2019
DOI: 10.1016/j.websem.2018.06.002
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Semantic annotation of natural history collections

Abstract: Large collections of historical biodiversity expeditions are housed in natural history museums throughout the world. Potentially they can serve as rich sources of data for cultural historical and biodiversity research. However, they exist as only partially catalogued specimen repositories and images of unstructured, non-standardised, handwritten text and drawings. Although many archival collections have been digitised, disclosing their content is challenging. They refer to historical place names and outdated t… Show more

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Cited by 17 publications
(12 citation statements)
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References 34 publications
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“…This is a significant problem in SBD, which primarily represents implied content. Also, some implicit information needs background knowledge to support its inference, which can be addressed by combining the semantic-based bridge with ontology models (Stepanov et al 2018, Stork et al 2018. This can describe both directly and indirectly related entities by identifying hidden relations.…”
Section: An Existing Event Description For Emergency Event Understandingmentioning
confidence: 99%
“…This is a significant problem in SBD, which primarily represents implied content. Also, some implicit information needs background knowledge to support its inference, which can be addressed by combining the semantic-based bridge with ontology models (Stepanov et al 2018, Stork et al 2018. This can describe both directly and indirectly related entities by identifying hidden relations.…”
Section: An Existing Event Description For Emergency Event Understandingmentioning
confidence: 99%
“…Fisher and Mantle (2012) described noninvasive specimen scanning methodology, without even taking items out of collection drawers. Stork et al (2019) have recently started a global-scale project to link digital data of specimen collections of natural history findings worldwide in a single Internet database. Digitized information of collections makes them more accessible to a wider scientific community and suitable for digital analysis for a broad range of future research (Colvin 2014;Enghoff and Seberg 2006;Gutiérrez and Pine 2017;McLean et al 2015;NSCA 2005;Ownes and Duin 2008;Page et al 2015;Sánchez-Cordero and Martinez-Meyer 2000;Singh and Singh 2012;Wiedenmann, Dowling, and Barnes 2014).…”
Section: Specimen Digitization and Databasingmentioning
confidence: 99%
“…Provenance analysis is a well-known topic in data-centric domains such as the data annotation, management, and warehousing [18][19][20][21]. However, the problem of IPA is not intensively studied so far in the literature.…”
Section: Related Workmentioning
confidence: 99%