Abstract

The digital era provides new opportunities for taxonomists, as well as for everyone that studies biodiversity. Many herbaria have been able to digitize their collections, a process that started with the typing of label data, moving more recently towards the digitization of each sample with the simultaneous acquisition of high-resolution images. Here we discuss some of the challenges we faced in digitizing samples and provide a series of suggestions to avoid common mistakes for herbaria that have yet to start the process. We used a professional camera, database management software, and a barcode scanner to digitize the collections of herbaria CRI, ECT, FURB, LUSC, and UFRN. Pre-revision of samples with prior restoration when needed, barcode fixation, and a good database allowed faster digitization of samples. Good database software and the formation of a network among small herbaria accelerated digitization and increased the number of images available of Brazilian biodiversity. Thus far, our joint efforts made 118,000 specimen images available online with the purpose of accelerating botanical research.

Highlights

  • The advent of the computer ushered in a new era for the biological sciences, with new biodiversity analyses employing algorithms, especially in ecology and conservation research (Hampton et al 2013; Nualart et al 2017)

  • We discuss some of the challenges we faced in digitizing samples and provide a series of suggestions to avoid common mistakes for herbaria that have yet to start the process

  • We used a professional camera, database management software, and a barcode scanner to digitize the collections of herbaria CRI, ECT, FURB, LUSC, and UFRN

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Summary

Introduction

The advent of the computer ushered in a new era for the biological sciences, with new biodiversity analyses employing algorithms, especially in ecology and conservation research (Hampton et al 2013; Nualart et al 2017). Many herbaria have been able to digitize their collections, a process that started with the typing of label data, moving more recently towards the digitization of each sample with the simultaneous acquisition of high-resolution images.

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