Subject of information entity is one of the fundamental concepts in the field of information science. Subject of any document represents its intellectual potential -- 'aboutness' of the document. Traditionally, subject (along with title and author) is the one of three major ways to access information, so subject metadata plays a central role in this process and the role is constantly growing. Previous research concluded that the larger bibliographic database is, the richer subject vocabularies and classification schemes are needed to support information discovery. Further, a high proportion of information objects are unretrievable without subject headings in metadata records. This exploratory study provides the analysis of the subject metadata in MARC 21 bibliographic records created in 2020; and develops understanding of the level and patterns of 'aboutness' representation in the MARC 21 bibliographic records. Study also examines how these records apply the recent RDA and MARC21 guidelines and features intended to support functionality in a Linked Data environment. Methods of Social Network Analysis were applied along with content analysis, to answer research questions of this study. Suggestions for future research, implications for education, and practical recommendations for library metadata creation and management are discussed.

Cultural heritage institutions, including galleries, libraries, museums, and archives are increasingly digitizing physical items and collecting born-digital items and making these resources available on the Web. Metadata plays a vital role in the discovery and management of these collections. Existing frameworks to identify and address deficiencies in metadata rely heavily on count and data-value based metrics that are calculated over aggregations of descriptive metadata. There has been little research into the use of traditional network analysis to investigate the connections between metadata records based on shared data values in metadata fields such as subject or creator. This study introduces metadata record graphs as a mechanism to generate network-based statistics to support analysis of metadata. These graphs are constructed with the metadata records as the nodes and shared metadata field values as the edges in the network. By analyzing metadata record graphs with algorithms and tools common to the field of network analysis, metadata managers can develop a new understanding of their metadata that is often impossible to generate from count and data-value based statistics alone. This study tested application of metadata record graphs to analysis of metadata collections of increasing size, complexity, and interconnectedness in a series of three related …