Organizing an in-class hackathon to correct pdf-to-text conversion errors of genomics & informatics 1.0

Sunho Kim, Royoung Kim, Hee Jo Nam, Ryeo Gyeong Kim, Enjin Ko, Han Su Kim, Jihye Shin, Daeun Cho, Yurhee Jin, Soyeon Bae, Ye Won Jo, San Ah Jeong, Yena Kim, Seoyeon Ahn, Bomi Jang, Jiheyon Seong, Yujin Lee, Si Eun Seo, Yujin Kim, Ha Jeong KimHyeji Kim, Hye Lynn Sung, Hyoyoung Lho, Jaywon Koo, Jion Chu, Juwon Lim, Youngju Kim, Kyungyeon Lee, Yuri Lim, Meongeun Kim, Seonjeong Hwang, Shinhye Han, Sohyeun Bae, Sua Kim, Suhyeon Yoo, Yeonjeong Seo, Yerim Shin, Yonsoo Kim, You Jung Ko, Jihee Baek, Hyejin Hyun, Hyemin Choi, Ji Hye Oh, Da Young Kim, Hyun Seok Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-col-umn biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

Original languageEnglish
Article numbere33
Pages (from-to)1-8
Number of pages8
JournalGenomics and Informatics
Issue number3
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020, Korea Genome Organization.


  • Biomedical text mining
  • Corpus
  • Text analytics


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