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CURIOS MOBILE
Hai Nguyen
dot.rural Digital Economy Hub University of Aberdeen
Linked Data Exploitation for Tourist Mobile Apps in Rural Scotland
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THE CURIOS PROJECT• Facilitate historical societies in maintaining
the digital archive of their cultural heritage more sustainably and efficiently using open-source software (Drupal CMS) and open data standards (Linked Open Data).
• Use case: Outer Hebrides
• 45000 records
• Rich content: people, boats, historical events, places…
• Dedicated/active historical societies
• Project website: www.curiosproject.abdn.ac.uk
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CURIOS - THE CMS FOR LINKED DATA
• Open-sourced CMS: Drupal as a tool to directly exploit and maintain linked data
• The dataset and the software are loosely-coupling.
• Live demos:
• http://curios.abdn.ac.uk
• http://hebrideanconnections.com
• Code: https://github.com/curiosproject/curios
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CURIOS MOBILE• Motivation
• Reusability of Linked Data
• One data - Many views
• Semantic technologies can help in rural areas (connectivity, isolated contents)
• Aim: a mobile app for tourists in rural area.
• Challenges:
1. Connectivity problem
2. Huge archive (with noise)
3. Text generation from RDFs
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CURIOS SYSTEM OVERVIEWDatabase Clients
Triplestore
RESTful API
Content Management System
Read-only
Read-Write
Web servers
iOS app
Android app
CURIOS MOBILE
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APPROACHES TO TOURIST MOBILE APPS1. One-off download
• Rich-content
• Not up-to-date content
• Heavy download: 40-500 MB per application (excl. updates)
2. Pay as you go requests
• Needs reliable mobile connectivity
• Usually presented as a Web-app.
• CURIOS Mobile: pre-cached some data as seeds, growing the cache based on semantical relevance and user locations.
356 MB 459 MB
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A LINKED DATA SOLUTION
• Caching data based on
• Euclidean distance (location-based caching)
• Semantic relevance (semantics-based caching)
• User Preferences
• Help for Initial downloads
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LOCATION-BASED CACHING• Caching data based on Euclidean
distance
• Caching distance depends on signal distance
• Good for places where Internet connection is unreliable (“on/off” pattern)
• Bad for places where the whole area of interests does not have any signal at all (over-caching if caching distance is large)
• Only caching places. How about other record types (people, traditions, events, stories) ?
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SEMANTICS-BASED CACHING
• Caching data based on semantic relevance (object-property links)
• Allow all record types to be cached
• The more users browse, the more the cache grows
• If a record is linked to many other records, only cache the most interesting ones.
• Cached records can be used to push notifications while the user is moving in a no-connection area. (only GPS is required)
Red: viewed Dark blue: cached
Light blue: uncached
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AUTO-RECOMMEND CONTENTS
• Huge archive!!!
• 45000 individual records
• 33685 are people records
• 3001 places
• What to pick?
• Solutions:
• Locals’ suggestions: 325 records (64 places)
• How to automate this process?
• Build a Utility function based on level of significance/user preferences/locals’ suggestions.
• Level of significance: based on the links to and links from the record URI
• Also used to sorted records before caching on devices
1%
99%
Unsuggested recordsSuggested records
2%
98%
Unsuggested placesSuggested places
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TEXT GENERATION FROM RDF• Some records don’t have descriptions.
• How to generate an interesting story?
• User preferences (people/places/historical events etc)
• Type of records: people/place
• Proposed solution
• Directly generate text from RDF triples using properties and classes’ labels (Sun&Mellish, 2007)
• Only include “interesting” properties for special types (e.g., liveAt, childOf, etc.)
• Pros: Simple and flexible to data availability
• Cons: requires commitments from ontology designers
18%7%
75%
People Places Other
82%
18%
No descriptionHas description
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INITIAL RESULT
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SCREENSHOTS - ANDROID
Online map Offline map A croft
Prototype
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SCREENSHOTS - ANDROID
A record Links Pushed Notifications from cached records
Prototype
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SCREENSHOTS - IOS
Prototype
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CONCLUSION• CURIOS and CURIOS Mobile
• Linked data-based solutions for
• Unreliable connection problem in rural areas
• Auto-recommend interesting contents
• Generate texts directly from RDF