Big metadata exists in bibliographic, indexing, and research data repositories and is an important part of the cyberinfrastructure supporting information and data management, discovery, sharing, and reuse. Its other role – as a data source for data/text mining and knowledge discovery – is less visible compared to the one for management, discovery, sharing, and reuse of information and data. Research in big metadata analytics has been dynamic and encompasses a wide range of topics, methods, and applications that have been labeled as bibliometrics, citation analysis, scientometrics, and informetrics. New family members of big metadata such as Linked Data are also gaining momentum. 

As big metadata is pivotal for the data-intensive research, learning, health, and business, there has been a lack of discussion on what big metadata analytics encompasses, what theoretical, methodological, and computational issues need to be addressed, and how it might be applied to support decision making at team, organizational, and even national levels. Although using bibliographic metadata as the data source in research has a long history, using big metadata in data repositories is still a new area waiting to be explored. The purpose of this workshop is to bring current researchers who have used or are using big metadata in their projects to share their challenges, methods, datasets, and findings, through which we hope to produce a research agenda for a new research area –  big metadata analytics.