Recent advances in web technologies allow people to help solve complex problems by performing online tasks in return for money, learning, or fun. At present, human contribution is limited to the tasks defined on individual crowdsourcing platforms. Furthermore, there is a lack of tools and technologies that support matching of tasks with appropriate users, across multiple systems. A more explicit capture of the semantics of crowdsourcing tasks could enable the design and development of matchmaking services between users and tasks. The paper presents the SLUA ontology that aims to model users and tasks in crowdsourcing systems in terms of the relevant actions, capabilities, and rewards. This model describes different types of human tasks that help in solving complex problems using crowds. The paper provides examples of describing users and tasks in some real world systems, with SLUA ontology.

1. SLUA:
TOWARDS
SEMANTIC
LINKING
OF
USERS
WITH
ACTIONS
IN
CROWDSOURCING
www.insight-­‐centre.org
Umair
ul
Hassan,
Sean
O’Riain,
Edward
Curry
INSIGHT
Centre
for
Data
Analy4cs
Na4onal
University
of
Ireland,
Galway
1st International Workshop on Crowdsourcing the Semantic Web,
CrowdSem’13, Sydney, Australia

2. Paper
Overview
www.insight-­‐centre.org
• MoJvaJon
– MulJple
crowdsourcing
plaBorms
– Lack
of
tools
for
finding
tasks
– Need
to
query
across
plaPorms
for
skills
and
knowledge
of
workers
• Problem
– Enabling
interoperability
across
crowdsourcing
plaBorms
– Suppor4ng
users
in
their
search
for
tasks
– Enable
task
and
user
matching
services
• ContribuJon
– An
ini4al
lightweight
ontology
for
describing
crowd
sourced
tasks
and
users
with
regard
to
human
capabili4es,
ac4ons,
and
rewards
2

3. Agenda
www.insight-­‐centre.org
• Mo4va4on
– Crowdsourcing
Landscape
– Seman4c
Heterogeneity
•
•
•
•
Challenges
SLUA
Ontology
Examples
Summary
3

4. Crowdsourcing
Landscape
www.insight-­‐centre.org
4

5. Crowdsourcing
Landscape
www.insight-­‐centre.org
5

6. Challenges
www.insight-­‐centre.org
• Difficult
to
interoperate
across
crowdsourcing
systems
and
plaPorms
– e.g.
searching
for
appropriate
workers
on
StackExchange
for
Wiki
edi4ng
tasks
• VariaJons
of
data
semanJcs
across
systems
and
plaPorms
– Different
APIs
used
by
current
marketplaces
• ExisJng
Taxonomies
plaPorm-­‐centric
– Categorize
crowdsourcing
plaBorms
instead
of
tasks
– LiPkle
considera4on
human
of
factors
such
as
ac4ons,
capabili4es,
mo4va4on
6

7. Heterogeneous
Crowds
www.insight-­‐centre.org
Tasks
Platforms
Workers
Collaborative
Data Curation
Cyber Physical
Social System
• Mul4ple
requesters,
tasks,
workers,
plaBorm
7

8. PlaBorm
Heterogeneity
www.insight-­‐centre.org
Tasks
Human
AcJons
Required
CapabiliJes
Rewards
Wikipedia
Create
Content
Edit
Content
Moderate
Content
Write
text
Include
references
Highlight
mistakes
Domain
Knowledge
Wri4ng
Research
Social
Good
Quora
Ask
Ques4ons
Answer
Ques4ons
Write
text
Domain
Knowledge
Reputa4on
Amazon
Mechanical
Turk
Micro
Tasks
Transcribe,
Translate,
Categorize,
etc.
Various
Capabili4es
Money
TaskRabbit
Physical
Tasks
Collect
Item
Deliver
Item
Shop
Item,
etc.
Various
Capabili4es
Money
Microtask
Form
Filling
Scan
Correc4on
Data
Verifica4on
Play
games
Online
gaming
Fun
8

9. Proposed
Solu4on
www.insight-­‐centre.org
• A
common
model
for
describing
tasks
in
crowdsourcing
• Seman4cally
Linked
Users
and
Ac4ons
(SLUA)
– Lightweight
semanJc
descripJon
of
crowdsourcing
tasks
in
terms
of
human
capabiliJes,
acJons,
and
rewards
• SLUA
– Gaelic
word
for…
…“Crowd”
9

10. SLUA
Design
Medthdology
www.insight-­‐centre.org
1. Enumerate
similar
terms
on
crowdsourcing
plaBorms
2. Define
the
main
concept
in
each
group
of
terms
3. Compare
with
exis4ng
ontologies
4. Define
core
classes
and
their
rela4onships
5. Extend
core
classes
with
subclasses
6. Create
example
instances
10

11. Crowdsourcing
Terminology
www.insight-­‐centre.org
Amazon
Mechanical
Turk
Mobileworks
ShorXask
CrowdFlower
Task
HIT
Task
ShortTask
Microtask
User
Worker
Requester
Worker
Developer
Solver
Seeker
Contributor
Customer
Capability
Qualifica4on
Filter
Reward
Payment
Payment
Reward
Payment
• Terms
used
for
similar
concepts
in
crowdsourcing
plaBorms
11

12. Conceptual
Requirements
www.insight-­‐centre.org
• Task:
A
unit
of
work
to
be
performed
by
people
in
the
crowd
• AcJon:
The
cogni4ve
or
psychomotor
ac4vity
that
leads
towards
the
comple4on
of
a
task
• User:
The
human
par4cipant,
commonly
described
as
“worker”
in
crowdsourcing
marketplaces.
• Capability:
The
human
ability,
knowledge,
or
skill
that
allows
a
user
to
perform
the
necessary
ac4ons
for
task
comple4on.
• Reward:
A
core
concept
to
the
mo4va4on
of
people
in
the
crowd
12

13. Exis4ng
Ontologies
www.insight-­‐centre.org
Concept
PIMO
TMO
HRM-­‐O
FOAF
SIOC
Task
Task
Task
AcJon
User
Person
Job
Seeker
Person
UserAccount
Reward
Compensa4on
Reputa4on
Money
Salary
Fun
Altruism
Learning
Capability
Loca4on
Loca4on
Skill
Skill
Knowledge
Ability
Ability
Availability
Interval
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

14. SLUA
Core
Classes
and
Proper4es
www.insight-­‐centre.org
earns
User
Reward
performs
possesses
Action
Capability
offers
includes
Task
requires
14

15. SLUA
Sub-­‐classes
www.insight-­‐centre.org
• Capability
– The
ability
of
people
to
do
things
-­‐
both
the
capacity
and
the
opportuni4es
to
do
things.
– Main
capabili4es
in
literature
• Knowledge,
Skill,
Ability,
and
Others
(e.g.
Loca4on,
Availability)
• Reward
– The
benefit
generated
from
the
use
of
capability
in
both
labour
market
and
non-­‐labour
market
ac4vi4es.
– Main
rewards
in
literature
• Reputa4on,
Money,
Fun,
Learning,
Altruism
or
Social
Good
15

16. SLUA
Ontology
www.insight-­‐centre.org
Reputation
Money
Fun
Altruism
Learning
subClassOf
earns
User
Reward
performs
possesses
Action
Capability
offers
includes
Task
requires
subClassOf
Location
Skill
Knowledge
16
Ability
Availability

17. Example
Task
www.insight-­‐centre.org
Please
consider
adding
full
cita4ons
to
the
Wikipedia
ar4cle
slua:Task
a
slua:Loca4on
a
hPp://www.wikipedia.org/wiki/
A3_road/tasks/1
slua:requires
slua:Reward
:loc1
hPp://live.dbpedia.org/
resource/London
slua:Knowledge
rdfs:label
slua:requires
slua:includes
:ac1
a
a
:knw1
17
a
:rw1
rdfs:label
hPp://live.dbpedia.org/
resource/London
slua:Ac4on
slua:offers
Wiki
page
edit
a
slua:Reputa4on

18. SLUA
in
Ac4on
www.insight-­‐centre.org
Tasks
SLUA Mediated Task Routing
Task
Modelling
Task Routing
Worker
Profiling
Matching
Collaborative
Data Curation
Capability
Capability
Models
Task
Model
Model
Cold Start
Worker
Worker
Profiles
Worker
Profiles
Profiless
Ordering
SLUA Mediated Infrastructure Services
Cyber Physical
Social System
Application Interface, User Interface, Identity Management,
Notification Services
18
Workers

19. Collabora4ve
Data
Cura4on
www.insight-­‐centre.org
Programmers
Managers
Web of Data
DQ Rules &
Algorithms
Human
Computation
Entity Linking
Data Fusion
Relation Extraction
Databases
External Crowd
- High Availability
- Large Scale
- Expertise Variety
Relevance Judgment
Data Verification
Disambiguation
Textual Content
Clean Data
19
Internal Community
- Domain Knowledge
- High Quality Responses
- Trustable

20. Cyber-­‐Physical
Social
Systems
www.insight-­‐centre.org
Sensor Data
Collection
Temperature
of Room 202e
Energy
Decision
Models
Human
Actuation
Close Window
Room 202e
Monitored Physical Environment
Located near Room 202e
20

21. Summary
&
Future
Work
www.insight-­‐centre.org
• SLUA
is
an
ini4al
step
towards
defining
a
light-­‐
weight
ontology
for
describing
tasks,
acJons,
users,
rewards,
and
capabiliJes
in
crowdsourcing
plaBorms
• Future
Plans
– Enumerate
design
with
addi4onal
crowdsourcing
plaBorms
– Prototype
SLUA-­‐based
for
cross
plaBorm
query
– Task
rou4ng
system
used
match
between
tasks
and
users
with
SLUA
descriptors
21

22. Further
Reading
www.insight-­‐centre.org
International Workshop on “Crowdsourcing the Semantic Web”
Sydney, 21 October 2013
Ontology
Available
at:
hXp://vocab.deri.ie/slua
U.
Ul
Hassan,
S.
O’Riain,
and
E.
Curry,
“SLUA:
Towards
SemanJc
Linking
of
Users
with
AcJons
in
Crowdsourcing,”
in
1st
InternaJonal
Workshop
on
Crowdsourcing
the
SemanJc
Web,
2013.
hXp://deri.ie/users/umair-­‐ul-­‐hassan
22