- Tour de table
- Earle
Anne WikiTravel OpenSpace See WikiMapia project
Two types of geographical wikis:
Objective geography: Focused on mapping the exact location of places. For example, OpenStreeMap project reaction to the fact that geographic data in US is owned by a private corporation. People use GPS to collaboratively create maps of cities. WikiMapia is a mashup between GoogleMaps and some wiki platform. Some people are using it for social activism to show the impact of certain development projects (ex: Olympics).
Subjective geography: .... neighbourhoods described from the perspective of the people who live there. Places that only have a meaning in the mind of certain people (ex: does central Canada REALLY exist? ;-)). Wikis are good for mapping subjective geography, because this kind of data doesn't find its way in standard geographical databases. Ex: subway maps are all subjective now, not spatially accurate.
Bridging the gap between wikis and semantic webs. Space (and time) is a a concept that is universal and generally agreed upon, so it's realistic to expect that people will be able to tag spatial and gegraphical oriented information with semantic tags, and to do it in a somewhat consisten way (ex: is-a-country, takes-place-is, etc...).
No esperanto of semantics. Need some contextualisation for humans to understand the semantic tags. For example, WikiTravel, OpenGuides and WikiEvents use RDF outputs to deal with space, time, etc.. It would be neat if those sites agreed on a taxonomoy and vocabulary to share this information.
Relying on the community to clean up the semantic tags and make them consistent is a more wikiway of approaching this problem of tags inconsistency.
In WikiTravel, they used the CIA Factbooks format but they should have let the community evolve the format... in retrospect Evan feels it was a mistake.
Geonames.org: They have taken public domain data from USGS (US Geog. Survey), and the UN. Human beings cleaned up the data in a massive collaborative way (it's not a wiki Evan thinks). Becoming a very good geographical DB.
WikiEvents first compiles data about venues. But after that, recognizing what events happen in what venue can be more machine oriented. Fans do a good job of figuring out when an artist plays in what venue, but they don't do a good job at capturing the venue. But if you put fan pages together with the venues in the DB, you can usually do a good job at that.
Alain suggests that you could rope your community into writing and maintaining small scraping tools for each venue. Instead of maintaining the information, the community maintains the scrapers. Mark points out that MinorThird (Carnegie Mellon) is a machine learning based scraping tool that could be used for that.
Evan suggests a session on data interchange format for spatial and time data to favour exchange between sites like WikiTravel, OpenGuides, WikiEvents. Mark and Earl agree.