<br/>In academia, a considerable proportion of data sharing and analysis is conducted using spreadsheets. In this talk, we will discuss the advantages that come with the implementation of FAIR (Findable, Accessible, Interoperable, and Re-usable) databases to structure and share interdisciplinary siloed data from across multiple research groups.<br/><br/>Implementing a database to structure siloed research data takes a large amount of time to gather the data as well as the metadata (spectra and conditions) necessary to ensure any computational modelling is trustworthy. Backdating previous experiments can be challenging. However, once in a database, the data is made usable by computers, allowing for the implementation of computational modelling. These models can be used to guide and speed up research. Finally, tools and user interfaces can be built on the database to increase data shareability and ease of use for researchers. In this talk we will discuss our experience setting up and using databases in academia and the challenges and benefits of doing so.

Why should I put my results into a database? Challenges and FAIR practices

Where thousands of chemistry professionals meet to share ideas and advance scientific and technical knowledge. Spring 2023 abstracts, posters, and presentations will launch at the end of March.

ACS Spring 2023

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