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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "DCC" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'DCC: Data Cleaning Center for Survey and Assessment Data'
version: 1.2.1
doi: 10.32614/CRAN.package.DCC
abstract: Rule-driven, auditable cleaning of survey and assessment response data,
  implementing the WeianData Detect-Execute-Report workflow. Provides a multi-format,
  multi-encoding input layer (CSV, 'Excel', 'SPSS', 'Stata', 'SAS', Parquet, JSON),
  the dcc_data container with a provenance chain, level-0 structural diagnostics,
  five built-in response-quality detectors (missing items, straight-lining, response
  time, trap items, score anomalies), a declarative YAML rule engine, an execution
  engine with a cell-level audit log, answer-key scoring, multi-form to master item
  bank mapping, a normalized report model rendered as bilingual staff workbooks and
  HTML, complete statistical bundles, and versioned machine JSON/JSONL with findings-to-changes
  reconciliation, cell-level lineage tracing, and manifest-based one-command reproduction.
  Includes a protected bilingual strict project workbook and matching JSON contract
  with cell-addressed validation, non-mutating preflight, preview-first execution,
  and localized staff guidance. All formally supported input backends install with
  the package; PDF is optional rather than a fixed report output.
authors:
- family-names: Ma
  given-names: Kunxiang
  email: makunxiang@weiandata.com
repository: https://weiandata.r-universe.dev
repository-code: https://github.com/weiandata/DCC
commit: 26c7b668670610cc4b95606cc015b0445c14993a
url: https://github.com/weiandata/DCC
date-released: '2026-09-02'
contact:
- family-names: Ma
  given-names: Kunxiang
  email: makunxiang@weiandata.com