User-driven Wiki websites have long been a leading resource for climbing beta: Sites like Mountain Project, SummitPost, and RockClimbing.com all have had their strengths when a climber needs information about a specific area, especially as print guidebooks have become outdated. As bouldering areas explode with hundreds of newly developed problems, the task of keeping an up-to-date guide becomes even more difficult.
Now Sundev Lohr, a Salt Lake-based climber, hopes to make his app and communal guidebook creating website, WikiBoulder, a go-to resource for boulderers around the world. He was inspired by Bart van Raaij’s 2002 7 + 8 guide to the boulders at Fountainbleau — he loved its “beauty and simplicity,” and built WikiBoulder to reflect that.
Lohr says WikiBoulder is a mashup of Mountain Project and 8a.nu (a “scorecard” site where climbers track the routes they’ve sent), but does a bit more. He’s built a Topo Creator, which users can utilize to draw topo maps to bouldering areas (but only on Flash-enabled devices, so no iPhone/iPad until Lohr finishes re-writing it for those). Instead of a static jpeg map, the Topo Creator makes a dynamic map that other users can build upon, drawing additional problems and areas. Users can add photos, topos and video, and when uploading photos of a boulder, a user can draw a line showing where a specific problem goes on that boulder.
Similar to 8a.nu, WikiBoulder users can track the problems they’ve sent with a button on their phone, keeping a running tab of their climbs — as long as those problems are in the guide. If they’re not, you’ll have to add the problem you climbed. The app also allows users to track their data on a weekly basis and compete with each other in the vein of 8a.nu or Strava.
WikiBoulder currently has around 1,000 problems and about 300 users, and guide data is most concentrated in Scandinavia and in Utah, where Lohr is based. Now in its second version, the app is free but Lohr plans to develop a premium version and add features, including recommended problems based on user data, a la Netflix.