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gas the imagery surrounding content is now becoming the trend. As such, the movement toward graphic and video representation of data (enhancing the visualisation and the understanding of complex concepts), is becoming more pronounced. Article and page design is being adjusted to accommodate the inclusion of infographics and video in association with, as well as embedded within the article. While machine learning is likely the next phase – requiring a level of sophistication of meta-tagging and word semantic association – for now, the ‘stopping power’ of an article, or of a dataset within an article, is very much the success factor for human comprehension.


White, ProQuest: Challenges of scale and responses to it are clearly the most important theme of the last decade. On any given topic, there is simply too much information available in myriad formats and modalities for a person to comfortably digest with ease. Machine learning, algorithmic personalisation, the rise and normalisation of Wikipedia, Google’s ‘Featured Snippets,’ and Netflix burying search in favour of browsable ‘taste clusters’ are all attempts to mediate discovery at scale and account for this. Semantic enrichment leans on these types of algorithmic solutions to attend to the scale problem. In exchange, these solutions lean on semantic enrichment to appropriately isolate content into trusted categories, giving machine learning a stake in the ground from which it can extrapolate and identify similar material.


In what ways do these developments benefit researchers, librarians, and the wider publishing community?


Marmanis, CCC: These developments are critical to properly harness the collective research community’s scholarly output. There is no manual process that can effectively synthesise, draw inferences from, and take action on the millions of research articles published annually, nor their accompanying data sets. Essentially, these trends are driving us toward paradigm shifts across research domains – from biomedical applications to chemical engineering – making current processes more efficient, but also introducing new workflows and opportunities.


Maciocci, eLife: They allow for faster discovery, easier and more precise searches for relevant literature, and the


12 Research Information August/September 2018


pure marketing concept, it is the easiest way to articulate the value related to the human factor – making research findings stand out among the noise and vastness of the literature. Beyond the stopping power of an


article being linked to readability, the discoverability of an article through machine-recognition is on equal footing as a benefit. In essence, beyond the complexity of article dissemination challenges, both for the human factor (attention) and for the machine factor (discoverability), the concept of ‘stopping power’ is equally applicable.


“On any given topic, there is simply too much information available for a person to comfortably digest”


ability to reuse published science in novel and unexpected ways. However, in order for semantically enriched papers to really be useful, publishers might want to consider providing the right application programming interfaces (APIs) to developers to ensure the papers are accessible beyond the publisher’s site – and not just by the dominant search engines and service providers, but by researchers and developers alike. At eLife, we’ve made sure our APIs can be used easily to access any part of the article, allowing the community to come up with novel uses for what we publish, from desktop library applications such as ScienceFair to the ability to read eLife digests using Amazon’s voice services. As more publishers begin to do this, we can expect to see the digital publishing of academic literature to really start moving beyond its print origins and toward a more useful, accessible and reusable form.


Samulack, Editage: In the case of researchers and librarians, personal time is often the limiting factor. For the publishing community at large, wide distribution and readership is the goal. For an overlooked segment in the initial question, the public- at-large (who are on the outside, looking in), ‘open’ accessibility and discoverability are the needs. For all population segments, semantic enrichment (the visualisation of data through enriched content like infographics and video) addresses the ‘stopping power’ of an article or element of data. While this is a


White, ProQuest: Much of scholarly inquiry is centred around the people or organisations producing primary/ secondary material. Curation of content around these entities – themselves semantic concepts – makes this kind of inquiry possible. Implemented well, semantic enrichment provides meaningful answers faster, allowing scholars to build on or discard hypotheses more quickly. Researchers and librarians don’t need to study a system-specific language or workflow to conduct their inquiries; rather they can navigate using natural language or academic vernacular that makes sense within their discipline. The best solutions balance an emphasis on the quickest, most likely answer, while still creating opportunity for the unexpected ‘eureka’ moments that move scholarship forward. For the publishing community, these developments give us more information that allow us to find unique ways to be more useful, more relevant in supporting scholarship.


How is your organisation currently enhancing the semantic enrichment process?


Marmanis, CCC: We embed semantic enrichment of content in various product offerings. We partner with state-of-the- art tools and semantic lexicon providers and we also create domain-specific word embeddings that help us to further enhance our content.


Melissa Harrison, head of production operations, at eLife: eLife’s content represents a small fraction of the literature and, although we put a lot of effort into the quality of our JATS XML, working alone will not help with the aspirations we have for science. We are therefore active in the JATS community and have fostered JATS4R as a central organisation g


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