CSCW Artifact Packaging

SkillDatabases & data

Use when packaging what stands behind a CSCW paper, systems, analysis pipelines, codebooks, instruments, datasets from real communities, for review-time scrutiny and post-acceptance release, where community-data ethics constrain release more than any badge checklist.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the CSCW Artifact Packaging skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in CSCW-Skills/skills/cscw-artifact-evaluation/SKILL.md and read by ahel’s review.

CSCW has no artifact-evaluation committee stamping badges; the "evaluators" of your artifacts are the reviewers deciding whether to trust your methods, and later the researchers and the studied communities themselves who encounter the released materials. That second audience is the venue's distinctive constraint: a CSCW artifact release is an act with consequences for real people who never signed your consent form.

Artifact classes and their release logic

ArtifactReview-time formPost-acceptance formGoverning constraint
Study instruments (guides, surveys)Anonymized in supplementPublic archiveInstitution redaction only
CodebooksAnonymized in supplementPublic archiveParaphrased exemplars only
Analysis codeAnonymized archivePublic repository + DOI archiveStrip identity from history
Built systems / prototypesScreenshots/video + code where feasibleOpen source if maintainableThird-party assets, API keys
Trace datasetsAggregates or synthetic sampleAggregates; raw only if terms + ethics allowPlatform ToS + re-identification risk
Interview/field dataNeverAlmost neverConsent scope is absolute

The community re-identification test

Before releasing any dataset or exemplar text derived from an online community, run the adversary exercise — assume a motivated actor (a journalist, a harasser, a platform admin, a community member with a grudge):

  1. Quote search: can any released text snippet be pasted into a search engine and land on the original post? If yes, paraphrase or drop it.
  2. Join attack: can released fields (timestamps + community + activity counts) be joined against public APIs or archives to recover usernames? Coarsen until the join fails.
  3. Small-population exposure: would identifying the community (not any member) expose it to raids, deplatforming, or press attention it has not chosen? If the community is small or marginalized, community-level anonymity is part of the ethical contract — name it only with its agreement.
  4. Future-context check: platforms change hands and moderation regimes change; would this release be safe under a hostile future owner of the platform's data?

Document the outcome in a short release memo; it becomes the honest core of the paper's data-availability statement (cscw-reproducibility).

Minimum viable released package

release/
├── README.md            # what claims each artifact supports; setup in ≤ 5 steps
├── LICENSE              # code license + data terms, which may differ
├── instruments/         # guides, surveys, recruitment text (redacted)
├── codebook/            # definitions + paraphrased exemplars
├── pipeline/            # collection + analysis code, config, environment spec
├── data/
│   ├── aggregates/      # tables behind each figure
│   └── synthetic/       # optional: structure-preserving fake sample
└── ETHICS.md            # consent scope, what is withheld and WHY, contact path

ETHICS.md is the CSCW-specific file: it tells reusers what they may not do (re-identify, recontact, join against other datasets) and why the withheld parts are withheld. A release that explains its own limits earns more trust than a maximal dump.

Review-time discipline

  • Everything reviewers can open must be anonymous — including git metadata, archive paths, and hosting URLs (use anonymized repository services, not a lab server whose domain resolves the institution).
  • Never put decision-critical evidence only in the artifact; the paper must stand if a reviewer opens nothing.
  • Keep the review package and the eventual public release as separate builds from one source tree; the deanonymization diff at acceptance should be mechanical (cscw-camera-ready).

Release audit

[Claims map]     each artifact → the claim it supports (no orphan uploads)
[Adversary test] quote-search / join / community-exposure / future-context: pass?
[Consent gate]   every released item inside consent + ToS scope? y/n
[Two builds]     review build anonymous; release build attributed; same tree? y/n
[ETHICS.md]      withholdings explained, reuse limits stated? y/n

No CSCW badge program existed at the 2026-07-08 check; if one appears in a future cycle, its checklist supplements — never replaces — the community-protection tests above.

Signals

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Sep 2026
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Item type
skill
Key
cscw-artifact-evaluation
Source
github.com/brycewang-stanford/awesome-journal-skills