UNLV Special Collections and Archives 2019 Archival Processing Metrics Survey Dataset

The University of Nevada, Las Vegas (UNLV) Libraries Special Collections and Archives is studying how archival processing metrics (including the hours of labor required to process each linear/cubic foot) are gathered and used by our colleagues. UNLV Special Collections and Archives conducted a survey with the objective to gather informal opinions and realities about processing metrics in an effort to understand the broader use of such metrics, to learn what data points are most essential, and to understand why more archival programs are not collecting and assessing processing metrics. The survey utilized the web-based tool Google Forms to gather responses from archival professionals across the country. The survey instrument included a total of 18 questions. Quantitative data were gathered from multiple choice (choose one) questions, “check all boxes that apply” questions, and questions rating the importance of data points on a three-point scale. Multiple choice questions included an “other” option to gather responses not included in the options provided.

Quantitative data were collected from ten required questions of the following types:

● Respondent repository type (1)

● Multiple choice: select one (5)

● Multiple choice: select all that apply (2)

● Numeric rating (2)

Qualitative data were gathered via eight optional free text questions that invited respondents to provide rationale or context for their responses to quantitative questions. The final optional free text question was open-ended to encourage respondents to express any ideas or perspectives that had not been solicited by the survey questions.

As of 2020, there are no profession-wide guidelines to support consistent archival processing data collection and reporting. Consequently, repositories must identify their own individual purposes for collecting metrics and determine the minimum number of data points that will serve those purposes. This survey and the resulting dataset may be used to further analyze the professional climate regarding the value and use of processing metrics.