People are involved with the collection and curation of all biodiversity data, whether they are researchers, members of the public, taxonomists, conservationists, collection managers or wildlife managers. Knowing who those people are and connecting their biographical information to the biodiversity data they collect helps us contextualise their scientific work. We are particularly concerned with those people and communities involved in the collection and identification of biological specimens. People from herbaria and natural science museums have been collecting and preserving specimens from all over the world for more than 200 years. The problem is that many of these people are only known by unstandardized names written on specimen labels, often with only initials and without any biographical information. The process of identifying and linking individuals to their biographies enables us to improve the quality of the data held by collections while also quantifying the contributions of the often underappreciated people who collected and identified these specimens. This process improves our understanding of the history of collecting, and addresses current and future needs for maintaining the provenance of specimens so as to comply with national and international practices and regulations. In this talk we will outline the steps that collection managers, data scientists, curators, software engineers, and collectors can take to work towards fully disambiguated collections. With examples, we can show how they can use these data to help them in their work, in the evaluation of their collections, and in measuring the impact of individuals and organisations, local to global. 
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                            The disambiguation of people names in biological collections
                        
                    
    
            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. 
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                            - Award ID(s):
- 2033973
- PAR ID:
- 10377064
- Date Published:
- Journal Name:
- Biodiversity Data Journal
- Volume:
- 10
- ISSN:
- 1314-2836
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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