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Data Research Vision


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This presentation was presented by Marko Grobelnik (JSI) at the PlanetData project Kick-off Meeting on October 11, 2010 in Palma de Mallorca, Spain.

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Data Research Vision

  1. 1. Marko Grobelnik ( Stefan Institute (, Slovenia
  2. 2. Dealing with data NaturalDatabases Language Machine Social Semantic Web Processing Learning / Information Network Data Mining Retrieval AnalysisStoring / Modelquerying Community Interoperability Text discovery Search
  3. 3.   Integration of three key scientific paradigms ◦  Top-down approaches – model driven   (Semantic Web, KRR, Traditional NLP) ◦  Bottom-up approaches – data driven   (Machine Learning, Data Mining, Social Network Analysis, Information Retrieval, Modern NLP) ◦  Collaborative approaches – community driven   (Web2.0, Social Computing)  …integration of ideas from different paradigms opens possibilities to solve problems which were not easy solvable before
  4. 4.   Research areas (such as IR, KDD, ML, NLP, Usage SemWeb, …) are sub- cubes within the data Quality cube Context Dynamicity Scalability
  5. 5. Can we learnfrom listedtechnologies?
  6. 6. Can we learnfrom listedtechnologies?
  7. 7.   One possible conclusion: ◦  Future lies in uncovered parts of the data cube ◦  …note that items on data cube are changing  Upcoming technology trends combine existing “healthy” technologies as building blocks