Transparency & Spatial Data (aaag-transparency-and-data)
SkillDocs & knowledgeUse when handling data documentation, sharing, and spatial-data ethics for an Annals of the American Association of Geographers manuscript, provenance (sources, projections, processing), reproducibility, and geoprivacy / human-subjects protection. Prepares documentation; it does not over-state a verification gate the policy does not impose.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Then ask your AI: use the Transparency & Spatial Data (aaag-transparency-and-data) skill
What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in Annals-of-the-American-Association-of-Geographers-Skills/skills/aaag-transparency-and-data/SKILL.md and read by ahel’s review.
The Annals (Taylor & Francis, for the AAG) follows publisher and disciplinary norms for data availability and research integrity rather than (as at some journals) a mandatory, editor-run replication check before publication. The right posture is: document spatial-data provenance thoroughly, share what you ethically can, and protect location privacy. Confirm the current data- availability / sharing policy on the Taylor & Francis journal page (检索于 2026-06;以官网为准).
When to trigger
- Preparing data documentation, a data-availability statement, or supplementary materials
- Deciding what spatial data can be shared given geoprivacy, IRB, license, or proprietary limits
- Documenting qualitative or restricted location data so claims remain credible
- A reviewer asked how others could verify or reproduce the spatial analysis
Spatial-data provenance (the geography-specific core)
Document enough that another geographer could locate, re-project, and rebuild the dataset:
- Sources & licenses for every layer (census, satellite, OSM, administrative, field-collected), with access dates and terms.
- Projection / CRS and any re-projection; areal units and how they were defined or aggregated.
- Processing chain — classification, geocoding, spatial joins, resampling, filtering — as a logged, ordered pipeline, not "cleaned in GIS."
- Temporal alignment — vintages of layers and how they were harmonized.
Geoprivacy & human subjects (overrides sharing)
- Do not publish precise locations of identifiable individuals/households; use geographic masking (aggregation, jittering, areal reporting) and state the method.
- IRB/consent for interviews, fieldwork, and participatory mapping; protect informant and site identity.
- Sensitive sites (sacred, endangered-species, conflict) may require deliberate spatial coarsening — say so.
Reproducibility (good practice even without a pre-publication gate)
- Master script regenerates every table, figure, and map from raw/constructed data.
- README/codebook: provenance, projections, construction steps, and how to reproduce each exhibit.
- Seeds set for stochastic steps; software/package versions pinned (
renv.lock/requirements.txt). - Restricted data: a data-availability statement explaining what is shared, what is not and why, and an access path; provide synthetic/masked data so code can run where feasible.
Transparency posture by data type (geography-specific)
Because the Annals spans four areas, the availability expectation lands differently on different evidence. This grid keeps the posture honest; confirm mechanics against the current T&F policy.
| Data type | Typically shareable | Restricted | Provenance to document |
|---|---|---|---|
| Public geospatial (census, OSM) | data + code | none | source, vintage, CRS, join keys |
| Satellite / DEM | processing code + IDs | bulk imagery (host link instead) | sensor, dates, correction, resolution |
| Field GPS of people/sites | masked/aggregated data | exact coordinates | masking method, IRB, consent |
| Interviews / ethnography | coding scheme | identifiable transcripts/locations | anonymization, composite-disclosure note |
| Proprietary/licensed layers | code + access path | the layer itself | license terms, how to obtain |
Checklist
- Every layer's source, license, access date, and CRS documented
- Processing pipeline logged (classification/geocoding/joins/resampling)
- Geoprivacy handled — masking method stated for identifiable locations
- IRB/consent documented for human-subjects and field/participatory work
- Master script + README + seeds + pinned versions (where quantitative)
- Data-availability statement drafted; access path / synthetic data for restricted layers
- Current T&F data policy confirmed (do not assert a gate it does not impose)
Anti-patterns
- "Data cleaned in GIS" with no provenance, CRS, or processing log
- Publishing exact coordinates of vulnerable people or sensitive sites
- Claiming open data that license or geoprivacy will not permit
- Asserting an editor-verified replication mandate the policy does not state
- Un-seeded, unpinned code that "works on my machine"
Output format
【Provenance】sources + licenses + CRS + processing log documented? [Y/N]
【Geoprivacy】masking/aggregation for identifiable locations? [Y/N/NA]
【Human subjects】IRB/consent handled? [Y/N/NA]
【Reproducibility】master script + README + seeds + versions? [Y/N]
【Data-availability statement】shared / restricted (why) / access path / synthetic?
【Policy check】current T&F data policy confirmed? [Y/N/待核实]
【Next】aaag-review-process
Supplementary resources
../../resources/external_tools.md— reproducibility tooling, repositories, and geomasking options../../resources/official-source-map.md— T&F data-availability and AAG ethics references
Signals
- GitHub stars
- 1k
- Forks
- 155
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
aaag-transparency-and-data- Source
- github.com/brycewang-stanford/awesome-journal-skills
github.com/brycewang-stanford/awesome-journal-skills
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