Skills Data Science Ethical Artifact Release Guidelines for CSCW

Ethical Artifact Release Guidelines for CSCW

v20260724
cscw-artifact-evaluation
Provides comprehensive guidelines for researchers packaging and releasing artifacts (data, code, instruments) derived from real communities in CSCW research. It emphasizes ethical constraints, de-identification techniques (such as quote search and join attacks), and best practices for protecting studied communities' privacy, ensuring responsible sharing.
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Overview

CSCW Artifact Packaging

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

Artifact Review-time form Post-acceptance form Governing constraint
Study instruments (guides, surveys) Anonymized in supplement Public archive Institution redaction only
Codebooks Anonymized in supplement Public archive Paraphrased exemplars only
Analysis code Anonymized archive Public repository + DOI archive Strip identity from history
Built systems / prototypes Screenshots/video + code where feasible Open source if maintainable Third-party assets, API keys
Trace datasets Aggregates or synthetic sample Aggregates; raw only if terms + ethics allow Platform ToS + re-identification risk
Interview/field data Never Almost never Consent 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.

Info
Category Data Science
Name cscw-artifact-evaluation
Version v20260724
Size 4.74KB
Updated At 2026-07-28
Language