The document discusses augmented reality and discovery challenges. It describes Christian Glahn's work with augmented reality experiences across multiple devices and contexts. Some key challenges of discovery discussed include data aggregation, connectivity, privacy, and attention disruption. The document provides an example of using OpenStreetMap data for discovery and outlines next steps of launching an OSM point of interest service to better integrate and provide device-friendly access to categorized and linked data sources.

1. AR Discovery !
The Challenges!
Christian Glahn

2. This is where I work!

3. I don’t really do augmented reality!
?
Augmented
Reality
Augmented
Virtuality
Mixed
Reality

4. My real passion is about !
experiences in multi-device ecologies!

5. DISCOVERY!
Let’s talk about
and my business with it

6. How do we want to discover?!
• Not always more of the same
– If I just ate, then I don’t need more restaurants
– If I just spent 4h in a museum, then I need a café
more than another museum
– Etc.
• Create meaningful connections
– It I am on a business trip and its just before a
meeting, then I am not interested in finding a gym
• Follow rhythms
– If I always have dinner around 6PM, then I might
be interested in restaurants around that time
when not at home

7. Real-world example:!
Contextualized data access & enrichment!

8. Experience contexts!
Identity Location
TimeActivity
Relations
Experience
Zimmermann,
Lorenz
&
Oppermann,
2007

9. Identity Location
TimeActivity
Relations
Experience
Location
Identity
Time
Activity
Relations
Experience
Location
Identity
Time
Activity
Relations
Experience
Location
Identity
Time
Re
Experience
Location
Identity
Time
Activity
Relations
Experience
Relations
Location
Identi
Time
Activity
Experience
Discovery as !
automatic context matching!
Specht,
2009

10. The technical !
discovery process!
Sensing
Collecting
Aggregating
Controlling
Presenting
Experience
Glahn,
2009

11. The technical !
discovery process!
Sensing
Collecting
Aggregating
Controlling
Presenting
Experience

12. What is out there to discover?!
Cloud
Services
Ambient
Screens
Things
Business
Intelligence
Sensing
Collecting
Mobile Apps
Sensor
Networks
Browser or appprovided data

13. Challenges for discovery!
Data
Aggregation
Connectivity
Experience
Attention
DisruptionPrivacy

14. Challenges for discovery!
Data
Aggregation
Connectivity
Experience
Attention
DisruptionPrivacy
The character of these challenges
chages depending on the focus
and the scenario

15. Aggregating
Controlling
Presenting
Cloud
Service
Ambient
Screens
Things
Apps
Sensor
Networks
Cloud
Service
Addressing privacy and connectivity
by focussing on data aggregation!
generic queriesmultiple channels h:p://ar-­‐discovery.wikia.com/wiki/AR_Discovery_Scenarios

16. How to discover? An example
• OpenStreetMaps PoI/AoI
– Hierarchical Data (through geolocation data)
– Somewhat Structured Meta-Data
• ~80% of all tags used in the BCN area is “yes”
• Used on ~50% of the objects in BCN
– Plenty of linked data
• Wikipedia (710)
• Websites and URLs (533)
• Post Codes (3970)
• Emails (166) and phone numbers (412)
– Plenty of contextual data
• Language support
• Opening Hours
• Operator Information
• Accessibility

17. OSM linked data!
"GEOMETRY" MULTIPOLYGON
'osm_id' VARCHAR
'osm_way_id' VARCHAR
'name' VARCHAR
’type' VARCHAR
'aeroway' VARCHAR
'amenity' VARCHAR
'admin_level' VARCHAR
'barrier' VARCHAR
'boundary' VARCHAR
'building' VARCHAR
'craft' VARCHAR
'geological' VARCHAR
'historic' VARCHAR
'land_area' VARCHAR
'landuse' VARCHAR
’leisure' VARCHAR
'man_made' VARCHAR
'military' VARCHAR
'natural' VARCHAR
'office' VARCHAR
'place' VARCHAR
'shop' VARCHAR
'sport' VARCHAR
'tourism' VARCHAR
'other_tags' VARCHAR
multipolygons
Unique ID
Geolocation
Public Name
Category Tags
Linked Data
points
"GEOMETRY" MULTIPOLYGON
'osm_id' VARCHAR
'name' VARCHAR
'barrier' VARCHAR
'highway' VARCHAR
'man_made' VARCHAR
'is_in' VARCHAR
'place' VARCHAR
'address' VARCHAR
'ref' VARCHAR
'other_tags' VARCHAR

18. From data to discovery!
Aggregating
Controlling
Presenting
Task
Service
Device
Sensors
Location
Service
Task
Mgr
Location
Mgr

19. Context matching!
Identity
Location
Time
Activity
Relations
Task
Focus
Location
Identity
Time
Activity
Relations
Location
Location
Identity
Time
Activity
Relations
Task
Relations
Location
Identity
Time
Activity
Location
Location
IdentityTime
Activity
Relations
Task

20. My challenges for !
implementing discovery!
• Device friendly data
– Efficient data formats for
exchange and retrieval
• Identification of available data sources
• Integration of different data sources
– APIs
– Data-structures

21. Next steps!
We are about to launch a OSM POI service
• Consumer & device oriented
• Cleaned data
• Easier access to categorizations
• Easier access to linked data

22. What are your discovery challenges?
Where do you need more interoperability?
Christian Glahn
@phish108
http://slidesha.re/phish108
https://www.linkedin.com/in/cpglahn