Descriptive Metadata for Field Books: Methods and Practices of the Field Book Project

Nakasone, Sonoe; Sheffield, Carolyn

doi:10.1045/november2013-nakasone

“…The Field Book Project makes use of the Natural Collections Description (NCD) 12 standard for storing metadata on a collection level. Further, the project uses the Metadata Object Description Schema (MODS) 13 to create item level metadata [28]. The Biodiversity Heritage Library (BHL) 14 describe their data using XML and MODS or Dublin Core (DC).…”

Section: Semantic Annotation Of Natural History Collectionsmentioning

confidence: 99%

“…Coupling them with background knowledge, and linking them through formal descriptions, provides connectivity throughout the documents [21]. Work has already been done linking collections and items using the principles of linked data, not only regarding biodiversity [15,28], but cultural heritage collections in general [9,7,8,6,10,11]. Fewer examples exist where the content of items in such collections are semantically linked [7].…”

Section: Introductionmentioning

confidence: 99%

Semantic annotation of natural history collections

Stork¹,

Weber

²

,

Miracle

³

et al. 2019

Journal of Web Semantics

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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 They refer to historical place names and outdated taxonomic classifications and are written in multiple languages. Efforts to transcribe the handwritten text can make the content accessible, but semantically describing and interlinking the content would further facilitate research. We propose a semantic model that serves to structure the named entities in natural history archival collections. In addition, we present an approach for the semantic annotation of these collections whilst documenting their provenance. This approach serves as an initial step for an adaptive learning approach for semi-automated extraction of named entities from natural history archival collections. The applicability of the semantic model and the annotation approach is demonstrated using image scans from a collection of 8,000 field book pages gathered by the Committee for Natural History of the Netherlands Indies between 1820 and 1850, and evaluated together with domain experts from the field of natural and cultural history.

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“…The inclusion of these materials in digitization efforts was virtually unheard of a decade ago but is now increasing in prevalence. Some efforts, such as the Field Book Project (98), have focused on the digitization and annotation of original field notes, sketches, maps, and images. Others, such as the Collection Resources for Aquatic Coleoptera project (http://creac.kubiodiversityinstitute.org/collections/), emphasize not just the digitization of these materials but also their association with the specimens themselves (if they exist) in a single integrated platform.…”

Section: Field To Database: Digitization Beyond Specimensmentioning

confidence: 99%

“…Probably the biggest boost to morphology outside of improved microscopes was the advent of digital, threedimensional (3D) reconstructions of morphological features (25,44). Such 3D data have been used for deciphering the phylogenetic relationships of insect taxa (e.g., 9,41,42,43,55,102), obtaining additional data from amber and compression fossils (e.g., 1,50,101,104,117,132), examining internal anatomy (e.g., 35,40,68,86,87,105,124,152), investigating internal musculature used for power-amplified movements (e.g., 149), and describing new species in taxonomic revisions (e.g., 37,84,85,127). However, Deans et al (25, p. 328) highlight that "internal anatomy remains a largely untapped resource for evidence of taxonomic association and evolutionary history" and call for expanded use of modern techniques that provide access to internal features.…”

Section: Morphology: the Cuticle And Beyondmentioning

confidence: 99%

Entomological Collections in the Age of Big Data

Short

¹

,

Dikow

²

,

Moreau

³

2018

Annu. Rev. Entomol.

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With a million described species and more than half a billion preserved specimens, the large scale of insect collections is unequaled by those of any other group. Advances in genomics, collection digitization, and imaging have begun to more fully harness the power that such large data stores can provide. These new approaches and technologies have transformed how entomological collections are managed and utilized. While genomic research has fundamentally changed the way many specimens are collected and curated, advances in technology have shown promise for extracting sequence data from the vast holdings already in museums. Efforts to mainstream specimen digitization have taken root and have accelerated traditional taxonomic studies as well as distribution modeling and global change research. Emerging imaging technologies such as microcomputed tomography and confocal laser scanning microscopy are changing how morphology can be investigated. This review provides an overview of how the realization of big data has transformed our field and what may lie in store.

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Semantic Annotation of Natural History Collections

Stork

¹

,

Weber

²

,

Miracle

³

et al. 2018

SSRN Journal

2

0

View full text Add to dashboard Cite

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 taxonomic classifications and are written in multiple languages. Efforts to transcribe the handwritten text can make the content accessible, but semantically describing and interlinking the content would further facilitate research. We propose a semantic model that serves to structure the named entities in natural history archival collections. In addition, we present an approach for the semantic annotation of these collections whilst documenting their provenance. This approach serves as an initial step for an adaptive learning approach for semi-automated extraction of named entities from natural history archival collections. The applicability of the semantic model and the annotation approach is demonstrated using image scans from a collection of 8,000 field book pages gathered by the Committee for Natural History of the Netherlands Indies between 1820 and 1850, and evaluated together with domain experts from the field of natural and cultural history.

show abstract

Descriptive Metadata for Field Books: Methods and Practices of the Field Book Project

Cited by 3 publications

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Semantic annotation of natural history collections

Semantic annotation of natural history collections

Entomological Collections in the Age of Big Data

Semantic Annotation of Natural History Collections

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