Five task clusters that enable efficient and effective digitization of biological collections
Identifieur interne : 000262 ( Main/Exploration ); précédent : 000261; suivant : 000263Five task clusters that enable efficient and effective digitization of biological collections
Auteurs : Gil Nelson [États-Unis] ; Deborah Paul [États-Unis] ; Gregory Riccardi [États-Unis] ; Austin R. Mast [États-Unis]Source :
- ZooKeys [ 1313-2989 ] ; 2012.
Abstract
This paper describes and illustrates five major clusters of related tasks (herein referred to as
Url:
DOI: 10.3897/zookeys.209.3135
PubMed: 22859876
PubMed Central: 3406464
Affiliations:
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<front><div type="abstract" xml:lang="en"><label>Abstract</label>
<p>This paper describes and illustrates five major clusters of related tasks (herein referred to as <italic>task clusters</italic>
) that are common to efficient and effective practices in the digitization of biological specimen data and media. Examples of these clusters come from the observation of diverse digitization processes. The staff of iDigBio (The U.S. National Science Foundation’s National Resource for Advancing Digitization of Biological Collections) visited active biological and paleontological collections digitization programs for the purpose of documenting and assessing current digitization practices and tools. These observations identified five task clusters that comprise the digitization process leading up to data publication: (1) pre-digitization curation and staging, (2) specimen image capture, (3) specimen image processing, (4) electronic data capture, and (5) georeferencing locality descriptions. While not all institutions are completing each of these task clusters for each specimen, these clusters describe a composite picture of digitization of biological and paleontological specimens across the programs that were observed. We describe these clusters, three workflow patterns that dominate the implemention of these clusters, and offer a set of workflow recommendations for digitization programs.</p>
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