Improved standardization of transcribed digital specimen data

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Groom , Q , Dillen , M , Hardy , H , Phillips , S , Willemse , L & Wu , Z 2019 , ' Improved standardization of transcribed digital specimen data ' , Database-The journal of biological databases and curation , vol. 2019 , 129 .

Title: Improved standardization of transcribed digital specimen data
Author: Groom, Quentin; Dillen, Mathias; Hardy, Helen; Phillips, Sarah; Willemse, Luc; Wu, Zhengzhe
Contributor organization: Unit of Biodiversity Informatics
Finnish Museum of Natural History
Date: 2019-12-09
Language: eng
Number of pages: 14
Belongs to series: Database-The journal of biological databases and curation
ISSN: 1758-0463
Abstract: There are more than 1.2 billion biological specimens in the world's museums and herbaria. These objects are particularly important forms of biological sample and observation. They underpin biological taxonomy but the data they contain have many other uses in the biological and environmental sciences. Nevertheless, from their conception they are almost entirely documented on paper, either as labels attached to the specimens or in catalogues linked with catalogue numbers. In order to make the best use of these data and to improve the findability of these specimens, these data must be transcribed digitally and made to conform to standards, so that these data are also interoperable and reusable. Through various digitization projects, the authors have experimented with transcription by volunteers, expert technicians, scientists, commercial transcription services and automated systems. We have also been consumers of specimen data for taxonomical, biogeographical and ecological research. In this paper, we draw from our experiences to make specific recommendations to improve transcription data. The paper is split into two sections. We first address issues related to database implementation with relevance to data transcription, namely versioning, annotation, unknown and incomplete data and issues related to language. We then focus on particular data types that are relevant to biological collection specimens, namely nomenclature, dates, geography, collector numbers and uniquely identifying people. We make recommendations to standards organizations, software developers, data scientists and transcribers to improve these data with the specific aim of improving interoperability between collection datasets.
1181 Ecology, evolutionary biology
113 Computer and information sciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

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