The world’s natural history collections constitute an enormous evidence base for scientific research on the natural world. To facilitate these studies and improve access to collections, many organisations are embarking on major programmes of digitization. This requires automated approaches to mass-digitization that support rapid imaging of specimens and associated data capture, in order to process the tens of millions of specimens common to most natural history collections. In this paper we present Inselect—a modular, easy-to-use, cross-platform suite of open-source software tools that supports the semi-automated processing of specimen images generated by natural history digitization programmes. The software is made up of a Windows, Mac OS X, and Linux desktop application, together with command-line tools that are designed for unattended operation on batches of images. Blending image visualisation algorithms that automatically recognise specimens together with workflows to support post-processing tasks such as barcode reading, label transcription and metadata capture, Inselect fills a critical gap to increase the rate of specimen digitization.
The world’s natural history collections contain at least 2 billion specimens, representing a unique data source for answering fundamental scientific questions about ecological, evolutionary, and geological processes. Unlocking this treasure trove of data, stored in thousands of museum drawers and cabinets, is crucial to help map a sustainable future for ourselves and the natural systems on which we depend. The rate-limiting steps in the digitisation of natural history collections often involve specimen handling due to their fragile nature. Insects comprise the single largest collection type in the Natural History Museum, London (NHM), reflecting their global diversity. The NHM pinned insect collection, estimated at 25 million specimens, will take over 700 person years to digitise at current rates. In order to ramp up digitisation we have developed ALICE for Angled Label Image Capture and Extraction. This multi-camera setup and associated software processing pipeline enables primary data capture from angled images, without removal of the labels from the specimen pin. As a result ALICE enables a single user to sustainably image over 1,000 specimens per day, allowing us to digitally unlock the insect collections at an unprecedented rate.
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