How FAIR is MARC?: FAIR data principles and bibliographic data

Abstract

FAIR Data Principles provide a framework for considering how best to make data available in a way that is 1) findable, 2) accessible, 3) interoperable, and 4) reusable. Designed to be simple to understand and machine-actionable, FAIR principles support data use and reuse. This conceptual paper investigates the application of FAIR principles to bibliographic data through an examination of the current standard for encoding library records, MARC. To this end, this paper begins by describing the FAIR principles. It then looks to understand the MARC standard and applies the FAIR principles to the data affordances provided by the MARC encoding itself. In doing so, it probes the question of the extent to which MARC, as a standard, is FAIR. Ultimately, MARC is historically designed for machine-readability, not machine-actionability; although it is well suited to the description of bibliographic materials and is widely used, it does not adhere fully to any of the four FAIR principles. Even so, this examination suggests that FAIR principles could be useful in assessing specific MARC record datasets, particularly as bibliographic data is more widely shared and reused.