A Virtuous Cycle of Semantics and Participation

A Virtuous Cycle of Semantics and Participation

Doctoral dissertation of: Davide Eynard
Advisor: Prof. M.Colombetti
Tutor: Prof. A.Bonarini

2
Ch 1

Introduction

Politecnico di Milano, 07-04-2009 Davide Eynard

3

Participative systems

A particular class of social systems in which people can interact, share
information, or both.

Encyclopedias Maps Bookmarks

Music News Word processors


4

Participation and semantics

How does the virtuous cycle work?

Data

Structure


5

Motivations

Successful
 See “What is Web2.0” by Tim O'Reilly
 On the Internet, but also inside intranets

Interesting from different point of views:
 Psychology
• Incentives, bootstrap problem
 HCI
• New interfaces and interaction paradigms
 Social Sciences
• Collective intelligence, trust
 KM
• Use meaningful formats for interoperability
 New technologies
• Scalability, reliability


6

There's Bad and “Bad”

Bad collaborative system
 Too complex
 Bad interaction with user
 No incentives to participate
 Tool doesn't fit the objective
 “I love the system – I just don't use it!”

“Bad” collaborative system
 Users like it
 Fits tool and community well, but...
 ... it could be made better with semantics!


7

Research objectives

Given a community, a task and a context

 develop a methodology to evaluate whether a system
correctly fits an activity

 use semantics to make the system better, incentivating
user contribution


8
Ch 2

Background


9

Background – Social Systems

 Creating and publishing
• blogs, wikis, collaborative editors
 Communicating
• e-mail, forums, chat, microblogging
 Sharing
• p2p, client-server, social bookmarking
 Recommending
• implicitly or explicitly, specific or general
 Coordinating
• calendars, project or knowledge management
 Networking
• social networks (object centered or not)
 Playing
• MUD, MMORPG (Second Life)
 Market places
• auctions, recruitment


10

Background – Basics on social interactions

 Wenger, Lave
• Communities of Practice
• Legitimate Peripheral Participation
• see Bryant, Forte, Bruckman:
Becoming Wikipedian

Image courtesy of Ross Mayfield's Weblog

 Engeström, Vygotsky
• Activity Theory

Image courtesy of University of Helsinki - Center for Activity Theory
and Developmental Work Research


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Background – Semantic Web

“An extension of the current Web, in which information is given well
defined meaning, better enabling computers and people to work in
cooperation”


12
Ch 3

Our work


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Our work – Evaluate and design

The Six Ws: User-centered design:
 Who  keep semantics hidden
• user, community, producer,  reuse and standardize
consumer  merge with the activity
 What
 evolve with complexity
• tool, object, contents, traces
 How
(see D. Norman: “The design of
• explicit vs implicit
everyday things”)
participation, coupling
 When
• sync vs async participation
 Where
• context, centralized vs
distributed
 Why
• incentives, engagement


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Our work – Extend systems with semantics

Semantics have been applied on different levels
 Link data (“a little semantics goes a long way”, J. Hendler)
 Better describe knowledge
 Infer new knowledge with reasoning

When ontologies are used, they are applied on different levels too

Upper

Domain

Context
System [B.1]


15
Ch 4, 5, 6

Experimental
developments


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Semantic Wikis

Wikis are not all the same:
Wikipedia + OMP Intranet ?
Generic Internet users who Generic Internet users who Employees with specific
Who write for everyone write for everyone addressee (group, boss)
Internal atomic docs,
Encyclopedia, divided in Hypertextual book (mostly
What articles atomic)
reports, attachments,
annoucements
Contributive, often
Contributive, collective, Mostly collective, explicit
How explicit participation participation
collective, explicit/implicit
participation
Asynchronous (stronger need
When Asynchronous Asynchronous
for updates!)
Centralized in an intranet
Centralized (what about
Where China?)
Centralized context (authorship,
confidentiality)
Social/personal incentives, Social/personal incentives, “Because my boss says so”,
Why small COP often just individuals groups/labs as COP

Semantic extensions:
 for data (templates for contents – describe knowledge)
 and metadata (about pages and attachments – describe and infer)


17

Folksonomies

Main limits: Generic Internet users who
 no synonym control Who mostly tag for themselves

 “basic level” variations What Classification technology
Contributive, implicit, low
 lack of precision How coupling
 lack of recall When Asynchronous

 lack of hierarchy Where Usually centralized

 system-dependent
Why Personal incentives

Folksonomy + Ontology
 disambiguate words
 add hierarchy
 interlink folksonomies
 (describe and link)

[B.2, B.3, B.5]


18

Annotation Systems: Linking Open (meta)Data

Linking Open Data is:
 a project which aims at making data freely available to anyone,
setting RDF links between items from different data sources
 a paradigm to publish information on the Web

Metadata = information about information
 anything which has a URI can be commented (or annotated)
 common limits of annotation systems:
• low user incentives
• cannot reuse metadata over different systems
 LOD as a possible solution
• provides a large data base to bootstrap system
• suggests a widespread, machine interpretable standard for
information sharing and reuse
• what about linking other types of data?
[D.1, B.4, D.2]


19
Ch 7

Conclusions


20

Conclusions

we chose a topic


21

Conclusions

we chose a topic
we extended it


22

Conclusions

we chose a topic
we extended it
(in different directions)


23

Conclusions

we chose a topic
we extended it
this allowed us to study it from other perspectives


24

Conclusions

we chose a topic
we extended it
this allowed us to study it from other perspectives

Results
 the behavior and the success of a
participative system depend on many
different factors (i.e. community, incentives,
context)
 we developed a general methodology to
evaluate participative systems and
technologies and we applied it to some
specific cases
 for each of these cases, we used
semantics to build better tools


25

Conclusions

Our contributions
 General
• our methodology does not depend on a particular system
 Specific
• we applied semantics on different levels (and not just on contents)
to build a better intranet wiki;
• we applied semantic disambiguation techniques to address some of
the most important problem of folksonomies and provided a new,
hierarchical interface to browse tag-based systems;
• we suggested a solution to the bootstrap problem, which employs
already available open data sources to provide a user incentive;
• by converting email and web history to a standard and shared
representation, we automatically linked two of the most accessed
data repositories to a huge amount of related information.
Limits
 Our evaluations were mostly focused on datasets and
algorithms


26

Conclusions

Future work
 Develop a model for the evaluation, the extraction, and the
reconciliation of data coming from different and heterogeneous
data sources
 Delve deeper into the intelligent part of collective intelligence


27

The end

Thank you! Questions?


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Relevant publications

 [D.2] Eynard, D. (2008) Using semantics and participation to customize
personalization. HP Labs Technical Report HPL-2008-197.
 [B.5] Bindelli, S., C. Criscione, C.A. Curino, M.L. Drago, D. Eynard, & G.
Orsi (2008). Improving Search and Navigation by Combining Ontologies
and Social Tags. Proc. of the 1st International Workshop on Ambient Data
Integration, Monterey, Mexico.
 [B.4] Eynard, D., & M. Colombetti (2008). Exploiting user gratification for
collaborative semantic annotation. Proc. SWUI 2008.
 [B.3] Laniado, D., D. Eynard & M. Colombetti (2007). Using WordNet to turn
a folksonomy into a hierarchy of concepts. Proc. 4th Fourth Italian Semantic
Web Workshop, 192–201.
 [B.2] Laniado, D., D. Eynard & M. Colombetti (2007). A semantic tool to
support navigation in a folksonomy. Proc. 18th Conference on Hypertext
and Hypermedia (ACM Press, New York), 153–154,.
 [D.1] Eynard, D., J. Recker & C. Sayers (2007). An IMAP plugin for
SquirrelRDF. HP Labs Technical Report HPL-2007-161.
 [B.1] Eynard, D. (2007). Research on collaborative information sharing
systems. Proc. Knowledge Web PhD Symposium 2007, 81–82.


Contact Davide Eynard

Tel. 02 2399 4010
Fax 02 2399 3411

eynard@elet.polimi.it
http://www.dei.polimi.it/people/eynard
Project page @AIRLab: http://airwiki.elet.polimi.it

Back

30

Semantic Wikis

 Data
• semantic templates using a domain ontology

 Metadata
• automatic extraction and ontology supported management of
attachment metadata
• context ontology to describe properties and relations between
documents


31

Annotation Systems: Linking Open (meta)Data

 Email
• An automatic IMAP to RDF translation tool
• Information can be queried on the fly with
SPARQL, saved in RDF and piped to
external services

 Browser history
• Linking history data (visited or bookmarked
URLs) with related, already available
metadata from Freebase

 Semantic Annotation Tools
• Exploiting user gratification for collaborative
semantic annotation


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Linking Open (meta)Data

Browser
 Linking history data (visited or bookmarked URLs) with related,
already available metadata


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Linking Open (meta)Data

Semantic Annotation Tools
 Exploiting user gratification for collaborative semantic annotation


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Annotation systems

Speakinabout architecture:


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Taxonomy of participation - a total mess!

alone with others
do/create

suggest

share

contributive
participative/collective
social


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Levels of participation - The county fair example

• many people participate (take part) to the event
• some contributed with suggestions, actions or resources
• some collaborated to organize it
• some are just there to have fun, or for their business
• ... but the fair success depends on all of them!
• see Engeström's Activity Theory


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1) Structure data


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Folksonomies: datasets and stats

x axis: tags ordered by usage
y axis: percentage of tags belonging to WordNet
We have collected a large
dataset from del.icio.us that
allowed us to study tags
statistically.


A Virtuous Cycle of Semantics and Participation

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