For a while, I was interested in understanding what makes one pedestrian OSM way better than another. I wanted to know if there is some generic way to identify good walking routes from OSM data. I looked at Garmin and Strava heatmaps at first. Then I checked Strava segments and their proximity to points of interest such as rivers, ponds, and parks. Then I thought to look at my running pace along OSM ways to separate good and not-so-good walking routes. My idea was simple — a good walking route means a smooth running pace. There are fewer stops, less waiting at intersections, etc. Of course, my pace depends on many factors, such as how far I have to run to get to a certain place. So it cannot be a simple cutoff, but rather the distribution of paces along a given segment. This turned out to be a reasonably good approximation of how good or bad I perceive each route to be. I created this Kaggle dataset as an illustration. This relies on my personal GPX data, so it does not scale, but it captures the kind of local knowledge that I find hard to share in any other way.