Public sources in Estonia

OSM in Estonia• First data – 23.07.2006, by LA2 (Sweden)• Tartu city import – 2009 January• NGO formalized – 2009 August

– To rise money– To have legal body for parties

• Corine Land Cover import – 2009 October• Official administrative borders• NGO Project grant (~26.000 €): 2010-11

– Localized global map with own servers– Local language support– Combination of OSM data with OSM-incompatible data– Community development, mapping parties

Why import?

• Small population density– Estonia: size of Netherlands, population 1.3 M– Some cities not covered yet by volunteers– Some roads/areas are very rarely reached by mappers

• Opportunity– Public datasources are available, good IT level by state– State organization is not too large, – E.g. public WMS by National Land Board

• Our result– About 2/3 of Estonian OSM is currently imported

Possible Sources• Two technical types:

– Vector data– On-line services (WMS)

• State government– National Land Board– Ministeries

• Municipalities• State agencies

– E.g. Environmental, nature protection • Companies

Could be handlers of public data

Issues

• License – what licence?– Our data is in Internet, why don’t you just use it?

• Do not know difference between:– access openess – usage rights

• Hard to access state by private person– Official requests, permissions– Formal rules by state prefer legal entities

• Strange cases– We already gave our data to X company, we do not want to

mess with this again.

Issues 2

• Law of geospatial data– State tries to monopolize all geodata handling– Legal know-how needed to be involved in the

process• State official position– Must follow the rules. If no rules, cannot do

anything

Extra data

• We have got also permission to use:– Aerial imagery– DEM model data

• Where to put them?

Suggestions

• Socialize and network (without Internet)• Formal NGO is useful to speak with state• Import– Import as little as possible (but as much as

needed)– Where existing data has very little value, so it can

be discarded safely– New datasets with no existing data, e.g. buildings