AI in practice: a multilingual survey of 2025 BioHackathon participants

This dataset arises from a multilingual survey of AI use among participants and community members in the DBCLS BioHackathon 2025 in Japan. The questionnaire, offered in English, Japanese, and Thai, asked about how often respondents use AI tools, what they use them for, obstacles they encounter, institutional support, satisfaction, and concerns. Additional items captured role, institution type, work country, and other demographics, totaling 105 responses. The dataset includes both raw anonymized responses and a cleaned, standardized English-only version suitable for quantitative analysis, along with the full questionnaire, a data dictionary for cleaned dataset, and a translation lookup table. Free-text answers were screened and redacted to remove URLs, names, and other potentially identifiable information. Together, these materials provide a community-level view of AI practice in genomics, bioinformatics, software development, and related areas, and can support work on AI adoption, policy, and methods for analyzing survey data on AI use in science.

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Publication Details

Journal
Gigabyte
Published
2026-04-03
DOI
https://doi.org/10.46471/gigabyte.179
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

AI in practice: a multilingual survey of 2025 BioHackathon participants

Chatarin Wangsanuwat, Hikaru Gyoji, Pumipat Tongyoo, Nattawet Sriwichai et al.
Gigabyte
Artificial Intelligence in Healthcare and Education
article

AI in practice: a multilingual survey of 2025 BioHackathon participants

Chatarin Wangsanuwat, Hikaru Gyoji, Pumipat Tongyoo, Nattawet Sriwichai, Pitiporn Noisagul, Susumu Goto, Lucas Feriau, Yukiko Noda, David Steinberg
article en

Abstract

This dataset arises from a multilingual survey of AI use among participants and community members in the DBCLS BioHackathon 2025 in Japan. The questionnaire, offered in English, Japanese, and Thai, asked about how often respondents use AI tools, what they use them for, obstacles they encounter, institutional support, satisfaction, and concerns. Additional items captured role, institution type, work country, and other demographics, totaling 105 responses. The dataset includes both raw anonymized responses and a cleaned, standardized English-only version suitable for quantitative analysis, along with the full questionnaire, a data dictionary for cleaned dataset, and a translation lookup table. Free-text answers were screened and redacted to remove URLs, names, and other potentially identifiable information. Together, these materials provide a community-level view of AI practice in genomics, bioinformatics, software development, and related areas, and can support work on AI adoption, policy, and methods for analyzing survey data on AI use in science.

GigabyteVol. 2026
Kasetsart University (TH), Mahidol University (TH), PEN American Center (US), Campo Arqueologico de Mertola (PT), Research Organization of Information and Systems (JP), Chiang Mai University (TH)
Leibniz-Gemeinschaft
Openalex Percentile: Top 35%
Artificial Intelligence in Healthcare and Education
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AI in practice: a multilingual survey of 2025 BioHackathon participants — Chatarin Wangsanuwat, Hikaru Gyoji, et al. · Gigabyte (2026) | TGRS Research Map | TGRS