Estimating herbarium specimen digitization rates: Accounting for human experience

Abstract

Premise: Herbaria are invaluable sources for understanding the natural world, and in recent years there has been a concerted effort to digitize these collections. To organize such efforts, a method for estimating the necessary labor is desired. This work analyzes digitization productivity reports of 105 participants from eight herbaria, deriving generalized labor estimates that account for human experience.

Methods and results: Individuals' rates of digitization were grouped based on cumulative time performing each task and then used to estimate a series of generalized labor projection models. In most cases, productivity was shown to improve with experience, suggesting longer technician retention can reduce labor requirements by 20%.

Conclusions: Using student labor is a common tactic for digitization efforts, and the resulting outreach exposes future professionals to natural history collections. However, overcoming the learning curve should be considered when estimating the labor necessary to digitize a collection.

Keywords: biodiversity data; digitization rates; herbaria; natural history collections.

Figure 1

The average technician skeletal databasing rate (specimen/minute) as a function of cumulative hours performing skeletal databasing. The mean rate at each two‐hour bin is indicated by the blue point, and the number of data points informing the mean is annotated over each point. The range of values at each bin are indicated by vertical bars.

Figure 2

The average technician imaging rate (specimen/minute) as a function of cumulative hours imaging. The mean rate at each two‐hour bin is indicated by the blue point, and the number of data points informing the mean is annotated over each point. The range of values at each bin are indicated by vertical bars.

Figure 3

The average technician barcode application rate (specimen/minute) as a polynomial function of cumulative hours applying barcodes. The mean rate at each two‐hour bin is indicated by the blue point, and the number of data points informing the mean is annotated over each point. The range of values at each bin are indicated by vertical bars.