Quantifying the consistency of scientific databases

Abstract

Science is a social process with far-reaching impact on our modern society. In the recent years, for the first time we are able to scientifically study the science itself. This is enabled by massive amounts of data on scientific publications that is increasingly becoming available. The data is contained in several databases such as Web of Science or PubMed, maintained by various public and private entities. Unfortunately, these databases are not always consistent, which considerably hinders this study. Relying on the powerful framework of complex networks, we conduct a systematic analysis of the consistency among six major scientific databases. We found that identifying a single "best" database is far from easy. Nevertheless, our results indicate appreciable differences in mutual consistency of different databases, which we interpret as recipes for future bibliometric studies.

20 pages, 5 figures, 4 tables

References in corpus (8)

• Graph Evolution: Densification and Shrinking Diameters
• Principles of scientific research team formation and evolution
• Collective credit allocation in science
• An expert system for detecting automobile insurance fraud using social network analysis
• Growth and structure of Slovenia's scientific collaboration network
• Community structure and the evolution of interdisciplinarity in Slovenia's scientific collaboration network
• Network-based statistical comparison of citation topology of bibliographic databases
• Communities and Patterns of Scientific collaboration