Service-based information extraction from herbarium specimens

By

Reimeier, Fabian
Röpert, Dominik
Güntsch, Anton
Kirchhoff, Agnes
Berendsohn, Walter G., 1965-

Type

Article

Date of Publication

2018-5-21

Original Publication

Metabarcoding and metagenomics

Volume

2

Pages

1--2

Subjects

herbarium sheets , image analysis , Optical Character Recognition , Web Service , workflow

Contributed by

Pensoft Publishers

Language

English

Published by

Bulgaria Pensoft Publishers 2017-

Identifiers

DOI: https://doi.org/10.3897/biss.2.25415

 

Abstract

On herbarium sheets, data elements such as plant name, collection site, collector, barcode and accession number are found mostly on labels glued to the sheet. The data are thus visible on specimen images. With continuously improving technologies for collection mass-digitisation it has become easier and easier to produce high quality images of herbarium sheets and in the last few years herbarium collections worldwide have started to digitize specimens on an industrial scale (Tegelberg et al. 2014). To use the label data contained in these massive numbers of images, they have to be captured and databased. Currently, manual data entry prevails and forms the principal cost and time limitation in the digitization process. The StanDAP-Herb Project has developed a standard process for (semi-) automatic detection of data on herbarium sheets. This is a formal extensible workflow integrating a wide range of automated specimen image analysis services, used to replace time-consuming manual data input as far as possible. We have created web-services for OCR (Optical Character Recognition); for identifying regions of interest in specimen images and for the context-sensitive extraction of information from text recognized by OCR. We implemented the workflow as an extension of the OpenRefine platform (Verborgh and De Wilde 2013).