Show HN: OpenTimes – Free travel times between U.S. Census geographies

39 comments

·March 17, 2025

Hi HN! Today I'm launching OpenTimes, a free database of roughly 150 billion pre-computed, point-to-point travel times between United States Census geographies. In addition to letting you visualize travel isochrones on the homepage, OpenTimes also lets you download massive amounts of travel time data for free and with no limits.

The primary goal here is to enable research and fill a gap I noticed in the open-source spatial ecosystem. Researchers (social scientists, economists, etc.) use large travel time matrices to quantify things like access to healthcare, but they often end up paying Google or Esri for the necessary data. By pre-calculating times between commonly-used research geographies (i.e. Census) and then making those times easily accessible via SQL, I hope to make large-scale accessibility research cheaper and simpler.

Some technical bits that may be of interest to HN folks:

- The entire OpenTimes backend is just static Parquet files on R2. There's no RDBMS or running service. The whole thing costs about $10/month to host and is free to serve.

- All travel times were calculated by pre-building the inputs (OSM, OSRM networks) and then distributing the compute over hundreds of GitHub Actions jobs.

- The query/SQL layer uses a setup I haven't seen before: a single DuckDB database file with views that point to static Parquet files via HTTP.

Finally, the driving times are optimistic since they don't (yet) account for traffic. This is something I hope to work on in the near future. Enjoy!

Visit

simonw

OK the way you're publishing the data with Parquet and making it accessible through DuckDB is spectacular.

Your README shows R and Python examples: https://github.com/dfsnow/opentimes?tab=readme-ov-file#using...

I got it working with the `duckdb` terminal tool like this:

  INSTALL httpfs;
  LOAD httpfs;
  ATTACH 'https://data.opentimes.org/databases/0.0.1.duckdb' AS opentimes;

  SELECT origin_id, destination_id, duration_sec
    FROM opentimes.public.times
    WHERE version = '0.0.1'
        AND mode = 'car'
        AND year = '2024'
        AND geography = 'tract'
        AND state = '17'
        AND origin_id LIKE '17031%' limit 10;

anitil

Lately duckdb is becoming a serious competitor for my use of datasette because it's eliminating a step for most of my workflows - converting csv to sqlite.

I've been thinking about how to swap it in as a backend for datasette (maybe as a plugin?) but it seems inherently riskier as it needs to at very least be able to read a folder to list all the csvs available for my usecase. If I could hook that up with its native s3 support I'd be unstoppable (at work)

simonw

I have a medium term ambition to make Datasette backends a plugin mechanism, and the two I am most excited about are DuckDB and PostgreSQL.

dfsnow

Thanks! I hadn't seen anyone do it this way before with a very large, partitioned dataset, but it works shockingly well as long as you're not trying to `SELECT *` the entire table. Props to the DuckDB folks.

Eventually I plan to add some thin R and Python wrapper packages around the DuckDB calls just to make it easier for researchers.

simonw

I blogged a few more notes here: https://simonwillison.net/2025/Mar/17/opentimes/

hatthew

Very cool! I love the interactive map, but have a couple UX suggestions:

I usually expect most features of a map to be zoom invariant, with the exception of level of detail. Having the colormap change is surprising, particularly that longer time buckets simply disappear as I zoom in. The two problems with this are that any time I zoom in or out I now have to double check the color key in case it's changed, and if I want to find a travel time for something far away I need to zoom in to find the destination and then back out to see the travel time. Perhaps you can let the user manually choose the colormap granularity/range, or find some way to have a colormap that works at all scales?

Second suggestion, related, is to display the travel time next to the geography ID in the bottom left corner. This would mitigate the issues with getting a good colormap, since I can then just hover over a geography to get its time anywhere that the colormap isn't sufficient.

dfsnow

These are great suggestions, thank you!

I played around with a single static colormap for all scales but couldn't find one that worked well/looked good. Perhaps I'll add a slider that lets you manually select the values of the legend.

The second suggestion is a no-brainer. I'll definitely get that added.

jonny_eh

Maybe it sticks to whatever colors are initially shown, and there's a button to "reset colors"?

c_moscardi

Amazing! GitHub actions to compute a giant skim matrix is an incredible hack.

I pretty regularly work with social science researchers who have a need for something like this... will keep it in mind. For a bit we thought of setting something like this up within the Census Bureau, in fact. I have some stories about routing engines from my time there...

jovas

I don't know.... It tells me that by car I can get someplace (that's geography close!) in < 15 min, but it's always taken me 20...

matthewfcarlson

I’ve been meaning to make a much more searchable realty system (think Redfin with significantly more filters) and can look across the whole country not just in a specific zip code. This would be awesome as you could compute travel time between points roughly then filter out results more accurately

zoklet-enjoyer

This map makes Des Moines, IA seem appealing.

WiggleGuy

This is super cool - I definitely have a lot to learn from this. I can probably use this for my project theretowhere.com

Kudos!

itissid

Travel time context in general could be useful for retrieval before ranking in searches like Yelp or Google maps like products for nearby events and places. My MVP use case is to configure a rerank based on commute "score".

For example there is just no way I'm going to commute from Brooklyn to Manhattan on a Monday night to eat out.

I live across the river from Manhattan and what I never understood was why yelp and Google maps upranks restaurants across the river on the other island even though it is highly improbable I would go there.

philipodonnell

Very cool! What did you use to make the ER diagram?

ctrlp

This is great! I've been thinking about building something like this for ages since I started using Smappen [0] for mapping travel times on road trips. Super useful way to travel if you're on an open-ended trip with flexibility.

[0] https://www.smappen.com/

ctrlp

Would be great to have multiple layers of times so you can plan out possible routes over days.

svcphr

How did you decide on routing engine? I’ve used Graphhopper in the past — is OSRM an improvement?

dfsnow

I actually tried a couple different engines before landing on OSRM. I started with R5 (since it can also do public transit) then switched to Valhalla.

The main limiting factor was speed. Basically all routing engines except for OSRM are too slow to compute continent-scale travel time matrices. For reference, it took Valhalla around a week to finish 3 billion point-to-point pairs. OSRM did the same calculation in about 2 hours.

I can't speak to Graphhopper since I haven't tried it. Maybe something to test in the future!

ynac

Well done, dfsnow!

* some islands seem hamstrung by the approach - see Vashon Island for example.

* curious what other dataset you might incorporate for managing next level of magnitude smaller trips - e.g. getting a quarter mile to the store for a frozen pizza at the seventh inning stretch.