{
    "proposals": [
        {
            "join_class": "category",
            "column": "startup_funding.City  Location",
            "kind": "external_candidate",
            "entry_id": null,
            "name": "GeoNames populated places (cities gazetteer)",
            "probable_url": "https://download.geonames.org/export/dump/",
            "license_expectation": "CC BY 4.0 (attribution required)",
            "join_story": "Matching each city name to a gazetteer would add population, country and coordinates to every funding row. Funding could then be read per head and by distance between hubs, rather than just by which city is biggest.",
            "teaches": "Whether a city's funding total reflects real startup intensity or just the size of the city."
        },
        {
            "join_class": "currency",
            "column": "startup_funding.Amount in USD",
            "kind": "external_candidate",
            "entry_id": null,
            "name": "US consumer price index for all urban consumers (FRED series CPIAUCSL)",
            "probable_url": "https://fred.stlouisfed.org/series/CPIAUCSL",
            "license_expectation": "Public domain (US Bureau of Labor Statistics data, redistributed by FRED)",
            "join_story": "Joining a monthly price index would let the dollar amounts be restated in constant money. Growth or decline in funding over the years could then be separated from plain inflation.",
            "teaches": "How much of the apparent change in funding over time is real and how much is just the dollar's changing value."
        }
    ]
}