Exploring Archival Recovery and Reuse Across Disciplines

Event Start Date: Thursday, July 15, 2021 - 7:00 pm

Event End Date: Thursday, July 15, 2021 - 9:00 pm

The Recovering and Reusing Archival Data (RRAD) lab is hosting a webinar at AERI!

Increasingly, recognition of the vast value of data lying dormant within archives and cultural collections has spurred various efforts toward data rescue, recovery, and reuse within and beyond cultural institutions. These initiatives include but are not limited to crowdsourcing (e.g. Evans 2007; Ridge, ed. 2014; Van Hyning, 2019), efforts to salvage politically vulnerable scientific data (Janz, 2018), and efforts to extract computationally amenable research data from within collections to support novel reuse across disciplines. Yet, despite the substantial and growing literature on data reuse and curation to support reuse (e.g., Borgman, 2016; Tenopir et al., 2015; Akmon et al., 2011; Palmer et al., 2011; Schöch, 2013; Poole & Garwood, 2020; Padilla et al., 2019), many stakeholders’ attitudes towards, and practices of archival data recovery and reuse remains uneven and siloed.

Christine Borgman’s monograph Big Data, Little Data, No Data (2015) broadly maps and deeply explores this complex, multidisciplinary landscape, arguing that “[t]hese are collective challenges, best addressed as knowledge infrastructure issues. The more stakeholders who come to the table, the deeper the conversation is likely to be” (273). Our Recovering and Reusing Archival Data (RRAD) Lab, formed at the University of Maryland iSchool in Spring 2021, studies the systems and communities of practice involved in cultures of recovery and reuse, to identify convergent, flexible, scalable solutions to these persistent and pressing issues.

In this panel, our team of early career archival and information scholars will ask of three interrelated projects exploring these collective challenges: Where are the gaps in collective efforts toward data reuse across a range of institutional contexts? What barriers confront different disciplinary communities? How can archival practice, structures, and norms support data reuse?

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