Data to knowledge in action: A longitudinal analysis of GenBank metadata

Area of Science:

• Science of science
• Research collaboration networks
• Knowledge diffusion studies

Background:

• Traditional studies focus on publication authorship for collaboration and knowledge diffusion.
• Research collaboration often begins during data production, preceding publication.
• The role of data production networks in knowledge diffusion remains underexplored.

Purpose of the Study:

• To investigate how collaboration in data production networks influences knowledge diffusion.
• To examine the relationship between data production networks and patent generation.
• To highlight the significance of data production in the science of science.

Main Methods:

• Utilized metadata from genetic sequence records in the National Institutes of Health's GenBank database.
• Constructed annual collaboration networks based on data production.
• Employed regression analysis to test hypotheses on network characteristics and patent output.

Main Results:

• Data production team size shows a positive correlation with the number of patents generated annually.
• Increased average connectivity (links) among actors in data production networks is associated with higher patent counts.
• Findings underscore the impact of early-stage research collaboration on downstream knowledge commercialization.

Conclusions:

• Data production collaboration is a significant driver of knowledge diffusion, as evidenced by patent activity.
• The structure and size of data production networks are critical factors influencing innovation.
• This research emphasizes the importance of considering data production in the science of science framework.