Hokkaido University

Institute for Chemical Reaction Design and Discovery

Research Outline

I aim to extract information about chemical reaction network graphs contained in the collection of scientific papers and use it to analyze chemical reactions. Developing such tools and providing them to chemists will serve as a starting point to establish a growing cooperation framework between data scientists and chemists which can yield valuable insights into the global chemical research landscape for the chemists, and for the data scientist an inroads to understanding the research design process and needs of specialists.

Natural language processing is the traditional tool to extract this kind of information, but it is difficult to recruit the help of experts for the necessary annotation step that provides the labels computers can use to understand which parts of a text signifies what concept. Nevertheless, using the above-mentioned tools, I hope that the close collaboration with chemists at ICReDD will provide me with an opportunity to establish a framework of mutual benefit. In addition, the recently developed neural net-based tools promise to reduce the burden of annotation by being able to process the large amounts of data available in the ever-growing literature to extract characteristic chemical information automatically.

The Researcher’s Perspective

My PhD supervisor was Professor Hiroyuki Yoshikawa, who is an eminent figure in the field of General Design Theory. He always emphasized that scientific findings should be to the benefit of humankind and so he coined the term of the modern evil. Modern evils are particular design solutions that cause greater problems elsewhere, such as the production of cheap and labor-saving plastic straws that are serious pollutants for the environment. I would like to contribute to overcoming such modern evils by understanding the design process itself and then expanding that understanding in the view of the wider context.

Representative Research Achievements

• A framework for reviewing the results of automated conversion of structured organic synthesis procedures from the literature
  Kojiro Machi, Seiji Akiyama, Yuuya Nagata, and Masaharu Yoshioka, Digital Discovery, 2025, Vol. 4, No. 1, pp. 172-180
  DOI: 10.1039/d4dd00335g
• Overview and Discussion of the Competition on Legal Information Extraction/Entailment (COLIEE) 2023
  Juliano Rabelo, Randy Goebel, Mi-Young Kim, Yoshinobu Kano, Masaharu Yoshioka and Ken Satoh, The Review of Socionetwork Strategies, 2024, Vol. 18, No. 1, pp. 27-47
  DOI: 10.1007/s12626-023-00152-0
• OSPAR: A Corpus for Extraction of Organic Synthesis Procedures with Argument Roles
  Kojiro Machi, Seiji Akiyama, Yuuya Nagata, and Masaharu Yoshioka, Journal of chemical information and modeling, 2023, Vol. 63, No. 21, pp. 6619-6628
  DOI: 10.1021/acs.jcim.3c01449
• Framework for Automatic Information Extraction from Research Papers on Nanocrystal Devices
  Thaer M. Dieb, Masaharu Yoshioka, Shinjiroh Hara, and Marcus C. Newton, Beilstein Journal of Nanotechnology, 2015, Vol. 6, 1872-1882
  DOI: 10.3762/bjnano.6.190
• Physical Concept Ontology for the Knowledge Intensive Engineering Framework
  Masaharu Yoshioka, Yasushi Umeda, Hideaki Takeda, Yoshiki Shimomura, Yutaka Nomaguchi, Tetsuo Tomiyama, Advanced Engineering Informatics, 2004, Vol. 18, No. 2, 95-113
  DOI: 10.1016/j.aei.2004.09.004