Making sense of mankind’s scholarly knowledge and expertise: collecting, interlinking, and organizing what we know and different approaches to mapping (network) science

In this paper I discuss and compare different approaches to collecting, interlinking, organizing, and making sense of scholarly knowledge and expertise in a comprehensive and timely fashion. ‘Comprehensive’ refers to the need for collecting and interlinking multilingual, multidisciplinary records from multiple sources such as publications, patents, grants, and others to truly capture all relevant knowledge. By ‘timely’ I want to emphasize that there has to be a way to integrate the most recent—that is, today’s—publications with existing holdings of scholarly knowledge and expertise. I then discuss the advantages and limitations of using search engines to access, and text mining and data mining to help extract, meaning from mankind’s wisdom. Next I suggest the usage of semantic association networks as a viable and complementary alternative for interlinking and making sense of scholarly knowledge and expertise. The second part of the paper exemplifies and contrasts three approaches that can be used to delineate and make sense of scholarly knowledge. The first approach uses questionnaire data, the second uses citation data from a major digital library, and the third uses personal bibliography files. These approaches are exemplified by mapping the emerging research area of network science. A particular focus is the identification of major experts, papers, and research areas and geospatial locations in which network science research is conducted. The paper concludes with a summary and outlook.