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Natural History institutes hold an immense number of specimens and artefacts. For years these collections were not accessible online, remaining inaccessible to researchers from far away and hidden from the general public. Large digitisation projects and cross-institutional agreements aim to bring their collections into the digital era, such as the SYNTHESYS+ project and the Distributed System of Scientific Collections (DiSSCo) Research Infrastructure. As specimens are 3D physical objects with different characteristics many techniques are available to 3D digitise them. For inexperienced users this can be quite overwhelming. Which techniques are already well tested in other institutions and are suitable for a specific specimen or collection? To investigate this, we have set up a dichotomous identification key for digitisation techniques: DIGIT-KEY, (https://digit.naturalheritage.be/digit-key). For each technique, examples used in SYNTHESYS+ Institutions are visualised and training manuals provided. All information can be easily updated and representatives can be contacted if necessary to request more information about a certain technique. This key can be helpful to achieve comparable results across institutions when digitising collections on demand in future DiSSCo research initiatives coordinated through the European Loans and Visits System (ELViS) for Virtual and Transnational Access.

Caesalpinioideae is the second largest subfamily of legumes (Leguminosae) with ca. 4680 species and 163 genera. It is an ecologically and economically important group formed of mostly woody perennials that range from large canopy emergent trees to functionally herbaceous geoxyles, lianas and shrubs, and which has a global distribution, occurring on every continent except Antarctica. Following the recent re-circumscription of 15 Caesalpinioideae genera as presented in Advances in Legume Systematics 14, Part 1, and using as a basis a phylogenomic analysis of 997 nuclear gene sequences for 420 species and all but five of the genera currently recognised in the subfamily, we present a new higher-level classification for the subfamily. The new classification of Caesalpinioideae comprises eleven tribes, all of which are either new, reinstated or re-circumscribed at this rank: Caesalpinieae Rchb. (27 genera / ca. 223 species), Campsiandreae LPWG (2 / 5–22), Cassieae Bronn (7 / 695), Ceratonieae Rchb. (4 / 6), Dimorphandreae Benth. (4 / 35), Erythrophleeae LPWG (2 /13), Gleditsieae Nakai (3 / 20), Mimoseae Bronn (100 / ca. 3510), Pterogyneae LPWG (1 / 1), Schizolobieae Nakai (8 / 42–43), Sclerolobieae Benth. & Hook. f. (5 / ca. 113). Although many of these lineages have been recognised and named in the past, either as tribes or informal generic groups, their circumscriptions have varied widely and changed over the past decades, such that all the tribes described here differ in generic membership from those previously recognised. Importantly, the approximately 3500 species and 100 genera of the former subfamily Mimosoideae are now placed in the reinstated, but newly circumscribed, tribe Mimoseae. Because of the large size and ecological importance of the tribe, we also provide a clade-based classification system for Mimoseae that includes 17 named lower-level clades. Fourteen of the 100 Mimoseae genera remain unplaced in these lower-level clades: eight are resolved in two grades and six are phylogenetically isolated monogeneric lineages. In addition to the new classification, we provide a key to genera, morphological descriptions and notes for all 163 genera, all tribes, and all named clades. The diversity of growth forms, foliage, flowers and fruits are illustrated for all genera, and for each genus we also provide a distribution map, based on quality-controlled herbarium specimen localities. A glossary for specialised terms used in legume morphology is provided. This new phylogenetically based classification of Caesalpinioideae provides a solid system for communication and a framework for downstream analyses of biogeography, trait evolution and diversification, as well as for taxonomic revision of still understudied genera.

There are approximately 1.5 billion specimens kept in European Natural History Collections. The mission for the Distributed System of Scientific Collections (DiSSCo) is to unite all these specimens into a one-stop e-science infrastructure of digital specimens. This is a monumental digitisation task and criteria for how to prioritise this effort are, therefore, crucial for the success of the project. In this report, we have reviewed the literature and designed and conducted surveys of the digitisation plans and criteria used by DiSSCo Partners to understand the prioritisation criteria used in the digitisation of natural history collections. As an attempt to provide some guidance for the digitisation of specimens, we suggest that an organisation (e.g. DiSSCo or an individual institution) that is planning to digitise natural history collections considers four categories of prioritisation criteria: Relevance, Data quality, Cost and Feasibility.

Scientific collections have been built by people. For hundreds of years, people have collected, studied, identified, preserved, documented and curated collection specimens. Understanding who those people are is of interest to historians, but much more can be made of these data by other stakeholders once they have been linked to the people’s identities and their biographies. Knowing who people are helps us attribute work correctly, validate data and understand the scientific contribution of people and institutions. We can evaluate the work they have done, the interests they have, the places they have worked and what they have created from the specimens they have collected. The problem is that all we know about most of the people associated with collections are their names written on specimens. Disambiguating these people is the challenge that this paper addresses. Disambiguation of people often proves difficult in isolation and can result in staff or researchers independently trying to determine the identity of specific individuals over and over again. By sharing biographical data and building an open, collectively maintained dataset with shared knowledge, expertise and resources, it is possible to collectively deduce the identities of individuals, aggregate biographical information for each person, reduce duplication of effort and share the information locally and globally. The authors of this paper aspire to disambiguate all person names efficiently and fully in all their variations across the entirety of the biological sciences, starting with collections. Towards that vision, this paper has three key aims: to improve the linking, validation, enhancement and valorisation of person-related information within and between collections, databases and publications; to suggest good practice for identifying people involved in biological collections; and to promote coordination amongst all stakeholders, including individuals, natural history collections, institutions, learned societies, government agencies and data aggregators.