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Report . 2018
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Report . 2018
License: CC BY
Data sources: Datacite
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Entity-Fishing For Scholarly Publishing: Challenges And Recommendations

Authors: Bertino, Andrea; Foppiano, Luca; Arias, Javier; Ekanger, Aysa; Thoden, Klaus;

Entity-Fishing For Scholarly Publishing: Challenges And Recommendations

Abstract

On 4th September 2018 the Göttingen State and University Library, with the support of the Max Weber Stiftung, organised the second HIRMEOS Workshop on Entity-Fishing for Digital Humanities and Scholarly Publishing. Entity-fishing enables identification and resolution of entities: named entities like person-name, location, organizations, as well as specialist and less commonly classified ones, such as concepts, artifacts, etc. . The workshop aimed to discuss and clarify practical concerns arising when using the service and possible new use cases presented by Edition Open Access, ScholarLed and Septentrio Academic Publishing. This report describes challenges related to the development of these applications and provides recommendations for its integration and use on digital publishing platforms. The solutions proposed can be further applied on other domains.

Country
Germany
Keywords

Text Mining, NERD, Entity-recognition, Open Access, Monographs, HIRMEOS,

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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