Gapfill

Gapfill is a term used across several disciplines to describe a process or activity in which missing material is supplied to complete a text, dataset, genome, or physical surface. The common thread is restoring continuity by introducing suitable content or material where it is absent. Depending on the field, gapfill can refer to an instructional exercise, a data imputation method, a genome-finishing step, or a surface-treatment technique.

In education, a gap-fill exercise (often called a fill-in-the-blank task) presents a text or sentence with one or more blanks. Learners must supply the missing word or phrase. Variants include multiple-choice options, partial deletions, or cloze tests that measure vocabulary knowledge, syntax, and reading comprehension.

In data analysis, gap filling or imputation refers to methods for handling missing values in data sets or time series. Approaches range from simple (mean, median, forward/backward fill) to advanced (linear or nonlinear interpolation, k-nearest neighbors, regression imputation, multiple imputation). The aim is to preserve statistical power and reduce bias introduced by missing data.

In genomics, gap filling describes the process of closing gaps in genome assemblies between contigs. This often uses additional sequencing with longer reads, targeted PCR, or other strategies to produce a more complete genome sequence.

In manufacturing and materials science, gap filling can involve applying filler material to fill voids, joints, or surface imperfections, followed by curing or finishing processes to achieve a continuous, smooth surface. See also cloze test, data imputation, genome finishing.