under development.

More information

  • Please note that this is a beta release and the data as well as the relations between them may be incomplete or inaccurate and will be subject to change.
  • LD Connect was developed in collaboration with STKO Lab in Santa Barbara, CA, USA.
  • The complete dataset and its subsets are available for exploring at http://ld.iospress.nl. Further technical details can also be found there.
  • LD Connect seeks to connect with other datasets and parties. They welcome any feedback and suggestions.
  • Contact: Stephanie Delbecque, s.delbecque@iospress.nl

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