Big metadata analytics focuses on understanding scholarly communication processes by using metadata from data repositories and other databases as the source to investigate the structures and dynamics of collaboration and intellectual networks as well as the impact of such networks on scientific capacity and knowledge diffusion. Projects in this focus area include Discovering Collaboration Network Structures and Dynamics in Big Data and Cyberinfrastructure-Enabled Collaboration Networks.
Metadata modeling and linking is another research area that takes a different approach in examining big metadata residing in data repositories. By tracking and analyzing how research data in different repositories and/or different stages of a research lifecycle are related and linked, we develop models to represent domain knowledge networks for metadata applications. Projects in this focus area include metadata modeling for gravitational wave research data management, metadata portability, and relation typology.