Envisaging a global infrastructure to exploit the potential of digitised collections.
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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. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in.
| Funder name | ISNI | Awards |
European Cooperation in Science and Technology, Belgium | Mobilise Action CA17106 on Mobilising Data, Experts and Policies in Scientific Collections | |
Centro de Estudos Ambientais e Marinhos, Universidade de Aveiro, Portugal / Fundação para a Ciência e a Tecnologia, Portugal / Ministério da Ciência, Tecnologia e Ensino Superior, Portugal | CESAM - FCT/MCTES UIDB/50017/2020+UIDP/50017/2020 | |
Fundação para a Ciência e a Tecnologia, Portugal / Ministério da Ciência, Tecnologia e Ensino Superior, Portugal | Ci2 - FCT/MCTES UIDP/05567/2020 | |
National Science Foundation, United States | DBI 2027654 | |
Fonds Wetenschappelijk Onderzoek, Begium | Grant no. FWO I001721N | |
Horizon 2020, European Union | BiCIKL (grant agreement No 101007492) - SYNTHESYS+ (grant agreement No 823827) | |
