United Maps - Where 2.0 2009 and WhereCamp

United Maps United Maps: Maps on a human scale. • rofessional Maps for the Geoweb. P • nited Maps GmbH  2009 U 1

United Maps Maps leave the car. in-dash OEM PDA smartphones mobile phones PND in-car AM • ell phones know where we are. C Maps become personal.

Maps made for cars don‘t make too much sense for mobile humans. original picture: http://ﬂickr.com/photos/greenspartan/2548517094/ - by greenspartan

United Maps Vehicle Maps don‘t make too much sense on personal mobile devices Conventional maps focus on vehicle traffic and streets: » no detail on pedestrian level » no multimodal navigation » random house footprints » few relevant POIs Mobile devices have different usecases. Users expect better maps.

United Maps United Maps fills gaps in maps. » large scale = deep zoom » public transport » seamless multimodal navigation » pathes, walkways and trails » precise house footprints » exact addresses » comprehensive content Better maps = better apps.

United Maps Better Maps = Better Apps Yahoo! Maps UM-DE (pre-release 04.09) Maps make the difference.

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United Maps Better Maps. » cities: up to 50% density » rural: up to 300% more streets, pathways and trails » attributes conserved » fully navigable » professional topology • White lines are basedata sets - red lines is United Maps better maps with dramatically enhanced streets and pedestrian features.

United Maps Mobile multimodal navigation on a human scale » algorithmic merging and matching of vector data sets indoor » licenced data from Navteq hyperlocal local or Tele Atlas (no mashup) streets » addition and completion of municipial missing features and layers regional » perpetual, dynamic updates national » unique content continental

United Maps Conventional field research and processing is expensive Conventional field research requires reasonable perpetual effort and resources. In 2007, Navteq alone spent $336m for map updates. 2006: 275$m 2005: 236$m 2004: 197$m Turner, A. and Forrest, B., (2008) Where 2.0 - The state of the Geospatial Web. page 6. http://cachefly.oreilly.com/radar/research/ Where2.0_excerpt.pdf

United Maps We use smart software instead of driving roads. Primary maps from Navteq or Tele Atlas are matched, merged and extended with supplemental data. The result are truely pedestrian maps for mobile usecases in an unseen map quality. Highly detailed, hyperlocal maps.

United Maps Crowd Mapping produces results OpenStreetMap quickly generates maps for populated areas. Great Idea! » professional quality? » routable? » comprehensive feature sets? » commercial products? » coverage? » precision? » reliability? » Hype?

United Maps How we do it: Algorithmic Conflation UM licences vector data from market What UM doesn‘t do: leaders and deploys a proprietary » layering > original topology is algorithm ... expanded, nodes and vertices are » to automatically match vector data added sets, geometries and attributes » photogrammetry > pixel images » with a precision of 95% correct aren‘t vectorized: we licence original positive matches resulting in ... and secondary vector data » a fully navigable topological » field research > we don‘t do field network based on primary data checks Original primary data is left untouched. Nodes are expanded to attach new, previously missing pathways, conserving all attributes.

United Maps primary data + cadastral data • ATKIS is a set of official german cadastre data that is conflated with the street network data from Navteq or Tele Atlas. Every country has cadastre data. Quality and/or availability varies.

primary + cadastre = United Maps United Maps • Two vector data sets are conflated into a single, more precise and comprehensive dataset. All attributes are conserved, the street networks becomes denser and remains fully navigable. A wealth of additional metadata is added.

United Maps Anyone can do that? The U.S. has a centralized, public domain dataset maintained by the US Census Bureau. TIGER (Topologically Integrated Geographic Encoding and Referencing), the equivalent of 57.000 topographical maps is “out of date, idiosyncratic and mostly incompatible“*. But at least there is something. *) „Getting there“. The science of driving directions. Nick Paumgarten. April 24, 2006; The New Yorker - http://tinyurl.com/czw3e9

United Maps Technology + Workflow The EU has neither centralized nor free data but thousands of authorities and agencies. European federalism, cultural and language barriers and completely heterogenous data makes mapping a bit trickier. We do maps since 30 years.

United Maps Rollout » DE ready in 2Q09 » 200 major European cities » Trials for U.S. and Asia running

United Maps Founders United Maps has a seasoned Founder-Management Team who combine and bring to the company more than 30 years of relevant industry experience. • Andreas Wiedmann – CEO » 20 years CEO/CFO in media and publishing » CEO of Germany‘s market-leading cartographic publisher CartoTravel (ADAC) • Stefan Knecht – CIO » 18 years in publishing, media and technologies » international product development, program management and sales • Carsten Recknagel – COO » 14 years in GIS and cartography » CTO at CartoTravel

United Maps Where United Maps comes from United Maps‘ staff produced european • We closely work with a german and worldwide maps for more than 30 university on academic projects and years. currently employ 15 experts at 2 locations in Munich and Eisenach, Some of us made Carto Travel, Germany. formerly Germany‘s mapping market leader: cartography, GIS, editorial processing and licencing is our • The first product, a hyperlocal and profession. fully navigable vector map of Germany will be released as UM-DE in April 2009. » Feb 2008: founded » Sep 2008: (seed-)funded » Nov 2008: started operations

much more United Maps

United Maps Contact United Maps GmbH Stefan Knecht – CIO Agnes-Pockels-Bogen 1 80992 München +49 89 4521 393 0 info@unitedmaps.net http://blog.unitedmaps.net See Slideshare for more!

United Maps Automatic Conflation Results Rural • A primary dataset is algorithmically conflated and hence merged with a secondary dataset. • For practical reasons and sequential processing, this is done by tiling an area into 5x5 km segments. • UM-DE consists of 15k technical tiles. primary dataset | secondary dataset | UM automated match

United Maps Automatic Conflation Results Rural • primary dataset | secondary dataset | UM automated match

United Maps Automatic Conflation Results Suburban • In rural areas, an up to 300% gain in additional roads and pedestrian pathes is achieved. • In sub-/urban areas, the enhancement varies up to 50% depending on the timeliness of primary and secondary data. • Red is the fully automatically matched vectors. • Blue is defined as the primary base vector set primary dataset | secondary dataset | UM automated match

United Maps Automatic Conflation Results Suburban • After a completely automated first run, the majority of points and lines are positively matched: corresponding geometry is met. • Despite its 95% precision, the current release of the algorithm still produces artefacts that need to be processed in a second run. primary dataset | secondary dataset | UM automated match | positive 1st run | QA 2nd run

United Maps Automatic Conflation Results Urban primary dataset | secondary dataset | UM automated match

United Maps Automatic Conflation Results Urban primary dataset | secondary dataset | UM automated match | positive 1st run | QA 2nd run

United Maps - Where 2.0 2009 and WhereCamp

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