A Topographical Investigation of Information Generation in Software engineering - PowerPoint PPT Presentation

a geographical analysis of knowledge production in computer science l.
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A Topographical Investigation of Information Generation in Software engineering

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  1. A Geographical Analysis of Knowledge Production in Computer Science Guilherme Vale Menezes Nivio Ziviani Alberto H. F. Laender Virgílio Almeida gmenezes@dcc.ufmg.br nivio@dcc.ufmg.br laender@dcc.ufmg.br virgilio@dcc.ufmg.br Federal University of Minas Gerais - Brazil

  2. Summary • Introduction • Data Gathering • Results • Conclusions LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  3. TheProblem • Study the characteristics of researchers of Computer Science graduate programs • 30 graduate programs in 3 geographic regions • Build collaboration social networks based on DBLP • We use several metrics of collaboration social networks • Giant Component • Clustering Coefficient LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  4. Steps • Comparison between 30 programs in 3 regions • Comparison between 30 Computer Science fields • Study of the interrelationship between fields • Temporal analysis of the 3 regions and the fields LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  5. Collaboration Network Author Collaboration LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  6. Collaborations in DCC-UFMG LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  7. Collaborations in DCC-UFMG LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  8. Summary • Introduction • Data Gathering • Results • Conclusions LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  9. Data Gathering • Part ofour data camefromPerfil-CCproject • ObjectiveofPerfil-CC: studyBrazilianComputerSciencegraduateprograms • A set of 30 programswaschosen • Focus: comparisonwith NorthAmericanprograms • Resultssupportedpublic policies • Data gathered in June 2007 LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  10. BrazilianPrograms PUC-Rio, UFRJ, UFPE, UFMG, USP-SP, USP-SC, UNICAMP, UFRGS 8 graduate programs 391 authors LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  11. Canadianand US Programs British Columbia, Toronto, Waterloo, Brown, CalTech, CMU, Cornell, Harvard, Illinois, MIT, Princeton, Stanford, UC Berkeley, UTexas Austin, Washington, Wisconsin 16 graduate programs 1,262 authors LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  12. French, Swissand UK Programs ETH Zurich, Cambridge U., Imperial College, Oxford U., École Polytechnique, Paris VI 6 graduate programs 611 authors LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  13. Data Gathering • Professors obtained from the departments’ websites • Publications from DBLP Programs: 30 Professors: 2,007 Authors: 76,537 Papers: 352,766 Venues: 2,176 LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  14. VenueClassification • 2,176 wereclassified (byhumans) into 30 fields • Thelistoffieldswasobtainedfrom a poll • ThebrazilianComputerScienceresearchcommunitywasconsulted • 312 researchersidentified 30 differentfields LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  15. ComputerScienceFields LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  16. ComputerScienceFields Algorithms andTheory LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  17. ComputerScienceFields Information Retrieval LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  18. ComputerScienceFields Bioinformatics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  19. Summary • Introduction • Data Gathering • Results • Conclusions LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  20. General Statistics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  21. General Statistics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  22. General Statistics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  23. General Statistics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  24. GiantComponent • A connectedcomponent is amaximumconnectedsubgraph LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  25. GiantComponent • A connectedcomponent is amaximumconnectedsubgraph LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  26. GiantComponent • A connectedcomponent is amaximumconnectedsubgraph • Thelargestconnectedcomponent is thegiantcomponent Giant Component size = 5 / 11 = 0.45 = 45% LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  27. GiantComponent LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  28. GiantComponentinsidePrograms LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  29. ClusteringCoefficient LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  30. ClusteringCoefficient • Clustering coefficient of the network is the average clustering coefficient of its vertexes • The clustering coefficient is a measure of transitivity LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  31. ClusteringCoefficient LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  32. ComputerScienceFields • Clustering Coefficient below the average (87%) for fields closely related to Mathematics • Algorithms and Theory (79%) • Operational Reaseach and Optimization (83%) • Formalisms, Logics and Semantics (83%) LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  33. InterrelationshipbetweenFields LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  34. InterrelationshipbetweenFields LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  35. GiantComponentEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  36. GiantComponentEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  37. GiantComponentEvolution Increase in the number of graduate programs in 1990s LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  38. GiantComponentEvolution Increase in government funding LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  39. GiantComponentEvolution A shift in policy: more support to research groups instead of individuals LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  40. GiantComponentEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  41. GiantComponentEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  42. GiantComponentEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  43. EdgesvsVertices LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  44. ClusteringCoefficientEvolution • 2 well-established fields • Computer Architecture • Databases • 2 emerging fields • Bioinformatics • Geoinformatics LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  45. ClusteringCoefficientEvolution LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  46. ClusteringCoefficientEvolution Densification LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  47. Summary • Introduction • Data Gathering • Results • Conclusions LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  48. Conclusions • Analysis of the characteristics of researchers of Computer Science graduate programs LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  49. Conclusions • Analysis of the characteristics of researchers of Computer Science graduate programs • Differences in the collaboration network of Br, Ca-US and Fr-Sw-UK • Giant component • Clustering coefficient LAboratory for Treating INformation (LATIN) – UFMG - Brazil

  50. Conclusions • Analysis of the characteristics of researchers of Computer Science graduate programs • Differences in the collaboration network of Br, Ca-US and Fr-Sw-UK • Giant component • Clustering coefficient • Smaller clustering coefficient for areas more closely related to Mathematics LAboratory for Treating INformation (LATIN) – UFMG - Brazil