The Reaction InChI (RInChI) extends the idea of the InChI, which provides a unique descriptor of molecular structures, towards reactions. Prototype versions of the RInChI have been available since 2011. The first official release (RInChI-V1.00), funded by the InChI Trust, is now available for download (http://www.inchi-trust.org/downloads/). This release defines the format and generates hashed representations (RInChIKeys) suitable for database and web operations. The RInChI provides a concise description of the key data in chemical processes, and facilitates the manipulation and analysis of reaction data.

The IUPAC International Chemical Identifier (InChI) provides a method to generate a unique text descriptor of molecular structures. Building on this work, we report a process to generate a unique text descriptor for reactions, RInChI. By carefully selecting the information that is included and by ordering the data carefully, different scientists studying the same reaction should produce the same RInChI. If differences arise, these are most likely the minor layers of the InChI, and so may be readily handled. RInChI provides a concise description of the key data in a chemical reaction, and will help enable the rapid searching and analysis of reaction databases.

TUCAN is a canonical serialization format that is independent of domain-specific concepts of structure and bonding. The atomic number is the only chemical feature that is used to derive the TUCAN format. Other than that, the format is solely based on the molecular topology. Validation is reported on a manually curated test set of molecules as well as a library of non-chemical graphs. The serialization procedure generates a canonical “tuple-style” output which is bidirectional, allowing the TUCAN string to serve as both identifier and descriptor. Use of the Python NetworkX graph library facilitated a compact and easily extensible implementation. Graphical Abstract

The UDM (Unified Data Model) is an open, extendable and freely available data format for the exchange of experimental information about compound synthesis and testing. The UDM had been initially developed in a collaborative project between Elsevier and Roche, where chemical reactions data from a variety of disparate data sources existing at Roche was consolidated and integrated into the Roche in-house version of the Reaxys database. Elsevier adapted the UDM model to its needs and finally donated its pre-4.0 release to the Pistoia Alliance for further development together with the five project founders (Elsevier, Roche, BIOVIA, GSK and Novartis, joined later by BMS), who contributed with funding and expertise to the Pistoia Alliance UDM project between 2017 and 2020. The latest UDM version 6.0 has been made freely available for the community under the MIT license in January 2021. The past, present, and future of the UDM exchange format are discussed in this article and factors that contribute to the successful adoption of the UDM format.

TUCAN is a canonicalization and serialization algorithm that is independent of domain-specific concepts of structure and bonding. Beyond the atomic number, all invariants used in the partitioning of a molecule are exclusively derived from the molecular topology and therefore make the algorithm also applicable to non-chemical graphs. In particular, the use of "fundamental" (chordless) cycles introduces an invariant of high discriminatory power which enables canonicalization of "difficult" graphs for which the popular Morgan algorithm fails. Extensive benchmarking is reported on a manually curated test set of molecules as well as a library of non-chemical graphs. In addition to the new canonicalization algorithm, the serialization procedure generates a unique "tuple-style" output which is fully bidirectional, allowing the TUCAN string to serve as both identifier and descriptor. Use of the Python NetworkX graph library facilitated a compact and easily extensible implementation.