Assessing large-scale digitization using Web analytics

Purpose: The purpose of this study is to assess the use of digital collections created via the large-scale digitization of archival collections. The large-scale digitization method specifically examined is the reuse of archival description from finding aids to create digital collections that consist mainly of compound digital objects, equivalent to a folder of items, minimally described at the aggregate level. This paper compares Web analytics data for two large-scale digital collections and one digital collection with rich, item-level description. Design/methodology/approach: This study analyzed one year of Web analytics for three digital collections. The main research question of this study is: Are digital collections of minimally described compound objects used less than digital collections of richly described single objects? Findings: This study found that the large-scale digital collections analyzed received less use than the traditional item-level collection, when examined at the item level. At the object level, the large-scale collections did not always receive less use than the traditional item-level collection. Research limitations/implications: This study is limited to three different digital collections from one institution. Web analytics also represent a limited interpretation of “use.” Practical implications: This study presents a method for other institutions to assess their own large-scale digitization efforts and contributes to the profession’s understanding of the impact of large-scale digitization. Originality/value: This paper is unique because it uses Web analytics to compare the use of large-scale digital collections to the use of traditional boutique digital collections.