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landscape analysis for the specimen data refinery

descriptionPublicationkeyboard_double_arrow_right Article 14 Aug 2020 United Kingdom Publisher:Pensoft PublishersJournal:Research Ideas and Outcomes, volume 6 (eissn: 2367-7163,

Authors: Walton, Stephanie; Livermore, Laurence; Bánki, Olaf; Cubey, Robert; Drinkwater, Robyn; Englund, Markus; Goble, Carole; +63 Authors

doi: 10.3897/rio.6.e57602

handle: 10261/239620

landscape analysis for the specimen data refinery

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Abstract

This report reviews the current state-of-the-art applied approaches on automated tools, services and workflows for extracting information from images of natural history specimens and their labels. We consider the potential for repurposing existing tools, including workflow management systems; and areas where more development is required. This paper was written as part of the SYNTHESYS+ project for software development teams and informatics teams working on new software-based approaches to improve mass digitisation of natural history specimens.

Country

United Kingdom

Related Organizations

The University of Manchester
Royal Botanic Gardens
United Kingdom
MUSEUM NATIONAL D'HISTOIRE NATURELLE
France
University of Salford
United Kingdom
Royal Botanic Garden Edinburgh
United Kingdom

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Keywords

collections digitisation, workflow management, Science, Digitisation, Natural history specimens, Machine learning, natural language processing, Linked open data, data reconciliation, nat, Data refinery, digitisation, data refinery, Natural language processing, Q, natural history specimens, Workflow management, Collections digitisation, Semantic segmentation, semantic segmentation, Data reconciliation, machine learning, linked open data

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Supplementary material 1 from: Walton S, Livermore L, Bánki O, Cubey RWN, Drinkwater R, Englund M, Goble C, Groom Q, Kermorvant C, Rey I, Santos CM, Scott B, Williams AR, Wu Z (2020) Landscape Analysis for the Specimen Data Refinery. Research Ideas and Outcomes 6: e57602. https://doi.org/10.3897/rio.6.e57602
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Impact byBIP!

	citations 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).	16
	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.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%