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Landscape Analysis for the Specimen Data Refinery

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

Landscape Analysis for the Specimen Data Refinery

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
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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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
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
20
Top 10%
Top 10%
Top 10%
71
68
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gold