Classify operational file types

classify_operational_file_type() assigns observed files to broad operational categories such as code, data, documents, generated website files, and other artefacts.

The current implementation provides an "r_development" profile derived from software development, reproducible research, and analytical repository workflows.

The broader objective of operational classification is to introduce an intermediate semantic layer between filesystem observations and contextual reconstruction.

Usage

classify_operational_file_type(
  x,
  extension = "extension",
  profile = "r_development"
)

Arguments

x

A data.frame or tibble containing observed files.

extension

Character scalar identifying the column that contains file extensions. Defaults to "extension".

profile

Character scalar defining the classification profile. Currently only "r_development" is implemented.

Value

A character vector of operational file type labels.

Possible values for the "r_development" profile include:

code

R source files.

markdown

Markdown, R Markdown, or Quarto files.

workspace

R workspace or serialized R objects.

data

Tabular spreadsheet or delimited data files.

artifact

Image artefacts.

document

PDF or word-processing documents.

website_generated

Generated website assets.

other

Files not matched by the selected profile.

Details

Classify observed resources into operational categories that support contextual reconstruction and Record Set derivation.

In many digital collections, archives, and research environments, files participate in operational roles that cannot be inferred from directory structure alone. Examples include source materials, preservation masters, derivative artefacts, metadata records, rights documentation, analytical outputs, and publication-ready resources.

Operational classification provides a lightweight mechanism for assigning observed resources to such workflow-oriented categories before higher-level contextualisation, Record Set construction, or semantic stabilisation takes place.

Classification is currently based on extension patterns and workflow-specific heuristics. The function does not inspect file contents, infer authoritative media types, determine archival significance, or perform provenance reasoning.

The resulting classifications should therefore be interpreted as operational hypotheses that support exploration, reconstruction, and contextualisation workflows rather than authoritative documentary assertions.

Future classification profiles may support archival, audiovisual, heritage, research-data, and Records in Contexts workflows, where operational roles provide an important bridge between low-level filesystem observations and higher-level documentary interpretation.

Examples

toy_files <- tibble::tibble(
  extension = c("R", "qmd", "csv", "png", "woff2")
)

classify_operational_file_type(
  toy_files,
  profile = "r_development"
)
#> [1] "code"              "markdown"          "data"             
#> [4] "artifact"          "website_generated"