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www.insight-centre.org
SLUA: TOWARDS SEMANTIC LINKING OF USERS WITH
ACTIONS IN CROWDSOURCING
Umair ul Hassan, Sean O’Riain, Edward Curry
INSIGHT Centre for Data Analytics
National University of Ireland, Galway
1st International Workshop on Crowdsourcing the Semantic Web,
CrowdSem’13, Sydney, Australia
www.insight-centre.org
Paper Overview
• Motivation
– Multiple crowdsourcing platforms
– Lack of tools for finding tasks
– Querying across platforms for skills and knowledge of workers
• Problem
– Enabling interoperability across crowdsourcing platforms
– Support users in their search for crowd tasks
– Enable task and user matching services
• Contribution
– An ontology for describing crowd sourced tasks and users with regard to
human capabilities, actions and rewards
2
www.insight-centre.org
Agenda
• Motivation
– Crowdsourcing Landscape
– Semantic Heterogeneity
• Challenges
• SLUA Ontology
• Examples
• Summary
3
www.insight-centre.org
Crowdsourcing Landscape
4
www.insight-centre.org
Crowdsourcing Landscape
5
www.insight-centre.org
Heterogeneity
Tasks Human Actions
Required
Capabilities
Rewards
Wikipedia Create Content
Edit Content
Moderate Content
Write text
Include references
Highlight mistakes
Domain Knowledge
Writing
Research
Quora Ask Questions
Answer Questions
Write text Domain Knowledge Reputation
Amazon
Mechanical
Turk
Micro Tasks Transcribe,
Translate,
Categorize, etc.
Various Capabilities Money
TaskRabbit Physical Tasks Collect Item
Deliver Item
Shop Item, etc.
Various Capabilities Money
Microtask Form Filling
Scan Correction
Data Verification
Play games Online gaming Fun
6
www.insight-centre.org
Challenges
• Difficult to interoperate across crowdsourcing
systems and platforms
– e.g. searching for appropriate workers on
StackExchange for Wiki editing tasks
• Variations of data semantics across systems and
platforms
– Different APIs used by current marketplaces
• Existing Taxonomies
– Categorize crowdsourcing platforms instead of tasks
– Do not consider human factors such as actions,
capabilities, motivation.
7
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Heterogeneous Crowds
• Multiple requesters, tasks, workers, platform
8
Cyber Physical
Social System
Tasks Workers
Collaborative
Data Curation
Tasks Workers
Task Management
Middleware
www.insight-centre.org
Proposed Model
• An common model for describing tasks in
crowdsourcing (CS) is required
• Methodology
– Enumerate similar terms on crowdsourcing platforms
– Define the main concept in each group of terms
– Compare with existing ontologies
– Define core classes and their relationships
– Extend core classes with subclasses
– Create example instances
9
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Crowdsourcing Terminology
• Terms used for similar concepts in
crowdsourcing platforms
10
Amazon
Mechanical
Turk
Mobileworks Shorttask CrowdFlower
Task HIT Task ShortTask Microtask
User Worker
Requester
Worker
Developer
Solver
Seeker
Contributor
Customer
Capability Qualification Filter
Reward Payment Payment Reward Payment
www.insight-centre.org
Model Requirements
• Required concepts
– Task: A unit of work to be performed by people in the
crowd
– Action: The cognitive or psychomotor activity that
leads towards the completion of a task
– User: The human participant, commonly described as
“worker” in crowdsourcing marketplaces.
– Capability: The human ability, knowledge, or skill that
allows a user to perform the necessary actions for task
completion.
– Reward: A core concept to the motivation of people in
the crowd
11
www.insight-centre.org
Existing Ontologies
Concept PIMO TMO HRM-O FOAF SIOC
Task Task Task
Action
User Person Job Seeker Person UserAccount
Reward Compensation
Reputation
Money Salary
Fun
Altruism
Learning
Capability
Location Location
Skill Skill
Knowledge
Ability Ability
Availability Interval
12
Personal Information Management Ontology (PIMO)
Task Management Ontology (TMO)
Human Resource Management Ontology (HRM-O)
Friend of a Friend (FOAF)
Semantically Interlinked Online Communities (SIOC)
www.insight-centre.org
SLUA Core
• Core classes and properties
13
Reward
Action
Capability
User Task
offersearns
includesperforms
requirespossesses
www.insight-centre.org
SLUA Sub-classes
• Capability
– The ability of people to do things - both the capacity
and the opportunities to do things.
– Main capabilities in literature
• Knowledge, Skill, Ability, and Others (e.g. Location,
Availability)
• Reward
– The benefit generated from the use of capability in
both labour market and non-labour market activities.
– Main rewards in literature
• Reputation, Money, Fun, Learning, Altruism or Social Good
14
www.insight-centre.org
SLUA Ontology
15
Reward
Action
Capability
User Task
offersearns
includesperforms
requirespossesses
Location Skill Knowledge Ability Availability
Reputation Money Fun Altruism Learning
subClassOf
subClassOf
www.insight-centre.org
Example Task
16
http://www.wikipedia.org/wiki/
A3_road/tasks/1
slua:Task
Please consider adding full citations to
the Wikipedia article
:loc1
slua:Location
http://live.dbpedia.org/resou
rce/London
:knw1
slua:Knowledge
http://live.dbpedia.org/resou
rce/London
:rw1
slua:Reward
slua:Reputation
:ac1
slua:Action Wiki page edit
rdfs:label
rdfs:label
a
a
a
a
a
a
slua:offers
slua:inludes
slua:requires
slua:requires
www.insight-centre.org
Example User
<http://www.wikipedia.org/wiki/user/u0901> a slua:User .
faof:name "Umair ul Hassan";
slua:possess [
a slua:Location;
slua:locatedIn <http://live.dbpedia.org/resource/London> ];
slua:possess [
a slua:Knowledge;
slua:locatedIn <http://live.dbpedia.org/resource/Roads> ];
slua:earns [
a slua:Reputation;
slua:amount "4 star" ].
17
www.insight-centre.org
Leveraging SLUA
• Task routing in heterogeneous crowdsourcing
18
Cyber Physical
Social System
Tasks Workers
Collaborative
Data Curation
Tasks Workers
Worker
Profiling
Task
Modelling
Task Routing
Matching
Cold Start
Ordering
Infrastructure Services
Application Interface, User Interface, Identity Management, Notification Services
Task
Model
Capability
Model
Capability
Models Worker
Profiless
Worker
Profiles
Worker
Profiles
www.insight-centre.org
Summary & Future Work
• SLUA is an initial step towards defining a light-
weight ontology for describing tasks, actions,
users, rewards, and capabilities in
crowdsourcing platforms
• Future plan
– Prototype based on SLUA for cross platform query
– Task routing system used match between tasks
and users with SLUA descriptors
19
www.insight-centre.org
Further Reading
U. Ul Hassan, S. O’Riain, and E. Curry, “SLUA: Towards Semantic Linking of Users with Actions in
Crowdsourcing,” in 1st International Workshop on Crowdsourcing the Semantic Web, 2013.
http://deri.ie/users/umair-ul-hassan
20
International Workshop on “Crowdsourcing the Semantic Web”
Sydney, 21 October 2013

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SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing

  • 1. www.insight-centre.org SLUA: TOWARDS SEMANTIC LINKING OF USERS WITH ACTIONS IN CROWDSOURCING Umair ul Hassan, Sean O’Riain, Edward Curry INSIGHT Centre for Data Analytics National University of Ireland, Galway 1st International Workshop on Crowdsourcing the Semantic Web, CrowdSem’13, Sydney, Australia
  • 2. www.insight-centre.org Paper Overview • Motivation – Multiple crowdsourcing platforms – Lack of tools for finding tasks – Querying across platforms for skills and knowledge of workers • Problem – Enabling interoperability across crowdsourcing platforms – Support users in their search for crowd tasks – Enable task and user matching services • Contribution – An ontology for describing crowd sourced tasks and users with regard to human capabilities, actions and rewards 2
  • 3. www.insight-centre.org Agenda • Motivation – Crowdsourcing Landscape – Semantic Heterogeneity • Challenges • SLUA Ontology • Examples • Summary 3
  • 6. www.insight-centre.org Heterogeneity Tasks Human Actions Required Capabilities Rewards Wikipedia Create Content Edit Content Moderate Content Write text Include references Highlight mistakes Domain Knowledge Writing Research Quora Ask Questions Answer Questions Write text Domain Knowledge Reputation Amazon Mechanical Turk Micro Tasks Transcribe, Translate, Categorize, etc. Various Capabilities Money TaskRabbit Physical Tasks Collect Item Deliver Item Shop Item, etc. Various Capabilities Money Microtask Form Filling Scan Correction Data Verification Play games Online gaming Fun 6
  • 7. www.insight-centre.org Challenges • Difficult to interoperate across crowdsourcing systems and platforms – e.g. searching for appropriate workers on StackExchange for Wiki editing tasks • Variations of data semantics across systems and platforms – Different APIs used by current marketplaces • Existing Taxonomies – Categorize crowdsourcing platforms instead of tasks – Do not consider human factors such as actions, capabilities, motivation. 7
  • 8. www.insight-centre.org Heterogeneous Crowds • Multiple requesters, tasks, workers, platform 8 Cyber Physical Social System Tasks Workers Collaborative Data Curation Tasks Workers Task Management Middleware
  • 9. www.insight-centre.org Proposed Model • An common model for describing tasks in crowdsourcing (CS) is required • Methodology – Enumerate similar terms on crowdsourcing platforms – Define the main concept in each group of terms – Compare with existing ontologies – Define core classes and their relationships – Extend core classes with subclasses – Create example instances 9
  • 10. www.insight-centre.org Crowdsourcing Terminology • Terms used for similar concepts in crowdsourcing platforms 10 Amazon Mechanical Turk Mobileworks Shorttask CrowdFlower Task HIT Task ShortTask Microtask User Worker Requester Worker Developer Solver Seeker Contributor Customer Capability Qualification Filter Reward Payment Payment Reward Payment
  • 11. www.insight-centre.org Model Requirements • Required concepts – Task: A unit of work to be performed by people in the crowd – Action: The cognitive or psychomotor activity that leads towards the completion of a task – User: The human participant, commonly described as “worker” in crowdsourcing marketplaces. – Capability: The human ability, knowledge, or skill that allows a user to perform the necessary actions for task completion. – Reward: A core concept to the motivation of people in the crowd 11
  • 12. www.insight-centre.org Existing Ontologies Concept PIMO TMO HRM-O FOAF SIOC Task Task Task Action User Person Job Seeker Person UserAccount Reward Compensation Reputation Money Salary Fun Altruism Learning Capability Location Location Skill Skill Knowledge Ability Ability Availability Interval 12 Personal Information Management Ontology (PIMO) Task Management Ontology (TMO) Human Resource Management Ontology (HRM-O) Friend of a Friend (FOAF) Semantically Interlinked Online Communities (SIOC)
  • 13. www.insight-centre.org SLUA Core • Core classes and properties 13 Reward Action Capability User Task offersearns includesperforms requirespossesses
  • 14. www.insight-centre.org SLUA Sub-classes • Capability – The ability of people to do things - both the capacity and the opportunities to do things. – Main capabilities in literature • Knowledge, Skill, Ability, and Others (e.g. Location, Availability) • Reward – The benefit generated from the use of capability in both labour market and non-labour market activities. – Main rewards in literature • Reputation, Money, Fun, Learning, Altruism or Social Good 14
  • 15. www.insight-centre.org SLUA Ontology 15 Reward Action Capability User Task offersearns includesperforms requirespossesses Location Skill Knowledge Ability Availability Reputation Money Fun Altruism Learning subClassOf subClassOf
  • 16. www.insight-centre.org Example Task 16 http://www.wikipedia.org/wiki/ A3_road/tasks/1 slua:Task Please consider adding full citations to the Wikipedia article :loc1 slua:Location http://live.dbpedia.org/resou rce/London :knw1 slua:Knowledge http://live.dbpedia.org/resou rce/London :rw1 slua:Reward slua:Reputation :ac1 slua:Action Wiki page edit rdfs:label rdfs:label a a a a a a slua:offers slua:inludes slua:requires slua:requires
  • 17. www.insight-centre.org Example User <http://www.wikipedia.org/wiki/user/u0901> a slua:User . faof:name "Umair ul Hassan"; slua:possess [ a slua:Location; slua:locatedIn <http://live.dbpedia.org/resource/London> ]; slua:possess [ a slua:Knowledge; slua:locatedIn <http://live.dbpedia.org/resource/Roads> ]; slua:earns [ a slua:Reputation; slua:amount "4 star" ]. 17
  • 18. www.insight-centre.org Leveraging SLUA • Task routing in heterogeneous crowdsourcing 18 Cyber Physical Social System Tasks Workers Collaborative Data Curation Tasks Workers Worker Profiling Task Modelling Task Routing Matching Cold Start Ordering Infrastructure Services Application Interface, User Interface, Identity Management, Notification Services Task Model Capability Model Capability Models Worker Profiless Worker Profiles Worker Profiles
  • 19. www.insight-centre.org Summary & Future Work • SLUA is an initial step towards defining a light- weight ontology for describing tasks, actions, users, rewards, and capabilities in crowdsourcing platforms • Future plan – Prototype based on SLUA for cross platform query – Task routing system used match between tasks and users with SLUA descriptors 19
  • 20. www.insight-centre.org Further Reading U. Ul Hassan, S. O’Riain, and E. Curry, “SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing,” in 1st International Workshop on Crowdsourcing the Semantic Web, 2013. http://deri.ie/users/umair-ul-hassan 20 International Workshop on “Crowdsourcing the Semantic Web” Sydney, 21 October 2013

Notes de l'éditeur

  1. SLUA ontology allows semantic description of crowdsourcing tasks in terms of human capabilities, actions, and rewards.
  2. Crowdsourcing is becoming prevalent There are variety of services and systems on the Web from marketplaces to knowledge bases
  3. - Crowdsourcing in variety of business models - Show the range of tasks and human services available online
  4. Why we need these dimension and their description.
  5. - An ontology is needed to standardize communication and enable unified semantics across systems