Package index • fscontext

Observation

Observe digital resources and create reproducible filesystem snapshots.

scan_storage(): Observe a filesystem and construct a reproducible snapshot
snapshot_storage(): Create and persist an observational snapshot of a filesystem
save_scan(): Persist an observational snapshot to disk
read_snapshot(): Read and combine observational filesystem snapshots
subset_snapshot(): Subset observational filesystem Instantiations
observe_universe(): Construct a longitudinal observational universe
observe_wacz(): Observe a WACZ web archive
quick_signature(): Compute a fast operational signature for a file
quick_signature_text(): Compute a fast operational signature for text

Construct contextual groupings and enrich observations with structural context.

context_roots(): Extract normalized contextual roots
coverage_roots(): Evaluate contextual root coverage
derive_record_set(): Derive contextual Record Set membership
invert_contextual_grouping(): Invert contextual grouping mappings
add_snapshot_context(): Add contextual identifiers to snapshot observations
add_structural_groups(): Attach structural grouping heuristics to snapshot observations
construct_structural_paths(): Construct recursive contextual structural paths

Analyse observations before semantic interpretation.

summarise_duplicates() summarize_duplicates(): Summarise repeated and divergent filesystem observations
summarise_observed_activity() summarize_observed_activity(): Summarise observed activity from filesystem observations
detect_generated_artifacts(): Detect operationally generated or low-priority artifacts
exclude_operational_noise(): Exclude operational noise from analytical workflows
classify_operational_file_type(): Classify operational file types
derive_structural_groups(): Derive structural aggregation metadata from relative paths

Create contextual Record Sets and semantically enriched recordset_df objects.

snapshot_to_reconstruction_context(): Reconstruct a contextual observational Record Set from filesystem snapshots
snapshot_to_recordset_df(): Create a contextual Record Set dataset
wacz_to_recordset_df(): Create a Record Set dataset from a WACZ observation
recordset_df(): Create a semantically annotated Record Set

Prepare observations for human review and semantic enrichment.

prelabel(): Create a prelabelled vector
is.prelabelled(): Test if a vector is prelabelled
as_character(): Semantic character coercion
as_value_key(): Standardize contextual semantic mappings
invert_value_key(): Invert contextual semantic mappings
refine(): Refine semantic assertions through contextual matching
refine_by_rulebook(): Iteratively refine semantic assertions using a rulebook
compile_rulebook(): Compile a semantic refinement rulebook
coverage_rules_path(): Evaluate contextual rule coverage for structural paths

Reproducible snapshots used throughout the documentation.