Publications by authors named "Laurence Livermore"

We present a genome assembly from an individual male (the meadow plant bug; Arthropoda; Insecta; Hemiptera; Miridae). The genome sequence is 987.9 megabases in span.

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Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed.

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Background: In 2018, the Natural History Museum (NHMUK, herbarium code: BM) undertook a pilot digitisation project together with the Royal Botanic Gardens Kew (project Lead) and the Royal Botanic Garden Edinburgh to collectively digitise non-type herbarium material of the subtribe Phaseolinae and the genera L.f. and Jacq.

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Determining when animal populations have experienced stress in the past is fundamental to understanding how risk factors drive contemporary and future species' responses to environmental change. For insects, quantifying stress and associating it with environmental factors has been challenging due to a paucity of time-series data and because detectable population-level responses can show varying lag effects. One solution is to leverage historic entomological specimens to detect morphological proxies of stress experienced at the time stressors emerged, allowing us to more accurately determine population responses.

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The digitising efforts of herbaria aim to increase access to and impact of scientific collections, by making the data digitally accessible to the global community. Digitising the NHMUK's botanical collection of around 5.1 million specimens is an ongoing process, but the majority of the type collections have already been imaged.

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The Natural History Museum, London (NHM) has embarked on an ambitious programme to digitise its collections. One aim of the programme has been to improve the workflows and infrastructure needed to support high-throughput digitisation and create comprehensive digital inventories of large scientific collections. This paper presents the workflow developed to digitise the entire Phthiraptera (parasitic lice) microscope slide collection (70,663 slides).

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Background: More and more herbaria are digitising their collections. Images of specimens are made available online to facilitate access to them and allow extraction of information from them. Transcription of the data written on specimens is critical for general discoverability and enables incorporation into large aggregated research datasets.

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Background A revised checklist of the British and Irish Chalcidoidea and Mymarommatoidea substantially updates the previous comprehensive checklist, dating from 1978. Country level data (i.e.

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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.

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Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated information, are minimized. Digitization of larger collections should employ an "industrial" approach, using the principles of automation and crowd sourcing, with minimal initial metadata collection including a mandatory persistent identifier.

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The Scratchpad Virtual Research Environment (http://scratchpads.eu/) is a flexible system for people to create their own research networks supporting natural history science. Here we describe Version 2 of the system characterised by the move to Drupal 7 as the Scratchpad core development framework and timed to coincide with the fifth year of the project's operation in late January 2012.

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