Literature DB >> 30319307

Visualizing natural history collection data provides insight into collection development and bias.

Vaughn Shirey1,2.   

Abstract

Natural history collections contain estimated billions of records representing a large body of knowledge about the diversity and distribution of life on Earth. Assessments of various forms of bias within the aggregated data associated with specimens in these collections have been conducted across temporal, taxonomic, and spatial domains. Considering that these biases are the sum of biases across all contributing collections to aggregate datasets, the assessment of bias at the collection level is warranted. Interactive visualization provides a powerful tool for the assessment of these biases and insight into the historical development of natural history collections, providing context for where sources of bias may originate and developing historical narratives to clarify our understanding of our own knowledge about life on Earth. Here, I present a case study on using Sankey diagrams to illustrate the development of the entomology type collection at the Academy of Natural Sciences of Drexel University in Philadelphia, Pennsylvania with the hope that extensions of these practices among individual natural history collections are modified and adopted.

Entities:  

Keywords:  biodiversity informatics; data bias; natural history collections; visualization

Year:  2018        PMID: 30319307      PMCID: PMC6180142          DOI: 10.3897/BDJ.6.e26741

Source DB:  PubMed          Journal:  Biodivers Data J        ISSN: 1314-2828


  4 in total

1.  Widespread sampling biases in herbaria revealed from large-scale digitization.

Authors:  Barnabas H Daru; Daniel S Park; Richard B Primack; Charles G Willis; David S Barrington; Timothy J S Whitfeld; Tristram G Seidler; Patrick W Sweeney; David R Foster; Aaron M Ellison; Charles C Davis
Journal:  New Phytol       Date:  2017-10-30       Impact factor: 10.151

2.  Distorted views of biodiversity: spatial and temporal bias in species occurrence data.

Authors:  Elizabeth H Boakes; Philip J K McGowan; Richard A Fuller; Ding Chang-qing; Natalie E Clark; Kim O'Connor; Georgina M Mace
Journal:  PLoS Biol       Date:  2010-06-01       Impact factor: 8.029

3.  Taxonomic bias in biodiversity data and societal preferences.

Authors:  Julien Troudet; Philippe Grandcolas; Amandine Blin; Régine Vignes-Lebbe; Frédéric Legendre
Journal:  Sci Rep       Date:  2017-08-22       Impact factor: 4.379

4.  Temporal degradation of data limits biodiversity research.

Authors:  Geiziane Tessarolo; Richard Ladle; Thiago Rangel; Joaquin Hortal
Journal:  Ecol Evol       Date:  2017-07-27       Impact factor: 2.912

  4 in total

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