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

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;

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.

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...

This is a fantastic project , and well done! How are you thinking about implementing traffic (it feels like that’s obviously essential for most practical use cases)?

Also just so I’m clear, is the shading corresponding to a time the represent mean travel time for the area, or the max travel time? E.g. if you pick Walking, and a neighborhood next to Central Park in New York City, even Even though parts of Central Park are directly adjacent to that neighborhood and should be a short travel time. The entirety of Central Park is shaded with a longer travel time, Does this mean I could theoretically get to the furthest point away from the selected area in Central Park in that travel time or is that more of like a mean travel time within that area and some travel times will be shorter or longer?

Looks cool. Please allow high max zoom levels, it’s hard to see individual street details on mobile.

This is an impressive project! Providing free access to such a massive dataset of pre-computed travel times could be a game-changer for researchers and policymakers who rely on spatial accessibility data but often face high costs with commercial providers.

The technical approach is also fascinating—using static Parquet files on R2 instead of a traditional database keeps costs low while maintaining accessibility via SQL and DuckDB. Offloading computation to GitHub Actions is a clever way to handle large-scale processing efficiently.

It'll be interesting to see how this evolves, especially with the potential addition of traffic-aware travel times. Great work!

This is a wonderful project. Seemingly simple on the surface. I'd love to see some notes of the frontend implementation. I see there's OpenFreeMap as presumably the base map, which uses MBTiles. Then custom geometry on top from Pmtiles, that I assume is generated for the project. How the colormapping is done I didn't find yet. Actually lots to unpack here.

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.

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/

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

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.

Only $10/mo? Where can we go to cover a month

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

Kudos!

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

Any plans on adding public transit?

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

The engineering behind it is very clever. Well done!

This map makes Des Moines, IA seem appealing.

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...

Does something like this exist for Europe?

Cool project! For me, seeing commutes time for 1 and 2 standard deviations would be useful too. Many times, people like to convey the lowest travel times, when I am more interested in the amount of time I need to budget to travel between two places to be on time 95% of the time.

awesome

well done

It seems that it ignores bridges over rivers making the travel time wildly inaccurate.

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