The National Institutes of Health (NIH) BRAIN Initiative (https://braininitiative.nih.gov/) funds the development and application of innovative technologies to aid in understanding the human brain. In 2017, it introduced funding mechanisms to support: the development of data archives, standards and tools collaborative research teams studying brain circuit functions' underlying behavior Grants to support the latter required the creation of data science cores, which were tasked with ensuring that the FAIR principles were applied to the data that was collected. NIH created a consortium of the directors of the data science cores for each of the ten grants funded in 2017 and 2018. The purpose of the consortium was to promote collaboration, and the sharing of tools and resources. I am the only librarian among the data science core directors, and I am working - both within my project team and the consortium - to increase the focus on metadata and data discovery. Work is currently ongoing in two areas. The first area involves collaboration with a member of one of the project teams, who had developed a metadata collection tool to capture detailed experimental metadata. We are working together to generalize the existing data model in order to support experimental metadata from all participating labs, and to customize the web interface in order to facilitate efficient metadata collection for labs collecting different types of data. The second area involves exploring the use of a data catalog to improve the discovery of BRAIN Initiative data. This talk will discuss these projects as well as my experiences in integrating with the project team and working within the data science consortium.