“The use of meta- tagging and word semantic association

nomenclature will become very important”


to bring together both open access and subscription-based publishers to agree on basic principles to make cross- publisher XML more comparable and mineable. We also subscribe to the Joint Declaration of Data Citations Principles and have been active in promoting the implementation of these principles within cross-publisher groups. We support the use of PIDs and also new initiatives such as the CReDIT taxonomy. Being involved in cross-publisher working groups and pulling together the editorial and technical representatives and infrastructure to realise these initiatives to their full potential is a challenge that all publishers are facing.

Samulack, Editage: At Editage, while we’ve been heavily focused on the readability of an article and how it is written and structured, we’ve also been focused on strategies of enhancement and enrichment of content within the research article. We’re bringing awareness to the publishing industry that the use of video and infographics highlight key findings and add stopping power to the attractiveness, curiosity, and discoverability (through DOI tags) of the article. Successful, high-profile collaborations with Cell Press, Brill, the Journal of Bone and Joint Surgery, the journal Neurology, and others, have been a testament to the success of semantic enrichment in both illustrative

14 Research Information August/September 2018

and written forms. In addition, we have been developing an automated document assessment tool, called Ada, to help cut down on the time and cost associated with desk rejections. Ada is a machine-driven document screening tool that leverages semantic rule-based decision-making algorithms to assess the readability of a scientific manuscript. Whether at point of manuscript receipt, or at any point in the editorial process, Ada can be taught to offer standardised and objective semantic decision-making surrounding the worthiness of moving forward with a manuscript on the grounds of a readability grade, compliance to certain pre-set ethical criteria such as plagiarism, standard guideline disclosures, and/or an internal checklist of language inclusions.

White, ProQuest: Not all content is text- based. Not all content can be ‘owned’ by one publisher. Relevance of content may differ among disparate user groups. Content interactions should factor in all of what was produced and who produced it, but also its importance to specific users consuming it. We work to find innovative ways to break down those silos – across modalities, publishers, publishing models and user groups – to ensure the answers we provide are complete, correct, and relevant. This takes the challenge of scale and adds new wrinkles, because less is under our immediate control. Matching a journal article with a video, an archival finding aid, an audio recording and a set of statistics, some of which we possess in our databases and some not – and ensuring all of it is immediately relevant to you is the goal. Allowing information to exist as it is without conforming to our needs as a publisher, while layering on top our semantic enrichment in support of scholarship is a major focus for us.

Looking to the future of scholarly communications, can you predict any major developments in the field of semantic enrichment?

Marmanis, CCC: The primary source of semantic enrichment is well-curated semantic lexicons. A major development in the field of

semantic enrichment would be the ability to develop semantic lexicons specific to a domain of discourse on the basis of a representative corpus, with minimal human intervention and in a way that is highly-accurate, cost-efficient, and complete.

Maciocci, eLife: Both semantic enrichment at the publisher side and the emergence of increasingly ‘smart’ AI, in combination with a broader uptake of open access, may lead to an increase in meta-discovery, where large-scale data mining of a semantically enriched corpus can generate new insights by uncovering previously unknown trends and correlations across seemingly unrelated papers. AI is likely to see an increase in the automatic inference of semantic context, reducing the amount of labour needed during the production and publication of online manuscripts by automating parts of the semantic tagging process.

Samulack, Editage: Because of the movement toward the future of machine reading, machine learning, and various other associated aspects of artificial intelligence, the use of meta-tagging and word semantic association nomenclature will become very important. But also, because of the focus today surrounding the human factor of article enrichment (infographics, video, and other forms of imagery), the ability to read this content and to fingerprint large data sets will be a challenge that needs to be addressed. Imagery will need to be accompanied by embedded plain language descriptions (like alt-text in support of machine readers for the visually impaired), and large datasets will need to have semantic descriptors to clarify parameters of context and scope that a machine can understand.

White, ProQuest: The knowledge graphs produced by human- and machine-based entity extraction have already started to supplant the content from which these entities were extracted as a source of answers to questions. Further evolutions toward open access publishing and the accompanying scale will accelerate this change. Traditional ‘relevance ranked search’ as a method of uncovering appropriate research materials will become an anachronism and semantic enrichment solutions will replace it. Users will expect their information systems to present trusted seminal works at the top of search results, vetted by the evidence of usage, in a context that explains how any answer was derived from the knowledge graph and cited content. The best of these solutions will be neither strictly AI nor strictly human-facilitated, but rather will strike a unique and interesting balance between the two. This, in turn, will expand the types of scholarly communications and inquiries available to researchers – and who knows what we will learn then?

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