History of Europe A case study in digital humanities

Agenda

•  The CVCE

•  What are the Digital Humanities?

•  The DHLab at the CVCE

•  Vision: From image collection to Social Graph

•  The CUbRIK approach

•  Demo

•  Challenges, Lessons learned & Outlook

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www.cvce.eu

09/04/2014 – History of Europe. A case study in digital humanities Dr.-Ing. Lars Wieneke, Head of Information & Technology, CVCE Luxembourg

www.cvce.eu  

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www.cvce.eu

09/04/2014 – History of Europe. A case study in digital humanities Dr.-Ing. Lars Wieneke, Head of Information & Technology, CVCE Luxembourg

www.cvce.eu  

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www.cvce.eu

09/04/2014 – History of Europe. A case study in digital humanities Dr.-Ing. Lars Wieneke, Head of Information & Technology, CVCE Luxembourg

www.cvce.eu  

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What are the digital humanities?

„[…] the issue would be not how much computing we need for getting the answers, but how much computer science needs us to ask the right questions.“ http://whatisdigitalhumanities.com, Domenico Fiormonte, Université Roma Tre

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What are the Digital Humanities?

Digital Humanities is the application of computational methods and tools for the humanities   but

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What are the Digital Humanities? Challenges

F.Kapplan, EPF Lausanne Venice  Fall  Digital  Humani3es  School  2013  

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What are the Digital Humanities? Challenges

F.Kapplan, EPF Lausanne Venice  Fall  Digital  Humani3es  School  2013  

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The DHLab at the CVCE

European  Integra3on  Studies  Humani'es  

Development  &    

Opera3ons  

DHLab  

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Our vision: Building a social graph from image collections

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Building a social graph from image collections

Building a social graph from image collections

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The CUbRIK Approach

The CUbRIK approach

•  European Community's Seventh Framework Program FP7-ICT

•  15 European partners •  Multimedia search

processing: Putting humans in the loop

•  Combination of human and machine computation

16 Lars Wieneke, CVCE, Luxembourg

The CUbRIK approach: four pillars

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Researcher  Requirements  

En3ty  Repository  

Efficient  Indexa3on  Process  

Toolchain  for  visualiza3on  and  analysis  

Requirements  

User  pull  

Technology  push  

Sourcing researcher requirements

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Sourcing researcher requirements

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Selection of target user group

First draft of the app scenario

Feedback on technical scope

Exploratory interviews

(daily work practices)Second draft of the

app scenario

Focus group(user needs and app

scenarios) Feedback on technical feasability

Lessons learned:issues and features

Specification

Implementation 1. demonstrator

Workshop: Review of app and features

Revised specification

Implementation 2. demonstrator

Evaluation and test

Stage 1

Stage 2

Stage 3

Stage 4

Stage 5

Users Requirements Technology

Users Requirements Technology

Building an Entity Repository

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Efficient indexation

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Raw content 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

Efficient indexation

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Face detection

Face identification

Clickworkers

Crowd Face position

validation

Expert Crowd

Expert validation

Collection ingestion

Social Graph creation

SMILA  

Demo

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Challenges

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•  Main challenges –  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 –  Truth and provenance

•  Approach –  Crowd-sourced verification of detected faces (false positives/negatives) –  Verification of identities through/places/events in time social networks of experts –  Visual knowledge discovery/exploration –  Integrated rights aware crawling and storage –  Integrated license and provenance management

Lessons learned

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•  No one truth in history but interpretation, context and discussion

•  Therefore need to represent ambivalence, contradictions and discussion

•  Close ties between data representation (Social graph) and their original

context (primary sources)

Outlook

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•  Integration of other document types

•  Improvement of the interface

•  Pre-filtering of identities

•  Gamification and social reputation for expert annotation

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Thank you for listening

29/09/2011 – Title

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