Herbarium collections shape our understanding of the world’s flora and are crucial for addressing global change and biodiversity conservation. The formation of such natural history collections, however, are not free from sociopolitical issues of immediate relevance. Despite increasing efforts addressing issues of representation and colonialism in natural history collections, herbaria have received comparatively less attention. While it has been noted that the majority of plant specimens are housed in the global North, the extent of this disparity has not been rigorously quantified to date. Here, by analyzing over 85 million specimen records and surveying herbaria across the globe, we assess the colonial legacy of botanical collections and how we may move towards a more inclusive future. We demonstrate that colonial exploitation has contributed to an inverse relationship between where plant biodiversity exists in nature and where it is housed in herbaria. Such disparities persist in herbaria across physical and digital realms despite overt colonialism having ended over half a century ago, suggesting ongoing digitization and decolonization efforts have yet to alleviate colonial-era discrepancies. We emphasize the need for acknowledging the inconvenient history of herbarium collections and the implementation of a more equitable, global paradigm for their collection, curation, and use.

The digitization of herbaria and their online access will greatly facilitate access to plant collections around the world. This will improve the efficiency of taxonomy and help reduce inequalities between scientists. The Botanic Garden Meise, Belgium, is currently digitizing 1.2 million specimens including label data. In this paper we describe the user requirements analysis conducted for a new herbarium web portal. The aim was to identify the required functionality, but also to assist in the prioritization of software development and data acquisition. The Garden conducted the analysis in cooperation with Clockwork, the digital engagement agency of Ordina. Using a series of interactive interviews, potential users were consulted from universities, research institutions, science-policy initiatives and the Botanic Garden Meise. Although digital herbarium data have many potential stakeholders, we focused on the needs of taxonomists, ecologists and historians, who are currently the primary users of the Meise herbarium data portal. The three categories of user have similar needs, all wanted as much specimen data as possible, and for those data, to be interlinked with other digital resources within and outside the Garden. Many users wanted an interactive system that they could comment on, or correct online, particularly if such corrections and annotations could be used to rank the reliability of data. Many requirements depend on the quality of the digitized data associated with each specimen. The essential data fields are the taxonomic name; geographic location; country; collection date; collector name and collection number. Also all researchers valued linkage between biodiversity literature and specimens. Nevertheless, to verify digitized data the researchers still want access to high quality images, even if fully transcribed label information is provided. The only major point of disagreement is the level of access users should have and what they should be allowed to do with the data and images. Not all of the user requirements are feasible given the current technical and regulatory landscape, however, the potential of these suggestions is discussed. Currently, there is no off-the-shelf solution to satisfy all these user requirements, but the intention of this paper is to guide other herbaria who are prioritising their investment in digitization and online web functionality.

Digitisation of natural history collections has evolved from creating databases for the recording of specimens' catalogue and label data to include digital images of specimens. This has been driven by several important factors, such as a need to increase global accessibility to specimens and to preserve the original specimens by limiting their manual handling. The size of the collections pointed to the need of high throughput digitisation workflows. However, digital imaging of large numbers of fragile specimens is an expensive and time-consuming process that should be performed only once. To achieve this, the digital images produced need to be useful for the largest set of applications possible and have a potentially unlimited shelf life. The constraints on digitisation speed need to be balanced against the applicability and longevity of the images, which, in turn, depend directly on the quality of those images. As a result, the quality criteria that specimen images need to fulfil influence the design, implementation and execution of digitisation workflows. Different standards and guidelines for producing quality research images from specimens have been proposed; however, their actual adaptation to suit the needs of different types of specimens requires further analysis. This paper presents the digitisation workflow implemented by Meise Botanic Garden (MBG). This workflow is relevant because of its modular design, its strong focus on image quality assessment, its flexibility that allows combining in-house and outsourced digitisation, processing, preservation and publishing ‡ ‡ ‡ § § § § § § © Nieva de la Hidalga A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.facilities and its capacity to evolve for integrating alternative components from different sources. The design and operation of the digitisation workflow is provided to showcase how it was derived, with particular attention to the built-in audit trail within the workflow, which ensures the scalable production of high-quality specimen images and how this audit trail ensures that new modules do not affect either the speed of imaging or the quality of the images produced.

The botanicalcollections.be website (http://www.botanicalcollections.be) is the culmination of the three year Digitale Ontsluiting Erfgoedcollecties (DOE!) project. Over this period we have digitally imaged 1.2 million African and Belgian herbarium specimens and much of their label data. All these data are freely available on our new virtual herbarium www.botani calcollections.be. For this we have to thank a generous grant from the Flemish Government.

There are many ways to capture data from herbarium specimen labels. Here we compare the results of in-house verses out-sourced data transcription with the aim of evaluating the pros and cons of each approach and guiding future projects that want to do the same. In 2014 Meise Botanic Garden (BR) embarked on a mass digitization project. We digitally imaged of some 1.2 million herbarium specimens from our African and Belgian Herbaria. The minimal data for a third of these images was transcribed in-house, while the remainder was out-sourced to a commercial company. The minimal data comprised the fields: specimen’s herbarium location, barcode, filing name, family, collector, collector number, country code and phytoregion (for the Democratic Republic of Congo, Rwanda & Burundi). The out-sourced data capture consisted of three types: additional label information for central African specimens having minimal data; complete data for the remaining African specimens; and, species filing name information for African and Belgian specimens without minimal data. As part of the preparation for out-sourcing, a strict protocol had to be established as to the criteria for acceptable data quality levels. Also, the creation of several lookup tables for data entry was necessary to improve data quality. During the start-up phase all the data were checked, feedback given, compromises made and the protocol amended. After this phase, an agreed upon subsample was quality controlled. If the error score exceeded the agreed level, the batch was returned for retyping. The data had three quality control checks during the process, by the data capturers, the contractor’s project managers and ourselves. Data quality was analysed and compared in-house versus out-sourced modes of data capture. The error rate by our staff versus the external company was comparable. The types of error that occurred were often linked to the specific field in question. These errors include problems of interpretation, legibility, foreign languages, typographic errors, etc. A significant amount of data cleaning and post-capture processing was required prior to import into our database, despite the data being of good quality according to protocol (error < 1%). By improving the workflow and field definitions a notable improvement could be made in the “data cleaning” phase. The initial motivation for capturing some data in-house was financial. However, after analysis, this may not have been the most cost effective approach. Many lessons have been learned from this first mass digitisation project that will implemented in similar projects in the future.