image: Providing publicly available linked machine-readable metadata from all IOS Press journals and books, LD Connect has been completely rebuilt and rebranded. Located at ld.iospress.nl, it features enhanced browse and semantic search capabilities, expanded data, and new tools. It also constructs artificial intelligence (AI)-powered embeddings derived from all full text data, further unsiloing research data and enriching contextual relationships. view more
Credit: IOS Press
Amsterdam/Santa Barbara, April 13, 2021 - IOS Press, an international publisher providing content and services for scientific, technical, and medical (STM) communities, is pleased to announce the relaunch of the renewed LD Connect (Linked Data Connect) website. Providing publicly available linked machine-readable metadata from all IOS Press journals and books, LD Connect has been completely rebuilt and rebranded. Located at ld.iospress.nl, it features enhanced browse and semantic search capabilities, expanded data, and new tools. It also constructs artificial intelligence (AI)-powered embeddings derived from all full text data, further unsiloing research data and enriching contextual relationships.
"We offer our linked data to the research and data science communities in order to stimulate new discoveries, enhance third party datasets, and empower innovation," explains IOS Press Digital Product Manager Stephanie Delbecque. "In collaboration with the research community, we are enriching and connecting human- and machine-readable data in more meaningful ways to contribute to an increased understanding of published research and furthering scientific progress."
Researchers, publishers, publishing analytics services, abstracting and indexing services, database developers, and other entities can benefit from LD Connect's improved retrieval, accessibility, reusability, and interoperability. Structured data can be searched, shared, reused, data mined, and linked to other data sources. With the help of machine learning techniques, the data conversion pipeline keeps on improving as more data are added.
By enriching and fostering the interlinking of data, contextual relationships among authors, institutions, and research areas can be visualized and interpreted and new relationships uncovered. LD Connect builds a powerful knowledge graph using links between the data known as "triples" in the form of subject-predicate-object expressions. Constructed from metadata from all IOS Press content, the portal currently contains about 16 million triples that provide a complete ecosystem of IOS Press scholarly relationships. Affiliations are geocoded and authors as well as affiliations are disambiguated using a co-reference resolution script.
LD Connect lets users explore its knowledge graph by browsing or using expert level semantic search. In addition, the complete dataset, its subsets, and additional technical details can be explored and downloaded.
To unleash the potential of LD Connect data IOS Press has worked in close collaboration with its users to develop a suite of powerful semantic search tools to query and visualize data: the LD Connect Toolbox. Harnessing the power of AI and machine learning, discovery tools that can unlock the relationships and patterns embedded in the data -- and help accelerate research - are currently in proof of concept stage.
"Thank you for providing this data for the scientific community! Publication metadata provided as knowledge graphs using established standards - as done in LD Connect - makes it much easier for any interested party to ingest and reuse this data, combine it with other data, etc. This enables easier development of applications such as literature search, topic tracing, reviewer finding, co-authorship network analysis, and more. I hope that other scholarly publishing houses will follow your lead!" observes Pascal Hitzler, PhD, Kansas State University.
"Because of LD Connect, authors who publish their work with IOS Press can do so with the assurance that their work is disseminated through both human- and machine-accessible channels," adds Stephanie.
LD Connect was developed in collaboration with STKO Lab at UCSB in Santa Barbara, CA, USA, and the co-reference resolution with DaSe Lab at Kansas State University in Manhattan, KS, USA.
The LD Connect team seeks collaboration with other datasets and parties and welcomes feedback and suggestions. Discover more about the LD Connect knowledge graph in the IOS Press Labs blog post.
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