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WIMMICSWeb-instrumented man-machine interactions, communities and semantics
   
Fabien GANDON
http://fabien.info
SOPHIA TEAM
 Inria
 CNRS
 University of Nice
Inria Lille - Nord Europe (2008)
Inria Saclay – Ile-de-France
(2008)
Inria Nancy – Grand Est
(1986)
Inria Grenoble – Rhône-
Alpes (1992)
Inria Sophia Antipolis Méditerranée (1983)
Inria Bordeaux
Sud-Ouest (2008)
Inria Rennes
Bretagne
Atlantique
(1980)
Inria Paris-Rocquencourt
(1967)
Montpellier
Lyon
Nantes
Strasbourg
Center
Branch
Pau
I3S
CHALLENGE
to bridge social semantics and
formal semantics on the Web
MULTI-DISCIPLINARY TEAM
 50 members (2015)
 14 nationalities
 1 DR, 3 Professors
 3CR, 4 Assistant professors
 1 SRP
DR/Professors:
 Fabien GANDON, Inria, AI, KR, Semantic Web, Social Web
 Nhan LE THANH, UNS, Logics, KR, Emotions
 Peter SANDER, UNS, Web, Emotions
 Andrea TETTAMANZI, UNS, AI, Logics, Agents,
CR/Assistant Professors:
 Michel BUFFA, UNS, Web, Social Media
 Elena CABRIO, UNS, NLP, KR, Linguistics
 Olivier CORBY, Inria, KR, AI, Sem. Web, Programming, Graphs
 Catherine FARON-ZUCKER, UNS, KR, AI, Semantic Web, Graphs
 Alain GIBOIN, Inria, Interaction Design, KE, User & Task models
 Isabelle MIRBEL, UNS, Requirements, Communities
 Serena VILLATA, CNRS, AI, Argumentation, Licenses, Rights
Inria Starting Position: Alexandre MONNIN, Philosophy, Web
RESEARCH CHALLENGES
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
RESEARCH CHALLENGES
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
How do we improve our interactions with a
semantic and social Web ?
• capture and model the users' characteristics?
• represent and reason with the users’ profiles?
• adapt the system behaviors as a result?
• design new interaction means?
• evaluate the quality of the interaction designed?

RESEARCH CHALLENGES
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
How can we manage the collective activity on social
media?
• analyze the social interaction practices and the
structures in which these practices take place?
• capture the social interactions and structures?
• formalize the models of these social constructs?
• analyze & reason on these models of social activity?

RESEARCH CHALLENGES
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
What are the needed schemas and extensions of
the semantic Web formalisms for our models?
• formalisms best suited for the models of the
challenges 1 & 2 ?
• limitations and extensions of existing formalisms?
• missing schemas, ontologies, vocabularies?
• links and combinations of existing formalisms?

RESEARCH CHALLENGES
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
What are the algorithms required to analyze and
reason on the heterogeneous graphs we obtained?
• analyze graphs of different types and their
interactions?
• support different graph life-cycles, calculations and
characteristics?
• assist different tasks of our users?
• design the Web architecture to deploy this?

METHODS AND TOOLS
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing





G2 H2

G1 H1
<
Gn Hn
METHODS AND TOOLS
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing
 • user models, personas, emotion capture
• mockups, evaluation campaigns
• KB interaction (context, Q&A, exploration, …)




G2 H2

G1 H1
<
Gn Hn
METHODS AND TOOLS
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing


• user models, personas, emotion capture
• mockups, evaluation campaigns
• KB interaction (context, Q&A, exploration, …)
• collective personas, coordinative artifacts
• community detection, labelling
• argumentation theory, sentiment analysis



G2 H2

G1 H1
<
Gn Hn
METHODS AND TOOLS
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing



• user models, personas, emotion capture
• mockups, evaluation campaigns
• KB interaction (context, Q&A, exploration, …)
• collective personas, coordinative artifacts
• community detection, labelling
• argumentation theory, sentiment analysis
• ontology-based knowledge representation
• formalisms: typed graphs, uncertainty
• knowledge extraction, data translation


G2 H2

G1 H1
<
Gn Hn
METHODS AND TOOLS
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing




• user models, personas, emotion capture
• mockups, evaluation campaigns
• KB interaction (context, Q&A, exploration, …)
• collective personas, coordinative artifacts
• community detection, labelling
• argumentation theory, sentiment analysis
• ontology-based knowledge representation
• formalisms: typed graphs, uncertainty
• knowledge extraction, data translation
• graph querying, reasoning, transforming
• induction, propagation, approximation
• explanation, tracing, control, licensing, trust
RESULTS 2013-2015
1. user & interaction design
2. communities & social networks
3. linked data & semantic Web
4. reasoning & analyzing




• e.g. DiscoveryHub, PRISSMA, QAKiS
[IJCAI, WI, Semantics, ESWC, Hypertext, IJSWIS, …]
• e.g. OCKTOPUS, WikiNEXT, SEEMPAD
[AI, CHI, ECAI, WI, COMMA, ASONAM, IAT, SAC, …]
• e.g. L4LOD, S4AC, Ratio4TA, Dbpedia.fr
[ECAI, IJCAI, LREC, AAMAS, RuleML, WebIST, …]
• e.g. CORESE, Licentia, DiscoveryHub, PRISSMA
[ISWC, EKAW, KCAP, WI, ESWC, Hypertext, ICAIL, …]
SEARCHING
 exploratory search
 question-answering
SEARCHING
 exploratory search
 question-answering
DBPEDIA.FR (extraction, end-point)
180 000 000 triples
models
Web architecture
SEARCHING
 exploratory search
 question-answering
DBPEDIA.FR (extraction, end-point)
180 000 000 triples
DISCOVERYHUB.CO
semantic spreading
activation
new evaluation protocol
SEARCHING
 exploratory search
 question-answering
DBPEDIA.FR (extraction, end-point)
180 000 000 triples
DISCOVERYHUB.CO
QAKiS.ORG
semantic spreading
activation
new evaluation protocol
[D:Work], played by [R:Person]
[D:Work] stars [R:Person]
[D:Work] film stars [R:Person]
starring(Work, Person)
linguistic relational
pattern extraction
named entity recognition
similarity based SPARQL
generation
select * where {
dbpr:Batman_Begins dbp:starring ?v .
OPTIONAL {?v rdfs:label ?l
filter(lang(?l)="en")} }
MODELING USERS
 individual context
 social structures
MODELING USERS
 individual context
 social structures
PRISSMA
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{ 3, 1, 2, { pr i ssma: poi } }
{ 4, 0, 3, { pr i ssma: envi r onment } }
:atTheMuseum
error tolerant graph
edit distance
context
ontology
MODELING USERS
 individual context
 social structures
PRISSMA
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{ 3, 1, 2, { pr i ssma: poi } }
{ 4, 0, 3, { pr i ssma: envi r onment } }
:atTheMuseum
error tolerant graph
edit distance
context
ontology
OCKTOPUS
tag, topic, user
distribution
tag and folksonomy
restructuring with
prefix trees
MODELING USERS
 individual context
 social structures
PRISSMA
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{ 3, 1, 2, { pr i ssma: poi } }
{ 4, 0, 3, { pr i ssma: envi r onment } }
:atTheMuseum
error tolerant graph
edit distance
context
ontology
OCKTOPUS
tag, topic, user
distribution
tag and folksonomy
restructuring with
prefix trees
EMOCA&SEEMPAD
emotion detection & annotation
QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
 &
G2 H2
 &
G1 H1
<
Gn Hn
abstract graph machine
STTL
QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
 &
G2 H2
 &
G1 H1
<
Gn Hn
RATIO4TA
predict &
explain
abstract graph machine
STTL
QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
INDUCTION
 &
G2 H2
 &
G1 H1
<
Gn Hn
RATIO4TA
predict &
explain
find missing
knowledge
abstract graph machine
STTL
QUERY & INFER
 graph rules and queries
 deontic reasoning
 induction
CORESE
LICENTIA INDUCTION
 &
G2 H2
 &
G1 H1
<
Gn Hn
RATIO4TA
predict &
explain
find missing
knowledge
license compatibility
and composition
abstract graph machine
STTL
ACHIEVEMENTS
• publications
• awards
• visibility
• 9 Ph.D. theses defended
• multidisciplinary publication
• best paper awards: ESWC 2013 ; EEE/WIC/ACM IAT
2014 ; IEEE Cognitive Infocommunications ; IEEE
BDAS 2014 ; IC2015
• PC of major journals and conferences
• General Chair ESWC 2015, PC chair ESWC 2014, ...
COLLABORATIONS
• collaborative projects (7)
• industrial contracts (6)
• scholarships (8)
+ MIREL
DIFFUSION / TRANSFER
• education, training
• industrial transfer
• two MOOCS (HTML5 EN 100K, Semantic Web FR 4K)
• important teaching activity
• W3C participation (AC Rep, several WG)
• 2 Carnot projects with SMEs
• first ANR LabCom on digital sciences
joint Lab Wimmics-Viseo
• spin-off to industrialize research results
one of the first software cooperatives
FUTURE
• Linked Data & Web diversity
• Artificial Web intelligence
• Human-Data Web Interactions
• Web-augmented interactions
• coupling AI and distributed AI with the Web
• knowledge representation & extraction on the Web
• incremental & linked formalizations
• argumentation mining & theory
• textual entailment & LOD-based NLP
• participatory design and evaluation
• natural language question-answering and dialogue
• visual analytics for linked data
• architecture & philosophy of the Web
WIMMICSbridging social semantics and formal semantics on the Web.
epistemic communitieslinked data
usages and introspection
contributions and traces

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Wimmics Research Team 2015 Activity Report

  • 1. WIMMICSWeb-instrumented man-machine interactions, communities and semantics     Fabien GANDON http://fabien.info
  • 2. SOPHIA TEAM  Inria  CNRS  University of Nice Inria Lille - Nord Europe (2008) Inria Saclay – Ile-de-France (2008) Inria Nancy – Grand Est (1986) Inria Grenoble – Rhône- Alpes (1992) Inria Sophia Antipolis Méditerranée (1983) Inria Bordeaux Sud-Ouest (2008) Inria Rennes Bretagne Atlantique (1980) Inria Paris-Rocquencourt (1967) Montpellier Lyon Nantes Strasbourg Center Branch Pau I3S
  • 3. CHALLENGE to bridge social semantics and formal semantics on the Web
  • 4. MULTI-DISCIPLINARY TEAM  50 members (2015)  14 nationalities  1 DR, 3 Professors  3CR, 4 Assistant professors  1 SRP DR/Professors:  Fabien GANDON, Inria, AI, KR, Semantic Web, Social Web  Nhan LE THANH, UNS, Logics, KR, Emotions  Peter SANDER, UNS, Web, Emotions  Andrea TETTAMANZI, UNS, AI, Logics, Agents, CR/Assistant Professors:  Michel BUFFA, UNS, Web, Social Media  Elena CABRIO, UNS, NLP, KR, Linguistics  Olivier CORBY, Inria, KR, AI, Sem. Web, Programming, Graphs  Catherine FARON-ZUCKER, UNS, KR, AI, Semantic Web, Graphs  Alain GIBOIN, Inria, Interaction Design, KE, User & Task models  Isabelle MIRBEL, UNS, Requirements, Communities  Serena VILLATA, CNRS, AI, Argumentation, Licenses, Rights Inria Starting Position: Alexandre MONNIN, Philosophy, Web
  • 5. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing
  • 6. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing How do we improve our interactions with a semantic and social Web ? • capture and model the users' characteristics? • represent and reason with the users’ profiles? • adapt the system behaviors as a result? • design new interaction means? • evaluate the quality of the interaction designed? 
  • 7. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing How can we manage the collective activity on social media? • analyze the social interaction practices and the structures in which these practices take place? • capture the social interactions and structures? • formalize the models of these social constructs? • analyze & reason on these models of social activity? 
  • 8. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing What are the needed schemas and extensions of the semantic Web formalisms for our models? • formalisms best suited for the models of the challenges 1 & 2 ? • limitations and extensions of existing formalisms? • missing schemas, ontologies, vocabularies? • links and combinations of existing formalisms? 
  • 9. RESEARCH CHALLENGES 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing What are the algorithms required to analyze and reason on the heterogeneous graphs we obtained? • analyze graphs of different types and their interactions? • support different graph life-cycles, calculations and characteristics? • assist different tasks of our users? • design the Web architecture to deploy this? 
  • 10. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing      G2 H2  G1 H1 < Gn Hn
  • 11. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing  • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …)     G2 H2  G1 H1 < Gn Hn
  • 12. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing   • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis    G2 H2  G1 H1 < Gn Hn
  • 13. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing    • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis • ontology-based knowledge representation • formalisms: typed graphs, uncertainty • knowledge extraction, data translation   G2 H2  G1 H1 < Gn Hn
  • 14. METHODS AND TOOLS 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing     • user models, personas, emotion capture • mockups, evaluation campaigns • KB interaction (context, Q&A, exploration, …) • collective personas, coordinative artifacts • community detection, labelling • argumentation theory, sentiment analysis • ontology-based knowledge representation • formalisms: typed graphs, uncertainty • knowledge extraction, data translation • graph querying, reasoning, transforming • induction, propagation, approximation • explanation, tracing, control, licensing, trust
  • 15. RESULTS 2013-2015 1. user & interaction design 2. communities & social networks 3. linked data & semantic Web 4. reasoning & analyzing     • e.g. DiscoveryHub, PRISSMA, QAKiS [IJCAI, WI, Semantics, ESWC, Hypertext, IJSWIS, …] • e.g. OCKTOPUS, WikiNEXT, SEEMPAD [AI, CHI, ECAI, WI, COMMA, ASONAM, IAT, SAC, …] • e.g. L4LOD, S4AC, Ratio4TA, Dbpedia.fr [ECAI, IJCAI, LREC, AAMAS, RuleML, WebIST, …] • e.g. CORESE, Licentia, DiscoveryHub, PRISSMA [ISWC, EKAW, KCAP, WI, ESWC, Hypertext, ICAIL, …]
  • 17. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples models Web architecture
  • 18. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples DISCOVERYHUB.CO semantic spreading activation new evaluation protocol
  • 19. SEARCHING  exploratory search  question-answering DBPEDIA.FR (extraction, end-point) 180 000 000 triples DISCOVERYHUB.CO QAKiS.ORG semantic spreading activation new evaluation protocol [D:Work], played by [R:Person] [D:Work] stars [R:Person] [D:Work] film stars [R:Person] starring(Work, Person) linguistic relational pattern extraction named entity recognition similarity based SPARQL generation select * where { dbpr:Batman_Begins dbp:starring ?v . OPTIONAL {?v rdfs:label ?l filter(lang(?l)="en")} }
  • 20. MODELING USERS  individual context  social structures
  • 21. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology
  • 22. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology OCKTOPUS tag, topic, user distribution tag and folksonomy restructuring with prefix trees
  • 23. MODELING USERS  individual context  social structures PRISSMA prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 { 3, 1, 2, { pr i ssma: poi } } { 4, 0, 3, { pr i ssma: envi r onment } } :atTheMuseum error tolerant graph edit distance context ontology OCKTOPUS tag, topic, user distribution tag and folksonomy restructuring with prefix trees EMOCA&SEEMPAD emotion detection & annotation
  • 24. QUERY & INFER  graph rules and queries  deontic reasoning  induction
  • 25. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE  & G2 H2  & G1 H1 < Gn Hn abstract graph machine STTL
  • 26. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain abstract graph machine STTL
  • 27. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE INDUCTION  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain find missing knowledge abstract graph machine STTL
  • 28. QUERY & INFER  graph rules and queries  deontic reasoning  induction CORESE LICENTIA INDUCTION  & G2 H2  & G1 H1 < Gn Hn RATIO4TA predict & explain find missing knowledge license compatibility and composition abstract graph machine STTL
  • 29. ACHIEVEMENTS • publications • awards • visibility • 9 Ph.D. theses defended • multidisciplinary publication • best paper awards: ESWC 2013 ; EEE/WIC/ACM IAT 2014 ; IEEE Cognitive Infocommunications ; IEEE BDAS 2014 ; IC2015 • PC of major journals and conferences • General Chair ESWC 2015, PC chair ESWC 2014, ...
  • 30. COLLABORATIONS • collaborative projects (7) • industrial contracts (6) • scholarships (8) + MIREL
  • 31. DIFFUSION / TRANSFER • education, training • industrial transfer • two MOOCS (HTML5 EN 100K, Semantic Web FR 4K) • important teaching activity • W3C participation (AC Rep, several WG) • 2 Carnot projects with SMEs • first ANR LabCom on digital sciences joint Lab Wimmics-Viseo • spin-off to industrialize research results one of the first software cooperatives
  • 32. FUTURE • Linked Data & Web diversity • Artificial Web intelligence • Human-Data Web Interactions • Web-augmented interactions • coupling AI and distributed AI with the Web • knowledge representation & extraction on the Web • incremental & linked formalizations • argumentation mining & theory • textual entailment & LOD-based NLP • participatory design and evaluation • natural language question-answering and dialogue • visual analytics for linked data • architecture & philosophy of the Web
  • 33. WIMMICSbridging social semantics and formal semantics on the Web. epistemic communitieslinked data usages and introspection contributions and traces