Metadata Lab is a research group led by Professor Jian Qin that studies a wide range of topics related to metadata with two focus areas: big metadata analytics and metadata modeling and linking.
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.
Pathways for new discovery
The projects employ a wide variety of methods and tools, which are often highly computational, sometimes at a very large scale. Research in both big metadata analytics and metadata modeling and linking creates pathways for the two to dive deeper in the networks of collaboration and knowledge diffusion and benefit each other’s pursuit for new discoveries and knowledge.
- Jian Qin presented her paper “Collaboration capacity: Measuring the impact of cyberinfrastructure-enabled collaboration networks,” co-authored with Jeff Hemsley and Sarah Bratt at the Science of Team Science (SCITS) 2018 Conference, Galveston, Texas, May 21-24, 2018.
- Sarah Bratt was selected as one of the five Science Production Function Society project at the Laboratory for Innovation and Society at Harvard (LISH)