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

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Davide EynardPolitecnico di Milano, 07-04-2009

Introduction

Ch 1

3


Participative systems

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

Encyclopedias BookmarksMaps

News Word processorsMusic

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Participation and semantics

How does the virtuous cycle work?

Data

Structure

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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

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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!

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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

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Background

Ch 2

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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

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Background – Basics on social interactions

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

Becoming Wikipedian

Engeström, Vygotsky• Activity Theory

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

Image courtesy of Ross Mayfield's Weblog

http://www.cc.gatech.edu/~asb/papers/bryant-forte-bruckman-group05.pdf

http://www.edu.helsinki.fi/activity/pages/chatanddwr/activitysystem/

http://www.edu.helsinki.fi/activity/pages/chatanddwr/activitysystem/

http://ross.typepad.com/blog/2006/04/power_law_of_pa.html

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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”

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Our work

Ch 3

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Our work – Evaluate and design

The Six Ws:

Who• user, community, producer,

consumer What

• tool, object, contents, traces How

• explicit vs implicit participation, coupling

When• sync vs async participation

Where• context, centralized vs

distributed Why

• incentives, engagement

User-centered design:

keep semantics hidden reuse and standardize merge with the activity evolve with complexity

(see D. Norman: “The design of everyday things”)

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Our work – Extend systems with semantics

SystemContext

Domain

Upper

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

[B.1]

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Experimental developments

Ch 4, 5, 6

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Semantic Wikis

Wikipedia OMP Intranet

Who

What

How

When Asynchronous Asynchronous

Where Centralized

Why

Generic Internet users who write for everyone

Generic Internet users who write for everyone

Employees with specific addressee (group, boss)

Encyclopedia, divided in articles

Hypertextual book (mostly atomic)

Internal atomic docs, reports, attachments,

annoucements

Contributive, collective, explicit participation

Mostly collective, explicit participation

Contributive, often collective, explicit/implicit

participation

Asynchronous (stronger need for updates!)

Centralized (what about China?)

Centralized in an intranet context (authorship,

confidentiality)

Social/personal incentives, small COP

Social/personal incentives, often just individuals

“Because my boss says so”, groups/labs as COP

Wikis are not all the same:

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

+ ?

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Folksonomies

Who

What

How

When Asynchronous

Where Usually centralized

Why

Generic Internet users who mostly tag for themselves

Classification technology

Contributive, implicit, low coupling

Personal incentives

Main limits: no synonym control “basic level” variations lack of precision lack of recall lack of hierarchy system-dependent

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

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

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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]

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Conclusions

Ch 7

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Conclusions

we chose a topic

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Conclusions

we chose a topicwe extended it

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Conclusions

we chose a topicwe extended it(in different directions)

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Conclusions

we chose a topicwe extended it(in different directions)this allowed us to study it from other perspectives

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Conclusions

we chose a topicwe extended it(in different directions)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

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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

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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

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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

[email protected]

http://www.dei.polimi.it/people/eynard

Tel. 02 2399 4010

Fax 02 2399 3411

Back

Project page @AIRLab: http://airwiki.elet.polimi.it

mailto:[email protected]

http://www.dei.polimi.it/people/eynard

http://airwiki.elet.polimi.it/

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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

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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:

http://davide.eynard.it/sa

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Taxonomy of participation - a total mess!

social

participative/collective

contributive

do/create

suggest

share

alone with others

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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

http://www.edu.helsinki.fi/activity/pages/chatanddwr/activitysystem

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1) Structure data

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Folksonomies: datasets and stats

x axis: tags ordered by usagey axis: percentage of tags belonging to WordNet

We have collected a large dataset from del.icio.us that allowed us to study tags statistically.

http://davide.eynard.it/?p=28

A Virtuous Cycle of Semantics and Participation

Technology

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