CUbRIK Presentation 
0 
Humanist-Machine Interaction for the 
digital humanities 
Building the Social graph of the History of European 
Integration 
DHLU 2013 
www.cubrikproject.eu
About CUbRIK 
 
European Community's Seventh FrameworkProgram FP7-ICT 
 
15 European partners 
 
Multimedia searchprocessing: Puttinghumans in the loop 
 
Demos: History of Europeand Fashion 
CUbRIK Presentation 
1
CUbRIK Presentation 
2 
Why CUbRIK approach 
 Human in the loop added value: 
Verification of identities/places/events ambiguous and temporal onlypossible by putting humans in the loop 
Integration of multiple perspectives 
 CUbRIK as an open toolbox allows 
follow-up and extension through 
third parties 
 “ 
Vertical”integration: 
GUI, components, crowdsourcing 
integrated in a platform
Specification process: User pull & technology push 
CUbRIK Presentation 
3
The situation today 
 
More and more sources such as images, textsand videos are being digitalized 
 
How can we extract high-level information fromthem? 
 
Harnessing the effectiveness of machines andthe expertise of (expert) crowds 
 
For starters: 3000 images representing thehistory of European integration, more documentsto come soon 
CUbRIK Presentation 
4
5 
History of Europe App 
 Name: HoE App 
 Domain: digital humanities 
 Target users: researchers in digital humanities 
Rationale: software-enhanced social hermeneuticsbased on heterogeneous multimedia archives 
Researcher approach 
Researchers manually verify information about historical photos 
Neglects aggregate information from different sources that could lead to new insights 
 CUbRIK solution: 
Full pipeline for the discovery of relationships in heterogeneous data 
Integration of human and machine computation 
Visualization of relationships 
Discursive interface enabling the mapping of multiple perspectives 
CUbRIK Presentation
6 
Main Challenges 
 The main challenges in the HoE app: 
Detection and identification of identities/places/events in time 
Verification of identities/places/events in time 
Analysis of relationships (e.g. co-occurrences) 
Rights aware crawling and storage 
Verification of provenance and license information 
 Approach: 
Crowd-sourced verification of detected faces (false positives/negatives) 
Verification of identities through/places/events in timesocial networks ofexperts 
Visual knowledge discovery/exploration 
Integrated rights aware crawling and storage 
Integrated license and provenance management 
CUbRIK Presentation
CUbRIKin a nutshell 
CUbRIK Presentation 
7
Pipelining the CUbRIKcomponents: Conflict resolution 
CUbRIK Presentation 
8 
Raw content 
High level features 
(automatic annotations) 
Conflict 
(e.g., “Image contains ‘Romano Prodi’ ” 
Confidence = low) 
? 
Conflict store 
Conflict manager 
Conflict resolution 
task store 
Conflict resolution 
task: conflict, 
required skill, priority, .. 
CUbRIK app for Conflict resolution 
Game 
Q&A 
Crowdtask
Pipelining the CUbRIKcomponents: Human input from click-workers 
Great choice for simple tasks: 
 
Face detection: false positives, false negatives 
 
Monetary motivation, via www.microtask.com 
Poor performance on complex tasks: 
 
Low resolution images 
 
Different angles etc. 
 
Actors recurring over time 
CUbRIK Presentation 
9
Pipelining the CUbRIKcomponents: Human input from experts 
Capable of complex tasks: 
 
In-depth knowledge of key actors 
 
Context knowledge allows inferences 
But: Different motivational models! 
 
Public goods 
 
Reputation 
CUbRIK Presentation 
10
Pipelining the CUbRIKcomponents: Towards a community of experts 
Time for a Demo! 
CUbRIK Presentation 
11
Usage for historians 
 
No one truth in history but interpretation, context and discussion 
 
Therefore need to represent ambivalence, contradictions and discussion 
 
Close ties between data representation (Socialgraph) and their original context (primarysources) 
CUbRIK Presentation 
12
Conclusion& Outlook 
 
Challenges 
 
Whatistruth? Humanitiesvs. Computer Science 
 
Gatheringrequirementsfortoolsthathaven‘tbeendevelopedyet 
 
Engagingcrowds 
 
Image copyrights 
 
Refinementoftheapplication 
 
Additional datasources 
 
Improvementoftheinterface 
 
Integration ofthedifferent components 
CUbRIK Presentation 
13
WWW.CUBRIKPROJECT.EU 
Visituson 
CUbRIK Presentation 
14 
@CUBRIKPROJECT 
Or follow us on Twitter

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Humanist machine interaction with histoGraph

  • 1. CUbRIK Presentation 0 Humanist-Machine Interaction for the digital humanities Building the Social graph of the History of European Integration DHLU 2013 www.cubrikproject.eu
  • 2. About CUbRIK  European Community's Seventh FrameworkProgram FP7-ICT  15 European partners  Multimedia searchprocessing: Puttinghumans in the loop  Demos: History of Europeand Fashion CUbRIK Presentation 1
  • 3. CUbRIK Presentation 2 Why CUbRIK approach  Human in the loop added value: Verification of identities/places/events ambiguous and temporal onlypossible by putting humans in the loop Integration of multiple perspectives  CUbRIK as an open toolbox allows follow-up and extension through third parties  “ Vertical”integration: GUI, components, crowdsourcing integrated in a platform
  • 4. Specification process: User pull & technology push CUbRIK Presentation 3
  • 5. The situation today  More and more sources such as images, textsand videos are being digitalized  How can we extract high-level information fromthem?  Harnessing the effectiveness of machines andthe expertise of (expert) crowds  For starters: 3000 images representing thehistory of European integration, more documentsto come soon CUbRIK Presentation 4
  • 6. 5 History of Europe App  Name: HoE App  Domain: digital humanities  Target users: researchers in digital humanities Rationale: software-enhanced social hermeneuticsbased on heterogeneous multimedia archives Researcher approach Researchers manually verify information about historical photos Neglects aggregate information from different sources that could lead to new insights  CUbRIK solution: Full pipeline for the discovery of relationships in heterogeneous data Integration of human and machine computation Visualization of relationships Discursive interface enabling the mapping of multiple perspectives CUbRIK Presentation
  • 7. 6 Main Challenges  The main challenges in the HoE app: Detection and identification of identities/places/events in time Verification of identities/places/events in time Analysis of relationships (e.g. co-occurrences) Rights aware crawling and storage Verification of provenance and license information  Approach: Crowd-sourced verification of detected faces (false positives/negatives) Verification of identities through/places/events in timesocial networks ofexperts Visual knowledge discovery/exploration Integrated rights aware crawling and storage Integrated license and provenance management CUbRIK Presentation
  • 8. CUbRIKin a nutshell CUbRIK Presentation 7
  • 9. Pipelining the CUbRIKcomponents: Conflict resolution CUbRIK Presentation 8 Raw content High level features (automatic annotations) Conflict (e.g., “Image contains ‘Romano Prodi’ ” Confidence = low) ? Conflict store Conflict manager Conflict resolution task store Conflict resolution task: conflict, required skill, priority, .. CUbRIK app for Conflict resolution Game Q&A Crowdtask
  • 10. Pipelining the CUbRIKcomponents: Human input from click-workers Great choice for simple tasks:  Face detection: false positives, false negatives  Monetary motivation, via www.microtask.com Poor performance on complex tasks:  Low resolution images  Different angles etc.  Actors recurring over time CUbRIK Presentation 9
  • 11. Pipelining the CUbRIKcomponents: Human input from experts Capable of complex tasks:  In-depth knowledge of key actors  Context knowledge allows inferences But: Different motivational models!  Public goods  Reputation CUbRIK Presentation 10
  • 12. Pipelining the CUbRIKcomponents: Towards a community of experts Time for a Demo! CUbRIK Presentation 11
  • 13. Usage for historians  No one truth in history but interpretation, context and discussion  Therefore need to represent ambivalence, contradictions and discussion  Close ties between data representation (Socialgraph) and their original context (primarysources) CUbRIK Presentation 12
  • 14. Conclusion& Outlook  Challenges  Whatistruth? Humanitiesvs. Computer Science  Gatheringrequirementsfortoolsthathaven‘tbeendevelopedyet  Engagingcrowds  Image copyrights  Refinementoftheapplication  Additional datasources  Improvementoftheinterface  Integration ofthedifferent components CUbRIK Presentation 13
  • 15. WWW.CUBRIKPROJECT.EU Visituson CUbRIK Presentation 14 @CUBRIKPROJECT Or follow us on Twitter