AR Discovery !The Challenges!

Christian Glahn

This is where I work!

I don’t really do augmented reality!

?

AugmentedReality

AugmentedVirtuality

MixedReality

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

DISCOVERY!Let’s talk about

and my business with it

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

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

Experience contexts!

Identity Location

TimeActivity

Relations

Experience

Zimmermann,  Lorenz  &  Oppermann,  2007  

Identity Location

TimeActivity

Relations

Experience

Location

Identity

Time

Activity

Relations

Experience

Location

Identity

Time

Activity

Relations

Experience

Location

Identity

Time

Activity

Relations

Experience

Location

Identity

Time

Activity

Relations

Experience

Relations

Location

Identity

Time

Activity

Experience

Discovery as !automatic context matching!

Specht,  2009  

The technical !discovery process!

SensingCollecting

Aggregating

Controlling

Presenting

Experience

Glahn,  2009  

The technical !discovery process!

SensingCollecting

Aggregating

Controlling

Presenting

Experience

What is out there to discover?!

CloudServices

Ambient ScreensThings

Business Intelligence

SensingCollecting

Mobile Apps

Sensor Networks

Browser or appprovided data

Challenges for discovery!

DataAggregation

Connectivity

Experience

Attention

DisruptionPrivacy

Challenges for discovery!

DataAggregation

Connectivity

Experience

Attention

DisruptionPrivacy

The character of these challenges chages depending on the focusand the scenario

Aggregating

Controlling

Presenting

CloudService

Ambient ScreensThings

Apps

Sensor Networks

CloudService

Addressing privacy and connectivity by focussing on data aggregation!

generic queriesmultiple channels h:p://ar-­‐discovery.wikia.com/wiki/AR_Discovery_Scenarios  

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

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 IDGeolocation

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

From data to discovery!

Aggregating

Controlling

Presenting

TaskService

DeviceSensors

LocationService

TaskMgr

LocationMgr

Context matching!

Identity

Location

Time

Activity

Relations

Task Focus

Location

Identity

Time

Activity

Relations

Location

Locatio

n

Identity

TimeActivity

Relations

Task

Relations

Location

Identity

Time

Activity

Location

Location

IdentityTime

Activity

Relations

Task

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

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

What are your discovery challenges?Where do you need more interoperability?

Christian Glahn

@phish108http://slidesha.re/phish108https://www.linkedin.com/in/cpglahn