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My Unfunded Projects
Victor de Boer
WAI meeting 21-10-2013
img: Flickr/Kalexanderson
My Unfunded Projects
1. LaVAIK: Linking and Visualising Aid information Kit
2. ICONS
3. Dance project
1. ICONS: Interaction design for low-
literacy communities
• Integrate local community radios and mobile ICT for
knowledge sharing
• Better support and integrate local languages in voice-
based services
– Development of appropriate speech elements (text-
to-speech and Speech recognition)
• Develop a free and open source toolbox for local
developers.
– Investigate self-sustainability
– Develop appropriate business models
– In collaboration with local communities.
Feature phones
Icon-based interaction
Icon-based interaction
NCR ATM interface for illiterate 'grammar' - ISOTYPE by Otto Neurath available at
http://imaginarymuseum.org/MHV/PZImhv/NeurathPictureLanguage.html
ICONS
What happened?
• FP7-ICT-2011-9
– International partnership building and support to dialogues
– April 2012
– 10 partners
– 104 pages
Particip
ant
Participant organisation name Country
1 (c) GEIE ERCIM France
2 (sci.c.) World Wide Web Foundation Switzerland
3 Telecom
4 Council for Scientific and Industrial
Research
5 VU University Amsterdam Neth.
6 Sahel Eco Mali
7 Université Cheikh Anta Diop de Dakar Senegal
8 Di Maquina UK
9 VU University Amsterdam Neth.
10 Nokia Finland
• Did not pass first round
– Not detailed enough on Req
elicitation methodology
– Management structure /
budget issues
2. LaVAIK: LINKING AND VISUALISING
AID INFORMATION KIT
LaVAIK: LINKING AND VISUALISING AID INFORMATION KIT
• International Aid Transparency Initiative (IATI)
• IATI registry (190+ organisations)
– http://iatiregistry.org
“IATI is a voluntary, multi-stakeholder initiative that seeks
to improve the transparency of aid in order to increase
its effectiveness in tackling poverty.”
“IATI Data Registry, the place to find IATI raw data in XML format.”
IATI Stakeholders
• Funders
o Where is the money of my organisation spent?
o Where do other organisations spend their money?
• Governments
o How much money is spent in my country?
o What are the budgets or planned disbursements for my country?
• Public
o Where is my tax money going?
o What are the organisations doing with my donations?
• Locals
o What organisations are working in my area?
o What projects are currently going on in my area?
Linked Data for IATI
Kasper Brandt, MSc Artificial Intelligence
1. A IATI Linked Data model is created based on requirements
elicited from interviews with experts.
2. Datasets are linked to the Linked Data model based on IATI
experts’ needs.
3. Linked Data applications are created, showing that linking IATI
data adds value to the data and is able to fulfill the needs of IATI
users.
4. Our approach and requirements are reusable for converting an
open dataset to a Linked Data model in general
Linked Data model - Triple store
• Triples loaded into a ClioPatria triple store:
o http://semanticweb.cs.vu.nl/iati/
o Sparql endpoint
– Dereferenceable URIs (!)
(http://purl.org/collections/iati/codelist/Sector/11420)
• Total number of triples: 36,629,017
• Total number of named graphs: 4,790
o Largest activities graph is UNOPS containing 1,231,896 triples
RDFLib
Python RDF/Turtle
Linking datasets
http://iati2lod.appspot.com
1. We will convert all the IATI
datasets available to Linked
Data.
2. Convert related open datasets
and indicators from UN-Habitat,
Worldbank and OECD to Linked
Data.
3. Generate contextualized links
between produced datasets as
well as existing datasets on the
Web of Data.
– Link to Landportal
– Link to local (Malian) rainfall /
market data
4. Provide a web-based toolkit for
multimodal and interactive
access to the enriched Linked
Aid Data.
UN HAbitat
Worldbank
OECD
Inst. of
Development
Studies LOD
Citizen
Journalism data
Sahel Pluvial
data
RadioMarché
Linked market data IATI data
Project goals
Web interface
What happened?
• Grand Challenges Round 11
– Increasing Interoperability of Social Good Data
– 3 pages
– 4 partners:
• VU
• DANS (Christophe)
• Zimmerman & Zimmerman
• Akvo
• 2700 proposals!
3. Dance project (EXMO, EM2)
Proposal: choreography assistant tool
Sensing
Representation
+
Reasoning
Presentation
generation
• Motion detection
• Floor sensors
• Move recognition
• Dance movement representation
• Dance choreography representation
• Use of background knowledge
• Pattern detection
• Choreography generation
• Visual presentation
• 3-D animation
• Auditory presentation
Sensing
data
Choreography
variation
Presentation
Choreography
Sensing
• Motion capture
– Marker-based
– Marker-less
• Joint rotations, limb
positions etc.
– unintuitive
• Backup: Video
annotation
img: news.stanford.edu
Representation languages of human movement:
Labanotation
Labanotation
LabanXML and Laban Editor
LED Labanotation editor http://donhe.topcities.com/pubs/led.html
Nakamura & Hachimura (2006)
Dance Forms
Benesh
• 7 elementary movements: [plie
(bend), etandre (stretch), releve (rise),
sauter (jump), glisse (glide), tourne
(turn), elancer (dart)]
• Positions: 1st, 2nd, 3rd,.. (left right
croise)
• Facing position (1…8)
• Position in space
• Direction of movement (de cote,
dessous, dessus, en avant, en arriere,
devant, derriere)
• Combinations (100+) pas-de-chat,
pas-de-bourre, piroutte
Cecchetti system
Based on interview with Marije Koning
XML Dance Grammar
Balakrishnan Ramadoss and Kannan Rajkumar. Modeling the Dance Video Semantics using
Regular Tree Automata Fundamenta Informaticae 86 (2008) 175–189 175 IOS Press
Representation and Reasoning
• Multi-tiered model
– Low-level image features
– Atomic movements (Labanotation?)
– Compound movements (100+ movements)
– Emotional content, Socio-cultural layers etc.
• Machine Learning for classification and
pattern detection
– Generative module (automatic choreographer)
Presentation
What happened?
1st try:
– FP-7 Future and Emerging Technologies Open Scheme (FET Open)
• nov 2011
– VUA, UvA (Frank Nack), School of Interactive Arts and Technology –
SFU California, Laboratoire d'Informatique pour la Mécanique et les
Sciences de l'Ingénieur , Palindrome, Unige
– Not accepted (High impact?)
2nd try: More healthcare oriented (VU movement science)
3rd try: NWO Creatieve industrie (2012)
– VU, UVA, Utwente (Vanessa Evers, Ronald Poppen, Dirk Heylen)
– Industry partner…
4th try?
So…
• Not every project gets accepted 
– Re-use some components for talks
• None of these is really dead
– If you’re interested in any one of these, come talk
to me 
v.de.boer@vu.nl

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My unfunded projects WAI talk

  • 1. My Unfunded Projects Victor de Boer WAI meeting 21-10-2013 img: Flickr/Kalexanderson
  • 2.
  • 3. My Unfunded Projects 1. LaVAIK: Linking and Visualising Aid information Kit 2. ICONS 3. Dance project
  • 4. 1. ICONS: Interaction design for low- literacy communities
  • 5. • Integrate local community radios and mobile ICT for knowledge sharing • Better support and integrate local languages in voice- based services – Development of appropriate speech elements (text- to-speech and Speech recognition) • Develop a free and open source toolbox for local developers. – Investigate self-sustainability – Develop appropriate business models – In collaboration with local communities.
  • 6.
  • 8.
  • 10. Icon-based interaction NCR ATM interface for illiterate 'grammar' - ISOTYPE by Otto Neurath available at http://imaginarymuseum.org/MHV/PZImhv/NeurathPictureLanguage.html
  • 11. ICONS
  • 12. What happened? • FP7-ICT-2011-9 – International partnership building and support to dialogues – April 2012 – 10 partners – 104 pages Particip ant Participant organisation name Country 1 (c) GEIE ERCIM France 2 (sci.c.) World Wide Web Foundation Switzerland 3 Telecom 4 Council for Scientific and Industrial Research 5 VU University Amsterdam Neth. 6 Sahel Eco Mali 7 Université Cheikh Anta Diop de Dakar Senegal 8 Di Maquina UK 9 VU University Amsterdam Neth. 10 Nokia Finland • Did not pass first round – Not detailed enough on Req elicitation methodology – Management structure / budget issues
  • 13. 2. LaVAIK: LINKING AND VISUALISING AID INFORMATION KIT
  • 14. LaVAIK: LINKING AND VISUALISING AID INFORMATION KIT • International Aid Transparency Initiative (IATI) • IATI registry (190+ organisations) – http://iatiregistry.org “IATI is a voluntary, multi-stakeholder initiative that seeks to improve the transparency of aid in order to increase its effectiveness in tackling poverty.” “IATI Data Registry, the place to find IATI raw data in XML format.”
  • 15. IATI Stakeholders • Funders o Where is the money of my organisation spent? o Where do other organisations spend their money? • Governments o How much money is spent in my country? o What are the budgets or planned disbursements for my country? • Public o Where is my tax money going? o What are the organisations doing with my donations? • Locals o What organisations are working in my area? o What projects are currently going on in my area?
  • 16. Linked Data for IATI Kasper Brandt, MSc Artificial Intelligence 1. A IATI Linked Data model is created based on requirements elicited from interviews with experts. 2. Datasets are linked to the Linked Data model based on IATI experts’ needs. 3. Linked Data applications are created, showing that linking IATI data adds value to the data and is able to fulfill the needs of IATI users. 4. Our approach and requirements are reusable for converting an open dataset to a Linked Data model in general
  • 17. Linked Data model - Triple store • Triples loaded into a ClioPatria triple store: o http://semanticweb.cs.vu.nl/iati/ o Sparql endpoint – Dereferenceable URIs (!) (http://purl.org/collections/iati/codelist/Sector/11420) • Total number of triples: 36,629,017 • Total number of named graphs: 4,790 o Largest activities graph is UNOPS containing 1,231,896 triples RDFLib Python RDF/Turtle
  • 20. 1. We will convert all the IATI datasets available to Linked Data. 2. Convert related open datasets and indicators from UN-Habitat, Worldbank and OECD to Linked Data. 3. Generate contextualized links between produced datasets as well as existing datasets on the Web of Data. – Link to Landportal – Link to local (Malian) rainfall / market data 4. Provide a web-based toolkit for multimodal and interactive access to the enriched Linked Aid Data. UN HAbitat Worldbank OECD Inst. of Development Studies LOD Citizen Journalism data Sahel Pluvial data RadioMarché Linked market data IATI data Project goals Web interface
  • 21. What happened? • Grand Challenges Round 11 – Increasing Interoperability of Social Good Data – 3 pages – 4 partners: • VU • DANS (Christophe) • Zimmerman & Zimmerman • Akvo • 2700 proposals!
  • 22. 3. Dance project (EXMO, EM2)
  • 23. Proposal: choreography assistant tool Sensing Representation + Reasoning Presentation generation • Motion detection • Floor sensors • Move recognition • Dance movement representation • Dance choreography representation • Use of background knowledge • Pattern detection • Choreography generation • Visual presentation • 3-D animation • Auditory presentation Sensing data Choreography variation Presentation Choreography
  • 24. Sensing • Motion capture – Marker-based – Marker-less • Joint rotations, limb positions etc. – unintuitive • Backup: Video annotation img: news.stanford.edu
  • 25. Representation languages of human movement: Labanotation
  • 27. LabanXML and Laban Editor LED Labanotation editor http://donhe.topcities.com/pubs/led.html Nakamura & Hachimura (2006)
  • 30. • 7 elementary movements: [plie (bend), etandre (stretch), releve (rise), sauter (jump), glisse (glide), tourne (turn), elancer (dart)] • Positions: 1st, 2nd, 3rd,.. (left right croise) • Facing position (1…8) • Position in space • Direction of movement (de cote, dessous, dessus, en avant, en arriere, devant, derriere) • Combinations (100+) pas-de-chat, pas-de-bourre, piroutte Cecchetti system Based on interview with Marije Koning
  • 31. XML Dance Grammar Balakrishnan Ramadoss and Kannan Rajkumar. Modeling the Dance Video Semantics using Regular Tree Automata Fundamenta Informaticae 86 (2008) 175–189 175 IOS Press
  • 32. Representation and Reasoning • Multi-tiered model – Low-level image features – Atomic movements (Labanotation?) – Compound movements (100+ movements) – Emotional content, Socio-cultural layers etc. • Machine Learning for classification and pattern detection – Generative module (automatic choreographer)
  • 34. What happened? 1st try: – FP-7 Future and Emerging Technologies Open Scheme (FET Open) • nov 2011 – VUA, UvA (Frank Nack), School of Interactive Arts and Technology – SFU California, Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur , Palindrome, Unige – Not accepted (High impact?) 2nd try: More healthcare oriented (VU movement science) 3rd try: NWO Creatieve industrie (2012) – VU, UVA, Utwente (Vanessa Evers, Ronald Poppen, Dirk Heylen) – Industry partner… 4th try?
  • 35. So… • Not every project gets accepted  – Re-use some components for talks • None of these is really dead – If you’re interested in any one of these, come talk to me  v.de.boer@vu.nl

Editor's Notes

  1. After Babel (1975)  is a comprehensive study of the subject of language and translation tual challenge proved beyond his capacities. The actual themes range widely and defy conventional taboos: the torment of the gifted when they live among-when they confront-the very great; the experience of sex in different languages; a love for animals greater than for human beings; the costly privilege of exile; a theology of emptiness. Yet a unifying perception underlies this diversity. The best we have or can produce is only the tip of the iceberg. Behind every good book, as in a lit shadow, lies the book which remained unwritten, the one that would have failed better.
  2. Spice this up Relate this to w4ra
  3. Sensing: The environment can be used in different stages of the choreography process. The choreographer can start with a semi-finished dance piece or only have a few dance phrases. The ambient environment detects the current choreography through computer vision, pressure sensors in floor and walls or other modalities. The existing choreography or parts of it are translated into a higher level dance representation language. Creative Reasoning: The current choreography is transferred to the creative reasoning engine in real time. Here, variations on the choreography are generated. This tool can produce new choreography parts varying spatial positioning, the number of performers, variations of dance phrases, repetitions of dance phrases and differences in expressions of movements. Background knowledge about similar or completely different choreographies as well as different dance styles can also be used to modify the choreography. This background knowledge is also stored in the higher level representation language. All operations on the current choreography can be determined by the user, but a more serendipitous use of the tool is also possible. Multiple variations of one choreography can be generated at the same time. Presentation: These newly generated choreographies are then presented to the choreographer. For this, 3-D video images of the new choreographies are projected on the walls of the environment. In this manner, the dancer/choreographer can absorb the variations while moving around the environment and he/she can choose to copy entire dance phrases or incorporate only parts of the suggestions. The ambient environment will detect the new movements in real time, creating a creative closed loop where choreographer and the environment work together to create a new dance piece. The tool can also be used offline. The tool then provides the choreographer with an in depth analysis of the current choreography through a dancer-friendly interface.
  4. Al these systems very academic, can be read by a few, mostly used for archival purposes
  5. Already more at normal level of dancer communication