Activity: Data Intake Card

Goal

Evaluate whether a health dataset is usable, ethical, documented, and appropriate for reproducible analysis. This activity is about judgment and documentation. No coding is required.

Approved Portals

Choose one dataset or indicator page from one of these portals:

• CDC/NCHS public-use survey data, such as NHANES or NHIS;
• WHO Global Health Observatory;
• BC Data Catalogue;
• Government of Canada Open Government Portal.

Each link goes to that source’s page in the Reference: Data Sources part of this book.

The NHANES Health Equity data spine may be used as the shared classroom example.

Student Template

Copy this template into your notes.

dataset_name: ""
publisher_org: ""
permalink_url: ""
date_accessed: "YYYY-MM-DD"
license_terms: ""
geography: ""
time_coverage: ""
data_level: ""   # microdata / aggregated indicator / unknown
file_format: ""  # CSV / RDS / XLSX / JSON / other
metadata_or_codebook: ""
variables_of_interest:
  - name: ""
    definition: ""
    unit: ""
    caveat: ""
known_limitations:
  - ""
privacy_security_notes: ""
stewardship_notes: ""
indigenous_data_relevance: "no / yes / unknown"
kt_framing_sentence: ""
how_to_cite: ""
ai_use_note: ""

Use unknown if you cannot confidently answer a field after checking the source documentation. Do not guess. Briefly state what you checked.

Completed Example

dataset_name: "NHANES Health Equity classroom dataset"
publisher_org: "CDC / National Center for Health Statistics"
permalink_url: "https://wwwn.cdc.gov/nchs/nhanes/"
date_accessed: "YYYY-MM-DD"
license_terms: "Public-use NHANES files; cite CDC/NCHS documentation"
geography: "United States"
time_coverage: "Multiple NHANES cycles represented in the prepared class file"
data_level: "Microdata-derived classroom dataset"
file_format: "CSV and RDS cached in examples/nhanes-equity/data/"
metadata_or_codebook: "CDC/NCHS NHANES documentation and case-study README"
variables_of_interest:
  - name: "BMI"
    definition: "Body mass index from NHANES body measures data"
    unit: "kg/m^2"
    caveat: "Use descriptively unless survey design and weights are handled correctly"
known_limitations:
  - "Prepared class dataset is for classroom analysis and should not be treated as a causal analysis"
  - "Population inference requires attention to NHANES survey design and weights"
privacy_security_notes: "Use public-use data responsibly, avoid small-cell claims, and do not upload row-level data to AI tools"
stewardship_notes: "State limitations plainly and avoid stigmatizing group comparisons"
indigenous_data_relevance: "unknown in the prepared class example; check source documentation for any project dataset"
kt_framing_sentence: "This dataset can help students practice describing health equity patterns while learning to state limits clearly"
how_to_cite: "Cite CDC/NCHS NHANES documentation and the course case-study README"
ai_use_note: "AI may help draft plain-language wording, but source documentation must be checked directly"

For how_to_cite, follow the course citation pattern: source organization, dataset name and cycle, publisher, URL, and access date. For example:

Centers for Disease Control and Prevention (CDC), National Center for Health Statistics. National Health and Nutrition Examination Survey (NHANES) 2017-2018 Documentation. Hyattsville, MD: U.S. Department of Health and Human Services. https://wwwn.cdc.gov/nchs/nhanes/ (accessed 2026-06-11).

Completion Checklist

To be marked complete, your card must include:

• stable source link or access date;
• publisher or steward;
• license or terms of use;
• geography and time coverage;
• data level and file format;
• documentation or codebook location;
• at least one documented variable definition;
• a 1-2 sentence note on how an AI tool could misrepresent or bias that variable, such as wrong category labels, outdated coding, or overgeneralization;
• one limitation or stewardship risk;
• one privacy or security note;
• Indigenous Data Sovereignty relevance marked as no, yes, or unknown;
• KT framing sentence;
• AI-use note.

Scoring Guide

Rating	Evidence
Complete	Source, publisher, terms, metadata, variable definition, limitation, stewardship note, KT framing, and AI-use note are present and grounded in documentation.
Needs work	Source documentation is missing, license terms are unclear, variable definitions are guessed, risks are absent, or AI-written text is not checked against official documentation.

Submission

Submit the completed card in Canvas under the Week 1 module as a required, unweighted Complete/Needs Work checkpoint. It carries no percentage weight and has no granular rubric. Its purpose is to identify setup, access, or workflow trouble early enough for the TA or instructor to help before later assignments build on it.

Submit only the completed card; no screenshot, reflection, or additional setup evidence is required. Starting in Week 2, keep a copy in your course repository as:

data-intake-card.md

Reproducibility Check

Before submitting, check:

• the link opens or the access date is recorded;
• the publisher and license are named;
• variable definitions come from documentation, not guesses;
• file format and data level are named;
• the AI-use note says what AI helped with and how the text was checked.