Beilstein ChemInfo Labs

Supporting community-led digital infrastructure and standards projects in chemistry.

InChI – Cooperation project on machine readability of chemical structures and reactions

 

In a cooperation with InChI Trust, we work on the generation and further development of the InChI - the International Chemical Identifier developed by IUPAC (International Union of Pure and Applied Chemistry) and the InChI Trust. The InChI Trust is a non-profit organization that supports the development and promotion of the InChI standard.

 

The Beilstein-Institut is directly supporting the InChI Trust with in-kind developer support to further extend the InChI. Our main contribution lies in the cheminformatics side of the project, i.e., the development of new algorithms and the further development of existing ones. Among other tasks, we are currently working on the recognition of organometallic structures. The development of the InChI documentation is also part of our work.

 

At the Beilstein-Institut, our aim is to integrate the InChI into the Beilstein Journals - this is pioneering work in the world of scientific publishing. For this purpose, the graphical structures submitted by the authors are analyzed and made machine-readable to convert them into data subject to FAIR data principles. The FAIR Principles describe data to which the criteria of findability, accessibility, interoperability, and reusability match. This allows computer systems to better access and interact with the data.

 

At the moment, the Beilstein Journals –  like all the all other chemistry journals – face the problem that chemical structures are stored as graphics or text and are not handled as chemical structures. This prevents any user experience based on the chemical properties of these structures. The goal is to create a semi-automated process to extract, convert and finally embed this information in future published articles in a machine-readable form and to possibly deliver this information to third parties services and repositories, e.g., PubChem, ChemSpider or Chemotion.

 

By embedding machine readable chemical information from chemical structures, reactions and associated metadata, our articles can be enriched by making their chemical information findable, accessible, interoperable and reusable (FAIR).