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England, the year 1665. The newly-established “Royal Society of London for Improving Natural Knowledge’ published Philosophical Transactions – the world’s first science journal then and the oldest continuously-published journal today. It established the concepts of scientific priority, peer review, archiving, and dissemination – all of which are still valid today.
More than 350 years and thousands of issues later, the Royal Society is launching a machine learning project to discuss and demonstrate the opportunities that one of the fastest-evolving technologies opens up for publishers, researchers, and readers. Semantic Technology is one of the building blocks of innovative projects that many leading publishers are using today, aiming to unlock the full potential of the vast knowledge bases they possess.
In our digital age, contributors and consumers are overwhelmed by thousands of articles containing millions of field-specific scientific concepts. Researchers and readers alike find it increasingly challenging to discover the most relevant content they need. They want to be able to see how information is related across the scholarly domains.By bringing Semantic Technology to the game, publishers create smarter, faster and easier content publishing workflows on one hand, and smarter, faster and easier content consumption for readers, on the other. Click To Tweet
Articles enriched with semantic information extraction improve content discoverability and enable publishers to better understand the content they manage and distribute. By recognizing the mentions of concepts from an extensive knowledge base and the relationships between them, and linking these concepts to their mentions in the text of an article, publishers have the advantage of the knowledge behind.
Thus, they are able to have a complete view of ongoing research and article content and upgrade and up-sell that content by delivering better recommendations based on the semantic fingerprint of the articles and how they relate to other articles.
For the readers of academic content, the benefit of this process is that it enables them to discover what they are looking for with the help of semantic search. This kind of search uses semantics to find a concept and its meaning, rather than keywords or phrases present in the text. When served with the most relevant search results and related content recommendations that are tailored to their interests and needs, readers get a more meaningful experience while navigating through academic content and become more engaged.
Academic and scientific publishers have been benefiting for years from the interlinked and richer context that they get by using yet another valuable technology – Linked (Open) Data. LOD enables publishers to link their proprietary data to open, freely available data on the Web in order to provide richer and more relevant context.
Integrating, arranging and storing information as Linked Data makes it easier for publishers to repackage, repurpose and reuse content across various disciplines, subjects and concepts in order to engage the increasingly demanding users who want their content customized and delivered fast.
Indeed, some of the leading publishers are already using semantic technology to create and distribute smarter content for the benefit of researchers, academics, contributors and readers alike.
There’s Springer Nature – the publisher established in May 2015 through the merger of Nature Publishing Group, Palgrave Macmillan, Macmillan Education, and Springer Science+Business Media. To give you just a basic idea of the company’s relevance in academic and scientific circles: 8 out of the 11 Nobel Prize Laureates for 2016 were authors of research or books published by Springer Nature.
Springer Nature has already been using Linked Data for some time to help solve the data fragmentation problem and to promote a culture of data governance and reuse. The publisher relies on Linked Data to boost content discoverability via morphological variations and synonyms in searches.
More recently, Springer Nature has selected Ontotext’s industry-leading semantic graph database GraphDB™ to power its new Linked Open Data platform SN SciGraph that aggregates sources from Springer Nature and key partners in the scholarly domain.
Ontotext’s Semantic Technology helps Springer Nature’s LOD platform to collate high-quality data from trusted and reliable sources across the research landscape such as funders, research projects, conferences and publications. Click To Tweet This high-quality data provides a rich semantic description of how information is related and visualizes the scholarly domain in interesting new ways.
Next up, there’s The Institution of Engineering and Technology (IET) – one of the world’s largest engineering institutions with over 167,000 members in 150 countries. The IET has also picked Ontotext to deliver their Semantic Technology in order to enable customers to get a deeper understanding of current developments and extract more value from the data they work with.
The publisher is using Ontotext’s GraphDB to improve the text indexing and discoverability in its Inspec database. The Inspec database consists of more than 550 million authors, subjects, institutions and metadata tags, creating a large amount of interrelated and overlapping data. With its ability to handle massive load, querying, and inferencing in real time, Ontotext’s powerful graph database is enabling the IET to better understand the content it manages and distributes.
Finally, there’s Elsevier – the publisher of scientific, medical and technology journals and provider of information solutions. Elsevier has created its own Dynamic Knowledge Platforms (DKP) as part of a smart content solution. The platform provides services and APIs to store and retrieve content enrichment and semantic metadata about content available at Elsevier as well as from other resources on the Web.
As you can see, renowned global publishers have already integrated various types of Semantic Technology in the way they create, index, enrich, deliver, and customize their content. This improves knowledge discovery, speeds up delivery workflows and enables publishers to have a 360 view of their most precious resource – content.
Having richer and semantically linked content increases business opportunities for publishers to update and up-sell it, depending on their readers’ needs. It also helps them create bespoke offerings for groups of users, which increases reader engagement, brand exposure and awareness. Thus, the power to unlock knowledge and to easily repurpose and reuse content opens up new business opportunities for the publishers embracing Semantic Technology and innovation.
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