Envisaging a global infrastructure to exploit the potential of digitised collections

Quentin Groom; Mathias Dillen; Wouter Addink; Arturo H. H. Ariño; Christian Bölling; Pierre Bonnet; Lorenzo Cecchi; Elizabeth R. Ellwood; Rui Figueira; Pierre-Yves Gagnier; Olwen M Grace; Anton Güntsch; Helen Hardy; Pieter Huybrechts; Roger Hyam; Alexis Joly; Vamsi Krishna Kommineni; Isabel Larridon; Laurence Livermore; Ricardo Jorge Lopes; Sofie Meeus; Jeremy A. Miller; Kenzo Milleville; Renato Panda; Marc Pignal; Jorrit H. Poelen; Blagoj Ristevski; Tim Robertson; Ana C Rufino; Joaquim Santos; Maarten Schermer; Ben Scott; Katja Chantre Seltmann; Heliana Teixeira; Maarten Trekels; Jitendra Gaikwad

doi:10.3897/bdj.11.e109439

Envisaging a global infrastructure to exploit the potential of digitised collections

Quentin Groom, Mathias Dillen, Wouter Addink, Arturo H. H. Ariño, Christian Bölling, Pierre Bonnet, Lorenzo Cecchi, Elizabeth R. Ellwood, Rui Figueira, Pierre-Yves Gagnier, Olwen M Grace, Anton Güntsch, Helen Hardy, Pieter Huybrechts, Roger Hyam, Alexis Joly, Vamsi Krishna Kommineni, Isabel Larridon, Laurence Livermore, Ricardo Jorge LopesSofie Meeus, Jeremy A. Miller, Kenzo Milleville, Renato Panda, Marc Pignal, Jorrit H. Poelen, Blagoj Ristevski, Tim Robertson, Ana C Rufino, Joaquim Santos, Maarten Schermer, Ben Scott, Katja Chantre Seltmann, Heliana Teixeira, Maarten Trekels, Jitendra Gaikwad

Open science lab for biodiversity

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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.

Oorspronkelijke taal	Engels
Tijdschrift	Biodiversity Data Journal
Volume	11
Exemplaarnummer	e109439
ISSN	1314-2828
DOI's	https://doi.org/10.3897/bdj.11.e109439
Publicatiestatus	Gepubliceerd - 30-nov.-2023

Thematische Lijst 2020

Data & Infrastructuur

Technologisch

ICT
beeldverwerking
beeldanalyse
bibliotheektechnieken
statistiek en modellering
bibliotheekkunde

Toegang verkrijgen tot document

10.3897/bdj.11.e109439Licentie: CC BY

BDJ_article_109439Licentie: CC BY

DiSSCo Vlaanderen (EVINBO)
De Wever, A. (Projectleider), Baert, K. (Medewerker), Berlengee, F. (Medewerker), Cools, N. (Medewerker), Cox, K. (Medewerker), De Cuyper, B. (Medewerker), De Haeck, A. (Medewerker), De Vos, B. (Medewerker), Gouwy, J. (Medewerker), Herr, C. (Medewerker), Huysentruyt, F. (Medewerker), Lettens, S. (Medewerker), Pieters, S. (Medewerker), Pollet, M. (Medewerker), Rutten, A. (Medewerker), Schamp, K. (Medewerker), Schouppe, M. (Medewerker), Teunen, L. (Medewerker), Van Den Berge, K. (Medewerker), Vanden Broeck, A. (Medewerker), Vander Mijnsbrugge, K. (Medewerker), Veltjen, E. (Medewerker), Verstraeten, A. (Medewerker) & Wilms, H. (Medewerker)
1/01/21 → 31/12/28
Project: Evinbo

Dit citeren

Groom, Q., Dillen, M., Addink, W., Ariño, A. H. H., Bölling, C., Bonnet, P., Cecchi, L., Ellwood, E. R., Figueira, R., Gagnier, P.-Y., Grace, O. M., Güntsch, A., Hardy, H., Huybrechts, P., Hyam, R., Joly, A., Kommineni, V. K., Larridon, I., Livermore, L., ... Gaikwad, J. (2023). Envisaging a global infrastructure to exploit the potential of digitised collections. Biodiversity Data Journal, 11(e109439). https://doi.org/10.3897/bdj.11.e109439

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title = "Envisaging a global infrastructure to exploit the potential of digitised collections",

abstract = "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.",

author = "Quentin Groom and Mathias Dillen and Wouter Addink and Ari{\~n}o, {Arturo H. H.} and Christian B{\"o}lling and Pierre Bonnet and Lorenzo Cecchi and Ellwood, {Elizabeth R.} and Rui Figueira and Pierre-Yves Gagnier and Grace, {Olwen M} and Anton G{\"u}ntsch and Helen Hardy and Pieter Huybrechts and Roger Hyam and Alexis Joly and Kommineni, {Vamsi Krishna} and Isabel Larridon and Laurence Livermore and Lopes, {Ricardo Jorge} and Sofie Meeus and Miller, {Jeremy A.} and Kenzo Milleville and Renato Panda and Marc Pignal and Poelen, {Jorrit H.} and Blagoj Ristevski and Tim Robertson and Rufino, {Ana C} and Joaquim Santos and Maarten Schermer and Ben Scott and Seltmann, {Katja Chantre} and Heliana Teixeira and Maarten Trekels and Jitendra Gaikwad",

year = "2023",

month = nov,

day = "30",

doi = "10.3897/bdj.11.e109439",

language = "English",

volume = "11",

journal = "Biodiversity Data Journal",

issn = "1314-2828",

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number = "e109439",

}

Groom, Q, Dillen, M, Addink, W, Ariño, AHH, Bölling, C, Bonnet, P, Cecchi, L, Ellwood, ER, Figueira, R, Gagnier, P-Y, Grace, OM, Güntsch, A, Hardy, H, Huybrechts, P, Hyam, R, Joly, A, Kommineni, VK, Larridon, I, Livermore, L, Lopes, RJ, Meeus, S, Miller, JA, Milleville, K, Panda, R, Pignal, M, Poelen, JH, Ristevski, B, Robertson, T, Rufino, AC, Santos, J, Schermer, M, Scott, B, Seltmann, KC, Teixeira, H, Trekels, M & Gaikwad, J 2023, 'Envisaging a global infrastructure to exploit the potential of digitised collections', Biodiversity Data Journal, vol. 11, nr. e109439. https://doi.org/10.3897/bdj.11.e109439

TY - JOUR

T1 - Envisaging a global infrastructure to exploit the potential of digitised collections

AU - Groom, Quentin

AU - Dillen, Mathias

AU - Addink, Wouter

AU - Ariño, Arturo H. H.

AU - Bölling, Christian

AU - Bonnet, Pierre

AU - Cecchi, Lorenzo

AU - Ellwood, Elizabeth R.

AU - Figueira, Rui

AU - Gagnier, Pierre-Yves

AU - Grace, Olwen M

AU - Güntsch, Anton

AU - Hardy, Helen

AU - Huybrechts, Pieter

AU - Hyam, Roger

AU - Joly, Alexis

AU - Kommineni, Vamsi Krishna

AU - Larridon, Isabel

AU - Livermore, Laurence

AU - Lopes, Ricardo Jorge

AU - Meeus, Sofie

AU - Miller, Jeremy A.

AU - Milleville, Kenzo

AU - Panda, Renato

AU - Pignal, Marc

AU - Poelen, Jorrit H.

AU - Ristevski, Blagoj

AU - Robertson, Tim

AU - Rufino, Ana C

AU - Santos, Joaquim

AU - Schermer, Maarten

AU - Scott, Ben

AU - Seltmann, Katja Chantre

AU - Teixeira, Heliana

AU - Trekels, Maarten

AU - Gaikwad, Jitendra

PY - 2023/11/30

Y1 - 2023/11/30

N2 - 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.

AB - 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.

U2 - 10.3897/bdj.11.e109439

DO - 10.3897/bdj.11.e109439

M3 - A1: Web of Science-article

SN - 1314-2828

VL - 11

JO - Biodiversity Data Journal

JF - Biodiversity Data Journal

IS - e109439

ER -

Envisaging a global infrastructure to exploit the potential of digitised collections

Uittreksel

Thematische Lijst 2020

Technologisch

Toegang verkrijgen tot document

Vingerafdruk

Projecten

DiSSCo Vlaanderen (EVINBO)

Dit citeren