UDM (Unified Data Model) for chemical reactions – past, present and future

Jarosław Tomczak; Elena Herzog; Markus Fischer; Juergen Swienty-Busch; Frederik van den Broek; Gabrielle Whittick; Michael Kappler; Brian Jones; Gerd Blanke

doi:10.1515/pac-2021-3013

Published by De Gruyter June 9, 2022

UDM (Unified Data Model) for chemical reactions – past, present and future

Jarosław Tomczak , Elena Herzog , Markus Fischer , Juergen Swienty-Busch , Frederik van den Broek , Gabrielle Whittick , Michael Kappler , Brian Jones and Gerd Blanke

From the journal Pure and Applied Chemistry

https://doi.org/10.1515/pac-2021-3013

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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.

Keywords: AL/ML ready data; compound synthesis; ELN; JSON; open source data format; RDFile; reaction data format; reaction data integration; UDM; UDM exchange format; unified data model for chemical reactions; XML based schema

Article note:

A collection of invited papers on Cheminformatics: Data and Standards.

Corresponding author: Elena Herzog, Elsevier Information Systems GmbH, Frankfurt am Main, Germany, e-mail: e.herzog@elsevier.com

Funding source: BIOVIA

Award Identifier / Grant number: Unassigned

Funding source: BMS

Funding source: Elsevier

Funding source: GSK

Funding source: Novartis

Funding source: Roche

Funding source: Pistoia Alliance

Acknowledgments

The authors are grateful to the entire UDM team and community for stimulating discussions and their contributions. In particular, to Roman Affentranger from Novartis, who was the original UDM project champion at Roche, the role was taken over by Brian Jones at a later stage. Hans Kraut from InfoChem (currently DeepMatter) made a remarkable contribution by his expertise and a donation of a sample SPRESI dataset that was converted to UDM and included in its release. Similarly, Elsevier donated a small dataset from the Reaxys database. Finally, Becky Upton and Nick Lynch from the Pistoia Alliance facilitated the transfer of the UDM license from the Pistoia owned license to the MIT license and supported the transfer of the project to a broader community.

Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This work was supported by BIOVA, BMS, ELSEVIER, GSK, Novartis, Roche and Pistoia Alliance.
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Published Online: 2022-06-09

Published in Print: 2022-06-27

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