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June 6, 2012
                                                                                      www.know-center.at




                     Commercially empowered
                     Linked Open Data Ecosystems in Research


                     http://code-research.eu/



                     Prof. Dr. Stefanie Lindstaedt




© Know-Center 2012                                   gefördert durch das Kompetenzzentrenprogramm
Key Facts
STREP, 2.4 M€ Budget, May 2012 - April 2014

Research Partners
   unstructured information analysis
   distributed databases
   semantic technologies
   visual analytics
Company Partners
   13 TB of research publications
   2 million light-weight ontologies
   steadily growing user community in the millions
                                                     2
   successful in web business strategies
                                                     © Know-Center 2011
The Vision …
nani gigantum humeris insidentes
                                    [Greek Mythology]




                        Dwarfs standing on
                          the shouldes of giants
                           Research builds on
                           past insights
                           We share knowledge
                           to create new knowledge




                                   [Isaac Newton, 1676]
                                                          3

                                                          © Know-Center 2011
The Reality ….



Covered under a pile of paper
.. with varying quality
.. with contradicting facts
.. with missing data


Timothy G. Armstrong, Alistair Moffat, William Webber,
Justin Zobel: Improvements that don't add up: ad-hoc
retrieval results since 1998. CIKM 2009: 601-610




     Can we do better?
                                                         4

                                                         © Know-Center 2011
Yes, we can ...
            Given textually enCODED
               scientific knowledge, we can
                  Extract facts from research papers
                  Integrate those facts with existing
                  knowledge
                  Make it available for visual analysis
                  Provide annotated data for
                  bootstrapping
                  a data economy
            Focus
                  Empirical observations/facts
                  Linked Open Data
                  Computer Science and Biomedical         5


                  Domain                                  © Know-Center 2011
Challenges

  Training data for text annotation is missing
  Algorithmic quality in extraction,
  disambiguation and querying is low
  Efficent linked data querying and
  aggregation is unsolved
  ...



              Approach
  User engagement (via marketplace concept)
  80/20 Solutions – just enough for getting users interested

                                                               6

                                                               © Know-Center 2011
Marketplace

                      Motivation
                          &
                    Independence




High Quality research has a (high) monetary turnover
Researchers maintain the freedom to market their
  research or make it open access
People can donate, if they find your work interesting


 Increased opportunities for researchers               7

                                                        © Know-Center 2011
Research Results

Crowd-sourcing enabled semantic enrichment &
integration techniques
             for integrating facts contained in
               unstructured information into the LOD cloud

Federated, provenance-enabled querying methods
            for fact discovery in LOD repositories

Web-based visual analysis interfaces
          to support human-based analysis,
             integration, and organization of facts

Socio-economic factors
(roles, revenue models, and value chains)       Fair Trade
              to motivate researchers
               to contribute                                 8

                                                             © Know-Center 2011
12th Int. Conference on Knowledge Technologies
      8th Int. Conference on Semantic Systems
5 to 7 September 2012 | Messe Congress Graz, Austria


        Lory Aroyo, VU Amsterdam, NL
        Social Web & TV
                           Erik Duval, KU Leuven, BE
                           Research 2.0 Infrastructure
       Chris Welty, IBM Watson, USA
       OntoClean

           David Mallon, Bersin & Associates, USA
           High-Impact Learning Culture                  9

                                                         © Know-Center 2011

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EDF2012 - CODE

  • 1. June 6, 2012 www.know-center.at Commercially empowered Linked Open Data Ecosystems in Research http://code-research.eu/ Prof. Dr. Stefanie Lindstaedt © Know-Center 2012 gefördert durch das Kompetenzzentrenprogramm
  • 2. Key Facts STREP, 2.4 M€ Budget, May 2012 - April 2014 Research Partners unstructured information analysis distributed databases semantic technologies visual analytics Company Partners 13 TB of research publications 2 million light-weight ontologies steadily growing user community in the millions 2 successful in web business strategies © Know-Center 2011
  • 3. The Vision … nani gigantum humeris insidentes [Greek Mythology] Dwarfs standing on the shouldes of giants Research builds on past insights We share knowledge to create new knowledge [Isaac Newton, 1676] 3 © Know-Center 2011
  • 4. The Reality …. Covered under a pile of paper .. with varying quality .. with contradicting facts .. with missing data Timothy G. Armstrong, Alistair Moffat, William Webber, Justin Zobel: Improvements that don't add up: ad-hoc retrieval results since 1998. CIKM 2009: 601-610 Can we do better? 4 © Know-Center 2011
  • 5. Yes, we can ... Given textually enCODED scientific knowledge, we can Extract facts from research papers Integrate those facts with existing knowledge Make it available for visual analysis Provide annotated data for bootstrapping a data economy Focus Empirical observations/facts Linked Open Data Computer Science and Biomedical 5 Domain © Know-Center 2011
  • 6. Challenges Training data for text annotation is missing Algorithmic quality in extraction, disambiguation and querying is low Efficent linked data querying and aggregation is unsolved ... Approach User engagement (via marketplace concept) 80/20 Solutions – just enough for getting users interested 6 © Know-Center 2011
  • 7. Marketplace Motivation & Independence High Quality research has a (high) monetary turnover Researchers maintain the freedom to market their research or make it open access People can donate, if they find your work interesting  Increased opportunities for researchers 7 © Know-Center 2011
  • 8. Research Results Crowd-sourcing enabled semantic enrichment & integration techniques  for integrating facts contained in unstructured information into the LOD cloud Federated, provenance-enabled querying methods  for fact discovery in LOD repositories Web-based visual analysis interfaces  to support human-based analysis, integration, and organization of facts Socio-economic factors (roles, revenue models, and value chains) Fair Trade  to motivate researchers to contribute 8 © Know-Center 2011
  • 9. 12th Int. Conference on Knowledge Technologies 8th Int. Conference on Semantic Systems 5 to 7 September 2012 | Messe Congress Graz, Austria Lory Aroyo, VU Amsterdam, NL Social Web & TV Erik Duval, KU Leuven, BE Research 2.0 Infrastructure Chris Welty, IBM Watson, USA OntoClean David Mallon, Bersin & Associates, USA High-Impact Learning Culture 9 © Know-Center 2011