We have observed an increased need for computational access and use of research data and publications across disciplines due to the recent rise of applied data science, machine learning (ML) and artificial intelligence (AI). In Chemistry, many databases of publications and structured data that are needed for ML and AI are behind paywalls and/or governed by restrictive term of use. Librarians, especially subject specialists in Chemistry, are developing a renewed fluency in identifying well-curated datasets, justifying collection fund repurposing, negotiating terms of use, facilitating access mechanism, and ensuring research output from such sources sharable. Subject specialists often need to work closely with copyright specialists, licensing specialists, and data librarians in their libraries to enable the computational use of our collection and to partner with database providers to make the sources more findable, accessible, interoperable, and reusable (FAIR) for our researchers. This presentation will first overview the availability and challenges of publications and well-curated datasets in Chemistry for computational access and use. Then, we will discuss how teams of librarians can renew our shared fluency in collection development and address the emerging computational needs of data and texts.

Renewed fluency in collection development: Computational access and use of texts and data

ACS Spring Meeting 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.