Harnessing Data Analytics for Enhanced Public Programming in Archives and Museums: A Scoping Review

Abstract

A notable lacuna exists in the extant research regarding the application of data analytics (DA) to augment public programming and cultivate robust connections between archives, museums, and their constituent communities. This scoping review aimed to address this gap by mapping the available literature at the intersection of data analytics, archives, and museums. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, a two-stage selection process was employed, utilising a comprehensive search strategy across four databases and seven specialised journals. This search identified 37 publications that met the pre-defined inclusion criteria. Findings revealed a growing interest in data-driven approaches, with nearly half of the reviewed studies explicitly linking data analytics to public programming. The review identified diverse data analytics techniques employed, ranging from traditional methods to cutting-edge artificial intelligence (AI) applications, and highlighted the various data sources utilised. Furthermore, this study examined the transformative potential of data analytics across several key dimensions of public programming, including access, archival management, user experience, public engagement, and research methodologies. The review noted ethical considerations, data quality issues, preservation challenges, and accessibility concerns associated with leveraging data analytics in archives and museums.

Keywords

• archives
• archival institution
• data analytics
• data analytics research
• museum
• public programming