Monthly archives: October 2017
Ray Boucher, Stephen Heller, Alan McNaught, Chem. Int., 2017, 29 https://doi.org/10.1515/ci-2017-0316 Read the article
The International Union of Pure and Applied Chemistry (IUPAC) held a symposium on Research Data, Big Data, and Chemistry at the 2017 World Chemistry Congress in São Paulo. The Union published a special issue of Chemistry International (CI) to accompany the symposium (https://doi.org/10.1515/ci-2017-0300). We have been asked to develop a special issue on a similar topic for Pure and Applied Chemistry (PAC), the scientific and technical journal of the Union. The CI issue focused on the historical context around research data in chemistry, and also looked at current issues and advocacy around research data. In the PAC issue, we also seek to include more specific examples of research data sharing, successes of big data analyses in chemistry and related areas, ethical considerations in applications of big data technologies in the sciences, as well as education and outreach. The target article length is 8-15 published pages, approximately 4000-7500 words. We aim to receive manuscripts before the end of the year, for publication in the first half to 2018. PAC offers ahead-of-print publication, so articles will be posted as accepted. In addition, PAC offers hybrid Open Access options for authors who desire immediate OA. Authors are also allowed to self-archive the final published manuscript 12 months after publication.
We would welcome your submission to this special issue. If you have any questions, please let us know. We can provide additional details, including instructions on submission. All manuscripts will be subject to the usual PAC peer review process. Also, if you have any colleagues who might be interested in submitting a publication in this area, please let us know.
Thanks for your interest,
Leah McEwen, Cornell University
David Martinsen, David Martinsen Consulting
Stephen R Heller, Igor Pletnev, Stephen Stein and Dmitrii Tchekhovskoi, J. Cheminformatics, 2015, 7:23 Read the article
Warr, W.A., J. Comput. Aided Mol. Des., 2015, 29: 681. https://doi.org/10.1007/s10822-015-9854-3 Read the article