The Multilingual Picture Database

Jon Andoni Duñabeitia; Ana Baciero; Kyriakos Antoniou; Mark Antoniou; Esra Ataman; Cristina Baus; Michal Ben-Shachar; Ozan Can Çağlar; Jan Chromý; Montserrat Comesaña; Maroš Filip; Dušica Filipović Đurđević; Margaret Gillon Dowens; Anna Hatzidaki; Jiří Januška; Zuraini Jusoh; Rama Kanj; Say Young Kim; Bilal Kırkıcı; Alina Leminen; Terje Lohndal; Ngee Thai Yap; Hanna Renvall; Jason Rothman; Phaedra Royle; Mikel Santesteban; Yamila Sevilla; Natalia Slioussar; Awel Vaughan-Evans; Zofia Wodniecka; Stefanie Wulff; Christos Pliatsikas

doi:10.1038/s41597-022-01552-7

The Multilingual Picture Database

Jon Andoni Duñabeitia
, Ana Baciero
, Kyriakos Antoniou
, Mark Antoniou
, Esra Ataman
, Cristina Baus
, Michal Ben-Shachar
, Ozan Can Çağlar
, Jan Chromý
, Montserrat Comesaña
, Maroš Filip
, Dušica Filipović Đurđević
, Margaret Gillon Dowens
, Anna Hatzidaki
, Jiří Januška
, Zuraini Jusoh
, Rama Kanj
, Say Young Kim
, Bilal Kırkıcı
, Alina Leminen

Terje Lohndal, Ngee Thai Yap, Hanna Renvall, Jason Rothman, Phaedra Royle, Mikel Santesteban, Yamila Sevilla, Natalia Slioussar, Awel Vaughan-Evans, Zofia Wodniecka, Stefanie Wulff, Christos Pliatsikas

The Gonda Multidisciplinary Brain Research Center

Antonio de Nebrija University
University of Tromsø – The Arctic University of Norway
Bournemouth University
Department of Rehabilitation Sciences
Cyprus University of Technology
Hellenic Open University
Western Sydney University
School of Psychological Sciences and Centre for Reading
Macquarie University
Department of Cognition
University of Barcelona
Department of Foreign Language Education
Middle East Technical University
Charles University
Research Unit in Human Cognition
University of Minho
Department of Linguistics
Department of Psychology
University of Belgrade
School of Education and English
University of Nottingham Ningbo China
School of Philosophy
National and Kapodistrian University of Athens
Department of Central European Studies
Malay Language Department
Universiti Putra Malaysia
School of Psychology and Clinical Language Sciences
University of Reading
Department of English Language and Literature
Hanyang University
C-unit
Laurea University of Applied Sciences
Department of Psychology and Logopedics
University of Helsinki
Department of Language and Literature
Norwegian University of Science and Technology
AcqVA Aurora Center
Department of English
Department of Neuroscience and Biomedical Engineering
Aalto University
Helsinki University Hospital
School of Speech-language Pathology and Audiology
University of Montreal
The Bilingual Mind Research Group
University of the Basque Country
Instituto de Lingüística
Universidad de Buenos Aires
School of Linguistics
Higher School of Economics
St. Petersburg State University
School of Human and Behavioural Sciences
Bangor University
Institute of Psychology
Jagiellonian University in Kraków
University of Florida

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

Abstract

The growing interdisciplinary research field of psycholinguistics is in constant need of new and up-to-date tools which will allow researchers to answer complex questions, but also expand on languages other than English, which dominates the field. One type of such tools are picture datasets which provide naming norms for everyday objects. However, existing databases tend to be small in terms of the number of items they include, and have also been normed in a limited number of languages, despite the recent boom in multilingualism research. In this paper we present the Multilingual Picture (Multipic) database, containing naming norms and familiarity scores for 500 coloured pictures, in thirty-two languages or language varieties from around the world. The data was validated with standard methods that have been used for existing picture datasets. This is the first dataset to provide naming norms, and translation equivalents, for such a variety of languages; as such, it will be of particular value to psycholinguists and other interested researchers. The dataset has been made freely available.

Original language	English
Article number	431
Journal	Scientific Data
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41597-022-01552-7
State	Published - Dec 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).

Funding

This research has been partially funded by the following grants: RED2018-102615-T and PID2021-126884NB-I00 from the Spanish Government and H2019/HUM-5705 from the Comunidad de Madrid granted to JAD; an Australian Research Council grant awarded to MA (DP190103067); a Ramon y Cajal research program awarded to CB (RYC2018-026174-I); an Israel Science Foundation grant awarded to MBS (1083/17); Funding by the Alexander von Humboldt Foundation awarded to JC; a Specifický vysokoškolský výzkum grant awarded to JC and JJ (260555); a Specifický vysokoškolský výzkum grant awarded to MF (260481); a National Research Fund awarded to SYK (NRF-2019R1G1A1100192); University of Helsinki funds awarded to AL; a Horizon 2020 grant awarded to NTY (H2020-MSCA-ITN-2017, 765556); an Academy of Finland grant awarded to HR (321460); an AcqVA Aurora Center of Excellence grant awarded to JR; an National Science Centre Poland grant awarded to ZW (2015/18/E/HS6/00428); a Spanish Government research grant awarded to MS (PGC2018-097970-B-I00); University of Montreal funds awarded to PR, and a Saint Petersburg State University grant awarded to NS (75288744, 121050600033-7); an award by the Cyprus Research and Innovation Foundation to KA (CULTURE/AWARD-YR/0421B/0005). The authors would like to thank the following colleagues for their support with various tasks, including translation of the materials, and data collection, screening, and preprocessing: Yolanda Acedo, Andrea Balázs, Ariane Brucher, Lihi Catz, Candela Dindurra, Ewa Haman, Marie Anna Hamanová, Máté Hegedűs, Boyoung Lee, Pantelis Lioumis, Viktória Balla, Magda Łuniewska, Yijin Lin, Gábor Marics, Khadidja Meftah, Ksenija Mišić, Marisol Murujosa, Helena Oliveira, Fanni Patay, Edurne Petrirena, Shen Qinfang, Michał Remiszewski, Rebeca Sanchez, Dana Suri-Barot and Agata Wolna.

Funders	Funder number
AcqVA Aurora Center of Excellence
University of Montreal
Alexander von Humboldt-Stiftung	260481, 260555
Helsingin Yliopisto
Horizon 2020 Framework Programme
Comunidad de Madrid
Australian Research Council	RYC2018-026174-I, DP190103067
Fonds National de la Recherche Luxembourg	NRF-2019R1G1A1100192
Academy of Finland	321460
Israel Science Foundation	1083/17
Narodowe Centrum Nauki	PGC2018-097970-B-I00, 2015/18/E/HS6/00428
Saint Petersburg State University	121050600033-7, 75288744
Horizon 2020	H2020-MSCA-ITN-2017, 765556
Research and Innovation Foundation	CULTURE/AWARD-YR/0421B/0005

Access to Document

10.1038/s41597-022-01552-7

Cite this

Duñabeitia, J. A., Baciero, A., Antoniou, K., Antoniou, M., Ataman, E., Baus, C., Ben-Shachar, M., Çağlar, O. C., Chromý, J., Comesaña, M., Filip, M., Đurđević, D. F., Dowens, M. G., Hatzidaki, A., Januška, J., Jusoh, Z., Kanj, R., Kim, S. Y., Kırkıcı, B., ... Pliatsikas, C. (2022). The Multilingual Picture Database. Scientific Data, 9(1), Article 431. https://doi.org/10.1038/s41597-022-01552-7

@article{b6c16b98313f48659ebe43c58b8ba504,

title = "The Multilingual Picture Database",

abstract = "The growing interdisciplinary research field of psycholinguistics is in constant need of new and up-to-date tools which will allow researchers to answer complex questions, but also expand on languages other than English, which dominates the field. One type of such tools are picture datasets which provide naming norms for everyday objects. However, existing databases tend to be small in terms of the number of items they include, and have also been normed in a limited number of languages, despite the recent boom in multilingualism research. In this paper we present the Multilingual Picture (Multipic) database, containing naming norms and familiarity scores for 500 coloured pictures, in thirty-two languages or language varieties from around the world. The data was validated with standard methods that have been used for existing picture datasets. This is the first dataset to provide naming norms, and translation equivalents, for such a variety of languages; as such, it will be of particular value to psycholinguists and other interested researchers. The dataset has been made freely available.",

author = "Du{\~n}abeitia, \{Jon Andoni\} and Ana Baciero and Kyriakos Antoniou and Mark Antoniou and Esra Ataman and Cristina Baus and Michal Ben-Shachar and {\c C}ağlar, \{Ozan Can\} and Jan Chrom{\'y} and Montserrat Comesa{\~n}a and Maro{\v s} Filip and {\D}ur{\d}evi{\'c}, \{Du{\v s}ica Filipovi{\'c}\} and Dowens, \{Margaret Gillon\} and Anna Hatzidaki and Ji{\v r}{\'i} Janu{\v s}ka and Zuraini Jusoh and Rama Kanj and Kim, \{Say Young\} and Bilal Kırkıcı and Alina Leminen and Terje Lohndal and Yap, \{Ngee Thai\} and Hanna Renvall and Jason Rothman and Phaedra Royle and Mikel Santesteban and Yamila Sevilla and Natalia Slioussar and Awel Vaughan-Evans and Zofia Wodniecka and Stefanie Wulff and Christos Pliatsikas",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41597-022-01552-7",

language = "אנגלית",

volume = "9",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Research",

number = "1",

}

Duñabeitia, JA, Baciero, A, Antoniou, K, Antoniou, M, Ataman, E, Baus, C, Ben-Shachar, M, Çağlar, OC, Chromý, J, Comesaña, M, Filip, M, Đurđević, DF, Dowens, MG, Hatzidaki, A, Januška, J, Jusoh, Z, Kanj, R, Kim, SY, Kırkıcı, B, Leminen, A, Lohndal, T, Yap, NT, Renvall, H, Rothman, J, Royle, P, Santesteban, M, Sevilla, Y, Slioussar, N, Vaughan-Evans, A, Wodniecka, Z, Wulff, S & Pliatsikas, C 2022, 'The Multilingual Picture Database', Scientific Data, vol. 9, no. 1, 431. https://doi.org/10.1038/s41597-022-01552-7

TY - JOUR

T1 - The Multilingual Picture Database

AU - Duñabeitia, Jon Andoni

AU - Baciero, Ana

AU - Antoniou, Kyriakos

AU - Antoniou, Mark

AU - Ataman, Esra

AU - Baus, Cristina

AU - Ben-Shachar, Michal

AU - Çağlar, Ozan Can

AU - Chromý, Jan

AU - Comesaña, Montserrat

AU - Filip, Maroš

AU - Đurđević, Dušica Filipović

AU - Dowens, Margaret Gillon

AU - Hatzidaki, Anna

AU - Januška, Jiří

AU - Jusoh, Zuraini

AU - Kanj, Rama

AU - Kim, Say Young

AU - Kırkıcı, Bilal

AU - Leminen, Alina

AU - Lohndal, Terje

AU - Yap, Ngee Thai

AU - Renvall, Hanna

AU - Rothman, Jason

AU - Royle, Phaedra

AU - Santesteban, Mikel

AU - Sevilla, Yamila

AU - Slioussar, Natalia

AU - Vaughan-Evans, Awel

AU - Wodniecka, Zofia

AU - Wulff, Stefanie

AU - Pliatsikas, Christos

PY - 2022/12

Y1 - 2022/12

N2 - The growing interdisciplinary research field of psycholinguistics is in constant need of new and up-to-date tools which will allow researchers to answer complex questions, but also expand on languages other than English, which dominates the field. One type of such tools are picture datasets which provide naming norms for everyday objects. However, existing databases tend to be small in terms of the number of items they include, and have also been normed in a limited number of languages, despite the recent boom in multilingualism research. In this paper we present the Multilingual Picture (Multipic) database, containing naming norms and familiarity scores for 500 coloured pictures, in thirty-two languages or language varieties from around the world. The data was validated with standard methods that have been used for existing picture datasets. This is the first dataset to provide naming norms, and translation equivalents, for such a variety of languages; as such, it will be of particular value to psycholinguists and other interested researchers. The dataset has been made freely available.

AB - The growing interdisciplinary research field of psycholinguistics is in constant need of new and up-to-date tools which will allow researchers to answer complex questions, but also expand on languages other than English, which dominates the field. One type of such tools are picture datasets which provide naming norms for everyday objects. However, existing databases tend to be small in terms of the number of items they include, and have also been normed in a limited number of languages, despite the recent boom in multilingualism research. In this paper we present the Multilingual Picture (Multipic) database, containing naming norms and familiarity scores for 500 coloured pictures, in thirty-two languages or language varieties from around the world. The data was validated with standard methods that have been used for existing picture datasets. This is the first dataset to provide naming norms, and translation equivalents, for such a variety of languages; as such, it will be of particular value to psycholinguists and other interested researchers. The dataset has been made freely available.

UR - https://www.scopus.com/pages/publications/85134625270

U2 - 10.1038/s41597-022-01552-7

DO - 10.1038/s41597-022-01552-7

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

C2 - 35864133

AN - SCOPUS:85134625270

SN - 2052-4463

VL - 9

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 431

ER -

The Multilingual Picture Database

Abstract

Bibliographical note

Funding

Access to Document

Other files and links

Fingerprint

Cite this