Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions.: Starting the Conversation on How We Could Get It Done

C. A. (Annemieke) Romein; Tobias Hodel; Femke Gordijn; Joris J. van Zundert; Alix Chagué; Milan van Lange; Helle Strandgaard Jensen; Andy Stauder; Jake Purcell; Melissa M. Terras; Pauline van den Heuvel; Carlijn Keijzer; Achim Rabus; Chantal Sitaram; Aakriti Bhatia; Katrien Depuydt; Mary Aderonke Afolabi-Adeolu; Anastasiia Anikina; Elisa Bastianello; Lukas Vincent Benzinger; Arno Bosse; David Brown; Ash Charlton; André Nilsson Dannevig; Klaas van Gelder; Sabine C.P.J. Go; Marcus J.C. Goh; Silvia Gstrein; Sewa Hasan; Stefan von der Heide; Maximilian Hindermann; Dorothee Huff; Ineke Huysman; Ali Idris; Liesbeth Keijzer; Simon Kemper; Sanne Koenders; Erika Kuijpers; Lisette Rønsig Larsen; Sven Lepa; Tommy O. Link; Annelies van Nispen; Joe Nockels; Laura M. van Noort; Joost Johannes Oosterhuis; Vivien Popken; María Estrella Puertollano; Joosep J. Puusaag; Ahmed Sheta; Lex Stoop; Ebba Strutzenbladh; Nicoline van der Sijs; Jan Paul van der Trouw; Barry Benaissa; Vladimir Vučković; Heleen Wilbrink; Sonia Weiss; David Joseph Wrisley; Riet Zweitstra

doi:10.5281/ZENODO.7267245

Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions. Starting the Conversation on How We Could Get It Done

C. A. (Annemieke) Romein, Tobias Hodel, Femke Gordijn, Joris J. van Zundert, Alix Chagué, Milan van Lange, Helle Strandgaard Jensen, Andy Stauder, Jake Purcell, Melissa M. Terras, Pauline van den Heuvel, Carlijn Keijzer, Achim Rabus, Chantal Sitaram, Aakriti Bhatia, Katrien Depuydt, Mary Aderonke Afolabi-Adeolu, Anastasiia Anikina, Elisa Bastianello, Lukas Vincent BenzingerArno Bosse, David Brown, Ash Charlton, André Nilsson Dannevig, Klaas van Gelder, Sabine C.P.J. Go, Marcus J.C. Goh, Silvia Gstrein, Sewa Hasan, Stefan von der Heide, Maximilian Hindermann, Dorothee Huff, Ineke Huysman, Ali Idris, Liesbeth Keijzer, Simon Kemper, Sanne Koenders, Erika Kuijpers, Lisette Rønsig Larsen, Sven Lepa, Tommy O. Link, Annelies van Nispen, Joe Nockels, Laura M. van Noort, Joost Johannes Oosterhuis, Vivien Popken, María Estrella Puertollano, Joosep J. Puusaag, Ahmed Sheta, Lex Stoop, Ebba Strutzenbladh, Nicoline van der Sijs, Jan Paul van der Trouw, Barry Benaissa, Vladimir Vučković, Heleen Wilbrink, Sonia Weiss, David Joseph Wrisley, Riet Zweitstra

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Professioneel

Samenvatting

This paper discusses best practices for sharing and reusing Ground Truth in Handwritten Text Recognition infrastructures, as well as ways to reference and acknowledge contributions to the creation and enrichment of data within these systems. We discuss how one can place Ground Truth data in a repository and, subsequently, inform others through HTR-United. Furthermore, we want to we want to suggest appropriate citation methods for HTR data, models, and contributions made by volunteers. Moreover, when using digitised sources (digital facsimiles), it becomes increasingly important to distinguish between the physical object and the digital collection. These topics all relate to the proper acknowledgement of labour put into digitising, transcribing, and sharing Ground Truth HTR data. This also points to broader issues surrounding the use of machine learning in archival and library contexts, and how the community should begin to acknowledge and record both contributions and data provenance.

Originele taal-2	Engels
Tijdschrift	Zenodo
Vroegere onlinedatum	30 nov. 2022
DOI's	https://doi.org/10.5281/ZENODO.7267245 https://doi.org/10.5281/ZENODO.7765903
Status	Gepubliceerd - 24 mrt. 2023

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10.5281/ZENODO.7267245Licentie: CC BY
10.5281/ZENODO.7765903

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Romein, C. A., Hodel, T., Gordijn, F., Zundert, J. J. V., Chagué, A., Lange, M. V., Jensen, H. S., Stauder, A., Purcell, J., Terras, M. M., Heuvel, P. V. D., Keijzer, C., Rabus, A., Sitaram, C., Bhatia, A., Depuydt, K., Afolabi-Adeolu, M. A., Anikina, A., Bastianello, E., ... Zweitstra, R. (2023). Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions. Starting the Conversation on How We Could Get It Done. Zenodo. https://doi.org/10.5281/ZENODO.7267245, https://doi.org/10.5281/ZENODO.7765903

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title = "Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions.: Starting the Conversation on How We Could Get It Done",

abstract = "This paper discusses best practices for sharing and reusing Ground Truth in Handwritten Text Recognition infrastructures, as well as ways to reference and acknowledge contributions to the creation and enrichment of data within these systems. We discuss how one can place Ground Truth data in a repository and, subsequently, inform others through HTR-United. Furthermore, we want to we want to suggest appropriate citation methods for HTR data, models, and contributions made by volunteers. Moreover, when using digitised sources (digital facsimiles), it becomes increasingly important to distinguish between the physical object and the digital collection. These topics all relate to the proper acknowledgement of labour put into digitising, transcribing, and sharing Ground Truth HTR data. This also points to broader issues surrounding the use of machine learning in archival and library contexts, and how the community should begin to acknowledge and record both contributions and data provenance.",

keywords = "Referencing, Sharing models, HTR, CRedIT",

author = "Romein, {C. A. (Annemieke)} and Tobias Hodel and Femke Gordijn and Zundert, {Joris J. van} and Alix Chagu{\'e} and Lange, {Milan van} and Jensen, {Helle Strandgaard} and Andy Stauder and Jake Purcell and Terras, {Melissa M.} and Heuvel, {Pauline van den} and Carlijn Keijzer and Achim Rabus and Chantal Sitaram and Aakriti Bhatia and Katrien Depuydt and Afolabi-Adeolu, {Mary Aderonke} and Anastasiia Anikina and Elisa Bastianello and Benzinger, {Lukas Vincent} and Arno Bosse and David Brown and Ash Charlton and Dannevig, {Andr{\'e} Nilsson} and Gelder, {Klaas van} and Go, {Sabine C.P.J.} and Goh, {Marcus J.C.} and Silvia Gstrein and Sewa Hasan and Heide, {Stefan von der} and Maximilian Hindermann and Dorothee Huff and Ineke Huysman and Ali Idris and Liesbeth Keijzer and Simon Kemper and Sanne Koenders and Erika Kuijpers and Larsen, {Lisette R{\o}nsig} and Sven Lepa and Link, {Tommy O.} and Nispen, {Annelies van} and Joe Nockels and Noort, {Laura M. van} and Oosterhuis, {Joost Johannes} and Vivien Popken and Puertollano, {Mar{\'i}a Estrella} and Puusaag, {Joosep J.} and Ahmed Sheta and Lex Stoop and Ebba Strutzenbladh and {van der Sijs}, Nicoline and {van der Trouw}, {Jan Paul} and Barry Benaissa and Vladimir Vu{\v c}kovi{\'c} and Heleen Wilbrink and Sonia Weiss and Wrisley, {David Joseph} and Riet Zweitstra",

year = "2023",

month = mar,

day = "24",

doi = "10.5281/ZENODO.7267245",

language = "English",

}

Romein, CA, Hodel, T, Gordijn, F , Zundert, JJV, Chagué, A, Lange, MV, Jensen, HS, Stauder, A, Purcell, J, Terras, MM, Heuvel, PVD, Keijzer, C, Rabus, A, Sitaram, C, Bhatia, A, Depuydt, K, Afolabi-Adeolu, MA, Anikina, A, Bastianello, E, Benzinger, LV, Bosse, A, Brown, D, Charlton, A, Dannevig, AN, Gelder, KV, Go, SCPJ, Goh, MJC, Gstrein, S, Hasan, S, Heide, SVD, Hindermann, M, Huff, D, Huysman, I, Idris, A, Keijzer, L, Kemper, S, Koenders, S, Kuijpers, E, Larsen, LR, Lepa, S, Link, TO, Nispen, AV, Nockels, J, Noort, LMV, Oosterhuis, JJ, Popken, V, Puertollano, ME, Puusaag, JJ, Sheta, A, Stoop, L, Strutzenbladh, E, van der Sijs, N, van der Trouw, JP, Benaissa, B, Vučković, V, Wilbrink, H, Weiss, S, Wrisley, DJ & Zweitstra, R 2023, 'Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions. Starting the Conversation on How We Could Get It Done', Zenodo. https://doi.org/10.5281/ZENODO.7267245, https://doi.org/10.5281/ZENODO.7765903

Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions. Starting the Conversation on How We Could Get It Done. / Romein, C. A. (Annemieke); Hodel, Tobias; Gordijn, Femke et al.
In: Zenodo, 24.03.2023.

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Professioneel

TY - JOUR

T1 - Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions.

T2 - Starting the Conversation on How We Could Get It Done

AU - Romein, C. A. (Annemieke)

AU - Hodel, Tobias

AU - Gordijn, Femke

AU - Zundert, Joris J. van

AU - Chagué, Alix

AU - Lange, Milan van

AU - Jensen, Helle Strandgaard

AU - Stauder, Andy

AU - Purcell, Jake

AU - Terras, Melissa M.

AU - Heuvel, Pauline van den

AU - Keijzer, Carlijn

AU - Rabus, Achim

AU - Sitaram, Chantal

AU - Bhatia, Aakriti

AU - Depuydt, Katrien

AU - Afolabi-Adeolu, Mary Aderonke

AU - Anikina, Anastasiia

AU - Bastianello, Elisa

AU - Benzinger, Lukas Vincent

AU - Bosse, Arno

AU - Brown, David

AU - Charlton, Ash

AU - Dannevig, André Nilsson

AU - Gelder, Klaas van

AU - Go, Sabine C.P.J.

AU - Goh, Marcus J.C.

AU - Gstrein, Silvia

AU - Hasan, Sewa

AU - Heide, Stefan von der

AU - Hindermann, Maximilian

AU - Huff, Dorothee

AU - Huysman, Ineke

AU - Idris, Ali

AU - Keijzer, Liesbeth

AU - Kemper, Simon

AU - Koenders, Sanne

AU - Kuijpers, Erika

AU - Larsen, Lisette Rønsig

AU - Lepa, Sven

AU - Link, Tommy O.

AU - Nispen, Annelies van

AU - Nockels, Joe

AU - Noort, Laura M. van

AU - Oosterhuis, Joost Johannes

AU - Popken, Vivien

AU - Puertollano, María Estrella

AU - Puusaag, Joosep J.

AU - Sheta, Ahmed

AU - Stoop, Lex

AU - Strutzenbladh, Ebba

AU - van der Sijs, Nicoline

AU - van der Trouw, Jan Paul

AU - Benaissa, Barry

AU - Vučković, Vladimir

AU - Wilbrink, Heleen

AU - Weiss, Sonia

AU - Wrisley, David Joseph

AU - Zweitstra, Riet

PY - 2023/3/24

Y1 - 2023/3/24

N2 - This paper discusses best practices for sharing and reusing Ground Truth in Handwritten Text Recognition infrastructures, as well as ways to reference and acknowledge contributions to the creation and enrichment of data within these systems. We discuss how one can place Ground Truth data in a repository and, subsequently, inform others through HTR-United. Furthermore, we want to we want to suggest appropriate citation methods for HTR data, models, and contributions made by volunteers. Moreover, when using digitised sources (digital facsimiles), it becomes increasingly important to distinguish between the physical object and the digital collection. These topics all relate to the proper acknowledgement of labour put into digitising, transcribing, and sharing Ground Truth HTR data. This also points to broader issues surrounding the use of machine learning in archival and library contexts, and how the community should begin to acknowledge and record both contributions and data provenance.

AB - This paper discusses best practices for sharing and reusing Ground Truth in Handwritten Text Recognition infrastructures, as well as ways to reference and acknowledge contributions to the creation and enrichment of data within these systems. We discuss how one can place Ground Truth data in a repository and, subsequently, inform others through HTR-United. Furthermore, we want to we want to suggest appropriate citation methods for HTR data, models, and contributions made by volunteers. Moreover, when using digitised sources (digital facsimiles), it becomes increasingly important to distinguish between the physical object and the digital collection. These topics all relate to the proper acknowledgement of labour put into digitising, transcribing, and sharing Ground Truth HTR data. This also points to broader issues surrounding the use of machine learning in archival and library contexts, and how the community should begin to acknowledge and record both contributions and data provenance.

KW - Referencing

KW - Sharing models

KW - HTR

KW - CRedIT

U2 - 10.5281/ZENODO.7267245

DO - 10.5281/ZENODO.7267245

M3 - Article

JO - Zenodo

JF - Zenodo

ER -

Romein CA, Hodel T, Gordijn F , Zundert JJV, Chagué A, Lange MV et al. Exploring Data Provenance in Handwritten Text Recognition Infrastructure: Sharing and Reusing Ground Truth Data, Referencing Models, and Acknowledging Contributions. Starting the Conversation on How We Could Get It Done. Zenodo. 2023 mrt. 24. Epub 2022 nov. 30. doi: 10.5281/ZENODO.7267245, 10.5281/ZENODO.7765903