{"doi":"10.1371/journal.pgph.0004067","title":"Using internet-assisted geocoding of 1940 census addresses to reconstruct enumeration districts for use with redlining and longitudinal health datasets","abstract":"Many historical administrative documents, such as the 1940 census, have been digitized and thus could be merged with geographic data. Merged data could reveal social determinants of health, health and social policy milieu, life course events, and selection effects otherwise masked in longitudinal datasets. However, most exact boundaries of 1940 census enumeration districts have not yet been georeferenced. These exact boundaries could aid in analysis of redlining and other geographic and social contextual factors important for health outcomes today. Our objective is to locate and map a large set of 1940 enumeration districts. We use online resources and algorithmic solutions to locate and georeference unknown 1940 enumeration districts. We geocode addresses using the OpenCage API and construct \"virtual\" enumeration districts by using a convex hull algorithm on those geocoded addresses. We also merge in Home Owners' Loan Corporation (HOLC) redlining maps from the 1930s to demonstrate how 1940 enumeration districts could be used in future work to examine the association between historic redlining and current health. We geocode 7,228,656 1940 census addresses from the largest 191 US cities in 1940 that contained 84% of the 1940 US urban population from the Geographic Reference File and construct 34,472 virtual enumeration districts in areas that had HOLC redlining maps. 18,340 virtual enumeration districts were previously unmapped, covering cities containing an additional 40% of the 1940 US urban population. Where virtual enumeration districts match with previously mapped districts, 96.8% of paired districts share HOLC redlining categorization. Researchers can use algorithmic methods to quickly process, geocode, merge, and analyze large scale repositories of historical documents that provide important data on social determinants of health. These 1940 enumeration district maps could be used with studies such as the Health and Retirement Study, Panel Study for Income Dynamics, and Wisconsin Longitudinal Study.","journal":"PLOS Global Public Health","year":2025,"id":551186,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":22.178386323199504,"corpus_rank":9377,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7769,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":50.0,"fair_percentile":62.702537450321,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1439893,"name":"Michel Boudreaux","orcid":"0000-0002-3657-5178","position":1,"is_corresponding":false},{"id":1447347,"name":"Kellee White Whilby","orcid":null,"position":2,"is_corresponding":false},{"id":306790,"name":"Rozalina G. McCoy","orcid":"0000-0002-2289-3183","position":3,"is_corresponding":false},{"id":699057,"name":"Neil Jay Sehgal","orcid":"0000-0002-6326-1115","position":4,"is_corresponding":false},{"id":1295034,"name":"Shuo Jim Huang","orcid":"0000-0002-4474-463X","position":0,"is_corresponding":true}],"reference_count":54,"raw_metadata":null,"created_at":"2026-07-19T02:54:25.065895Z","pmid":"39813208","pmcid":"PMC11734980","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":61.1111,"fair_a":56.25,"fair_i":20.0,"fair_r":33.3333,"fair_zscore":0.6155,"fair_rationale":{"fair_score":50.0,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":61.11,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"https://github.com/sjhuang1/1940-Census-Enumeration-Districts","grounded":true,"rationale":"The identifier is a GitHub URL, not a persistent identifier scheme (DOI, Handle, or repository accession).","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"Our dataset of 1940 enumeration district shapefiles and code to construct the dataset are publicly available in a repository: https://github.com/sjhuang1/1940-Census-Enumeration-Districts","grounded":true,"rationale":"The named host is GitHub, which is not a curated data repository listed in re3data/FAIRsharing (e.g., GEO, Dryad, Zenodo). 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'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No licence is stated for the data; the CC-BY licence applies to the article only.","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. 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