Data categorization: understanding choices and outcomes

New citation-based, dynamic classification scheme promotes responsible research evaluation.

Being aware of the characteristics and limitations of how we categorize research publications is important. It influences the way we think about established and innovative research topics, the way we analyze research activity and performance, and even the way we set up organizations to do research.

In this latest report from the Institute for Scientific Information (ISI)™ we introduce a new and highly innovative approach to data aggregation based on trusted research data in the Web of Science™ citation network, developed in collaboration with the leading academic scientometrics team at the Centre for Science and Technology Studies (CWTS) at Leiden University in the Netherlands.

This flexible, bottom-up approach demonstrated in InCites ™ Citation Topics showcases a more accurate representation of microclusters, or specialties by providing a more uniform content and improved citation normalization. This allows for the promotion of good data management practice and has a positive impact on improving knowledge, competency and confidence while ensuring the responsible use of research metrics.