Skills Data Science Guidelines for CSCW Supplementary Materials

Guidelines for CSCW Supplementary Materials

v20260724
cscw-supplementary
This guide details the best practices for preparing and submitting supplementary materials for CSCW submissions. It clarifies the difference between main papers, appendices, and separate files, emphasizing that anything needed to *trust* the method belongs here. Crucially, it provides deep guidelines on data anonymization, metadata scrubbing, and version control for review rounds.
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Overview

CSCW Supplementary Materials

Supplements at CSCW serve a journal-style review: they let reviewers verify the methods section without bloating a paper already policed by the contribution-vs- length standard. Because Revise and Resubmit sends the paper back to the same reviewers, the supplement is also a versioned record — round-two reviewers can and do compare it against round one.

What goes where

Material Main paper Appendix Separate supplement file
Method summary + key instrument excerpts
Full interview guide / survey instrument ✓ if long
Codebook (definitions + paraphrased exemplars)
Trace-pipeline ledger and attrition table summary code as archive
Analysis scripts ✓ (archive)
Additional tables/robustness checks
Consent forms / recruitment text
Raw transcripts, identifiable data never never never

Decision rule: anything a reviewer needs to evaluate a claim belongs in the paper or appendix; anything a reviewer needs to trust the method belongs in the supplement; anything participants did not consent to share belongs nowhere.

Anonymization is deeper than the PDF

The supplement is the classic identity leak at this venue, because it aggregates exactly the artifacts teams forget to scrub:

  • Documents: consent forms carry institution letterhead and IRB protocol numbers tied to a university; recruitment emails carry names. Redact, and check PDF/Office metadata (author fields, tracked changes, comments).
  • Code archives: repository paths (/home/username/), git history, package lockfiles with private registry URLs, notebook execution metadata. Export clean archives, never a cloned .git.
  • Data extracts: usernames, community names, timestamps precise enough to reverse-search, URL slugs. For small communities, the combination of quoted text and date can identify the community even with names removed.
  • Media: screenshots showing account handles, browser profiles, or platform locale details.

Mechanical sweep before upload:

# strings that must not appear anywhere in the supplement tree
grep -ri -l -E "(surname|firstname|university-name|lab-name|grant-no|protocol-no)" supplement/
# metadata in every PDF
for f in supplement/**/*.pdf; do exiftool "$f" | grep -iE "author|creator|company"; done
# accidental git history or user paths in code archives
find supplement/ -name ".git" -o -path "*Users*" -o -path "*home*" | head

Adapt the string list per project; run it on the packed archive, since packing often reintroduces metadata.

R&R versioning discipline

  • Keep every round's supplement frozen; name uploads by round (supplement-r2.zip), never overwrite.
  • If the response letter cites the supplement ("the revised codebook now includes ..."), the cited file must exist under that name — reviewers check.
  • New supplementary material added at R&R must be flagged in the change summary; silently appearing files read as scope creep or, worse, as identity leaks made under revision pressure.

Pre-upload checklist

[Inventory]   every supplement file listed in the paper or response letter? y/n
[Consent]     each artifact within participants' consent scope? y/n
[Sweep]       mechanical anonymity sweep run on the packed archive? y/n
[Size/format] platform limits confirmed on the live submission system? 待核实 per
              regime (PCS legacy vs Manuscript Central) — do not assume
[Round label] files named by round; prior rounds preserved? y/n

Platform-specific size and format caps were not verifiable at 2026-07-08; check the live Manuscript Central instructions for the rolling pathway before packaging.

Info
Category Data Science
Name cscw-supplementary
Version v20260724
Size 4.04KB
Updated At 2026-07-28
Language