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The Global Brain: Digital Transformations of Research<br />Eric T. Meyer and Ralph Schroeder<br />
The OeSS Project                     2005-2011<br />Oxford e-Social Science Project<br />Oxford<br />Internet<br />Institu...
OeSS Researcher Disciplines<br />Visualization Source: Boyack, Klavens & Borner (2005) Mapping the Backbone of Science. Sc...
Collaborative<br />Links<br />Oxford<br />
Empirical Social Science Approaches<br />
Reconfiguring Access<br />Source: Dutton (2010). Reconfiguring Access in Research: Information.<br />Expertise, and Experi...
Why is science and research growing more collaborative?<br />
Is technology driving it?<br />
Or are there big scientific questions that cannot be answered otherwise?<br />
Source:  Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge.  Jo...
Novel Features of the Online System<br /><ul><li>Scientific communication via many channels, but also a ‘system’
There is no single discipline (information science, media studies, science studies) which captures the sociology of online...
Measurement is possible in new ways and fields become visible
e-Research, defined as distributed and collaborative tools and data for knowledge production, can be mapped (using labels)...
Metrics will increasingly be used, also for science and research policymakers
There are new gatekeepers, but also struggles for visibility within a limited attention space</li></li></ul><li>Novel Feat...
There is no single discipline (information science, media studies, science studies) which captures the sociology of online...
Measurement is possible in new ways and fields become visible
e-Research, defined as distributed and collaborative tools and data for knowledge production, can be mapped (using labels)...
Metrics will increasingly be used, also for science and research policymakers
There are new gatekeepers, but also struggles for visibility within a limited attention space</li></li></ul><li>
The importance of research technologies<br />Technological instruments drive scientific advance (not the other way around)...
Networked Computing (shared, collaborative tools)<br />Types of Manipulation performed:<br /><ul><li> Pooling computing power
 High-throughput Analysis
 Resource repositories</li></ul>Research output, scientific knowledge <br /><ul><li>Type:
 Catalogue
Resource
Analysis
?</li></ul>Research Technology<br />Digital Data or other research materials <br />Types of research material:<br /><ul><l...
Datasets
Visualization
Text
Sensor Data</li></li></ul><li>Social:<br />Programmes<br />Technical:<br />Networks<br />Macro:<br />Grids, Shared Computi...
Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences.  Paper presented at th...
Source:  Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge.  Jo...
Visibility<br />Source:  Meyer, E.T., Park, H-W., Schroeder, R. (2009). Mapping Global e-Research: Scientometrics and Webo...
Source: Meyer, E.T., Park, H-W., Schroeder, R. (2009). Mapping Global e-Research: Scientometrics and Webometrics.  Proceed...
Source: Dutton, W. H., & Meyer, E. T. (2009). Experience with New Tools and Infrastructures of Research: An exploratory st...
Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge.  Jou...
Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences.  Paper presented at th...
Source:  Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge.  Jo...
Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences.  Paper presented at th...
Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences.  Paper presented at th...
Source: S.  Wuchty et al., (2007). The Increasing Dominance of Teams in Production of Knowledge.  Science  316, 1036 -1039...
Or are there big scientific questions that cannot be answered otherwise?<br />
Cases<br />SPLASH: Structure of Populations, Levels of Abundance, and Status of Humpbacks<br />GAIN: Genetic Association I...
Photo-identification<br />Humpback whales<br />
GAIN: <br />Genetic Association<br />Information Network<br />
Data needed to answer key questions for the scientists<br /><ul><li>1985-1997: Family association / linkage studies
250-300 samples (4 sites)
1997-2007: Family association / linkage studies
1000-1500 samples, 10 K SNPs (13 sites)
2007-2009: Genome wide association studies
3000-5000 samples, 1.2 M SNPs (Multiple multi-site studies combined)
2010+: Whole genome studies
30,000 samples, Millions of SNPs (World-wide collaborations)
Future: Sequencing of whole genome?</li></li></ul><li>
Particle Physics and EGEE: The world’s largest e-Science collaboration<br />
EGEE<br />Enabling Grids for e-Science<br />CERN<br />’Big Science’ <br />100+ research groups from many scientific domain...
Particle Physics and EGEE<br />LHC computing grid highly distributed and multi-tiered<br />Petabytes of data, 100,000s CPU...
Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203<br />
Source: CERN, CMS-PHO-GEN-2007-031-1, http://cdsweb.cern.ch/record/1274849<br />
Particle Physics and EGEE<br />The Large Hadron Collider, the most powerful particle accelerator<br />Searching for Higgs ...
EGEE<br />Other disciplines: a need for high-performance computing and shared computing resources (processing vs. storing)...
e-Research in Sweden – New ways of sharing data in the social and health sciences<br />
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OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder

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Presentation for the 2010 Oxford Internet Institute Summer Doctoral Programme on e-Research.

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  • Similar to previous but for search terms
  • Included to show field differences (particularly between social science and comp sci), which underscores how google-ability differs by field
  • Point out dis-intermediation / re-intermediation aspects of online distribution / dominance by Google
  • Transcript of "OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder"

    1. 1. The Global Brain: Digital Transformations of Research<br />Eric T. Meyer and Ralph Schroeder<br />
    2. 2. The OeSS Project 2005-2011<br />Oxford e-Social Science Project<br />Oxford<br />Internet<br />Institute<br />Oxford<br />e-Research<br />Centre<br />Institute for <br />Science, Innovation <br />and Society <br />at<br />Saïd Business School<br />
    3. 3. OeSS Researcher Disciplines<br />Visualization Source: Boyack, Klavens & Borner (2005) Mapping the Backbone of Science. Scientometrics 64(3): 351-374.<br />
    4. 4. Collaborative<br />Links<br />Oxford<br />
    5. 5. Empirical Social Science Approaches<br />
    6. 6. Reconfiguring Access<br />Source: Dutton (2010). Reconfiguring Access in Research: Information.<br />Expertise, and Experience. In Dutton & Jeffreys (eds) World Wide Research:<br />Reshaping the Sciences and Humanities. The MIT Press.<br />
    7. 7. Why is science and research growing more collaborative?<br />
    8. 8. Is technology driving it?<br />
    9. 9. Or are there big scientific questions that cannot be answered otherwise?<br />
    10. 10. Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Journal of Informetrics 3(3):246-260 <br />
    11. 11. Novel Features of the Online System<br /><ul><li>Scientific communication via many channels, but also a ‘system’
    12. 12. There is no single discipline (information science, media studies, science studies) which captures the sociology of online knowledge
    13. 13. Measurement is possible in new ways and fields become visible
    14. 14. e-Research, defined as distributed and collaborative tools and data for knowledge production, can be mapped (using labels) by means of scientometrics and web presence
    15. 15. Metrics will increasingly be used, also for science and research policymakers
    16. 16. There are new gatekeepers, but also struggles for visibility within a limited attention space</li></li></ul><li>Novel Features of the Online System<br /><ul><li>Scientific communication via many channels, but also a ‘system’
    17. 17. There is no single discipline (information science, media studies, science studies) which captures the sociology of online knowledge
    18. 18. Measurement is possible in new ways and fields become visible
    19. 19. e-Research, defined as distributed and collaborative tools and data for knowledge production, can be mapped (using labels) by means of scientometrics and web presence
    20. 20. Metrics will increasingly be used, also for science and research policymakers
    21. 21. There are new gatekeepers, but also struggles for visibility within a limited attention space</li></li></ul><li>
    22. 22. The importance of research technologies<br />Technological instruments drive scientific advance (not the other way around)<br />research technologies are ‘generic’, ‘open-ended general purpose devices’<br />e-Research provides examples of tools shared between disciplines and with globalizing ambitions<br />Networked tools and digitized research materials combine to produce manipulated data and resources as output<br />
    23. 23. Networked Computing (shared, collaborative tools)<br />Types of Manipulation performed:<br /><ul><li> Pooling computing power
    24. 24. High-throughput Analysis
    25. 25. Resource repositories</li></ul>Research output, scientific knowledge <br /><ul><li>Type:
    26. 26. Catalogue
    27. 27. Resource
    28. 28. Analysis
    29. 29. ?</li></ul>Research Technology<br />Digital Data or other research materials <br />Types of research material:<br /><ul><li>Images
    30. 30. Datasets
    31. 31. Visualization
    32. 32. Text
    33. 33. Sensor Data</li></li></ul><li>Social:<br />Programmes<br />Technical:<br />Networks<br />Macro:<br />Grids, Shared Computing<br />Aggregation<br />Disembedding<br />Social:<br />Disciplines, interorganizational collaboration<br />Technical:<br />Discipline or project specific networked tools<br />Meso:<br />Institutional<br />Social:<br />Research organizations<br />Technical:<br />Interfaces and locally accessible resources<br />Micro:<br />Users and their Tools<br />Infrastructure<br />Reembedding<br />
    34. 34. Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences. Paper presented at the 104th American Sociological Association Annual Meeting, August 8-11, San Francisco, California.<br />
    35. 35. Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Journal of Informetrics 3(3):246-260 <br />
    36. 36. Visibility<br />Source: Meyer, E.T., Park, H-W., Schroeder, R. (2009). Mapping Global e-Research: Scientometrics and Webometrics. Proceedings of the 5th <br />International Conference on e-Social Science, June 24-26, Cologne, Germany.<br />
    37. 37. Source: Meyer, E.T., Park, H-W., Schroeder, R. (2009). Mapping Global e-Research: Scientometrics and Webometrics. Proceedings of the 5th International Conference on e-Social Science, June 24-26, Cologne, Germany.<br />
    38. 38. Source: Dutton, W. H., & Meyer, E. T. (2009). Experience with New Tools and Infrastructures of Research: An exploratory study of distance from, and attitudes toward, e-Research. Prometheus, 27(3).<br />
    39. 39. Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Journal of Informetrics 3(3):246-260.<br />
    40. 40. Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences. Paper presented at the 104th American Sociological Association Annual Meeting, August 8-11, San Francisco, California.<br />
    41. 41. Source: Meyer, E.T., Schroeder, R. (2009). Untangling the Web of e-Research: Towards a Sociology of Online Knowledge. Journal of Informetrics 3(3):246-260 <br />
    42. 42. Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences. Paper presented at the 104th American Sociological Association Annual Meeting, August 8-11, San Francisco, California.<br />
    43. 43. Source: Schroeder, R., Meyer, E.T. (2009). Gauging the Impact of e-Research in the Social Sciences. Paper presented at the 104th American Sociological Association Annual Meeting, August 8-11, San Francisco, California.<br />
    44. 44. Source: S. Wuchty et al., (2007). The Increasing Dominance of Teams in Production of Knowledge. Science 316, 1036 -1039. <br />The Growth of Teams<br />
    45. 45. Or are there big scientific questions that cannot be answered otherwise?<br />
    46. 46. Cases<br />SPLASH: Structure of Populations, Levels of Abundance, and Status of Humpbacks<br />GAIN: Genetic Association Information Network<br />Meyer, E.T. (2009). Moving from small science to big science: Social and organizational impediments to large scale data sharing. In Jankowski, N. (Ed.), E-Research: Transformation in Scholarly Practice (Routledge Advances in Research Methods series). New York: Routledge.<br />
    47. 47.
    48. 48. Photo-identification<br />Humpback whales<br />
    49. 49.
    50. 50. GAIN: <br />Genetic Association<br />Information Network<br />
    51. 51. Data needed to answer key questions for the scientists<br /><ul><li>1985-1997: Family association / linkage studies
    52. 52. 250-300 samples (4 sites)
    53. 53. 1997-2007: Family association / linkage studies
    54. 54. 1000-1500 samples, 10 K SNPs (13 sites)
    55. 55. 2007-2009: Genome wide association studies
    56. 56. 3000-5000 samples, 1.2 M SNPs (Multiple multi-site studies combined)
    57. 57. 2010+: Whole genome studies
    58. 58. 30,000 samples, Millions of SNPs (World-wide collaborations)
    59. 59. Future: Sequencing of whole genome?</li></li></ul><li>
    60. 60. Particle Physics and EGEE: The world’s largest e-Science collaboration<br />
    61. 61. EGEE<br />Enabling Grids for e-Science<br />CERN<br />’Big Science’ <br />100+ research groups from many scientific domains<br />User forums<br />A ’project’, a – or the – European and global infrastructure?<br />A federation of projects<br />
    62. 62. Particle Physics and EGEE<br />LHC computing grid highly distributed and multi-tiered<br />Petabytes of data, 100,000s CPUs<br />Memoranda of understanding about the uses of computing resources<br />
    63. 63. Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203<br />
    64. 64. Source: CERN, CMS-PHO-GEN-2007-031-1, http://cdsweb.cern.ch/record/1274849<br />
    65. 65. Particle Physics and EGEE<br />The Large Hadron Collider, the most powerful particle accelerator<br />Searching for Higgs Boson <br />The largest e-Science collaboration worldwide, organizationally and technically<br />Enabling Grids for E-Science (EGEE): a European Grid moves beyond Europe and beyond physics<br />Does the model of physics transfer to other forms of research collaboration?<br />Reshapes the nature of collaboration<br />
    66. 66. EGEE<br />Other disciplines: a need for high-performance computing and shared computing resources (processing vs. storing)<br />A common middleware (gLite)?<br />A common organizational model (MOU’s, how to share data for publishing)<br />How to keep momentum going? The global geopolitics of e-Science, in physics and beyond (EGEE can’t fail, tries to embrace other projects, sets and follows standards, and competes and collaborates)<br />
    67. 67. e-Research in Sweden – New ways of sharing data in the social and health sciences<br />
    68. 68. e-Research in Sweden<br />Sweden has a major e-Research initiative<br />’Universal’ personal identification<br />Uniquely powerful datasets (e.g. twin registry)<br />UK (ID cards, NHS) and US parallels?<br />Significance: If Swedes can’t do it, no one can? <br />Future possibilities: public health via mobile phones?<br />
    69. 69. Preventing Flu via Mobile Phones?<br />
    70. 70. e-Research in Sweden<br />Use of population data in a ’transparent’ society with high trust between people, authorities and researchers…<br />…but, implementation of secure distributed access and ’incidents’ creating public concerns<br />Reshapes how data are collected<br />
    71. 71. SwissBioGrid - Shared computing power for biomedicine<br />
    72. 72. SwissBioGrid<br />Aims: high throughput analysis of proteomics data, virtual screening of possible drugs for dengue fever<br />Collaborators: Swiss Institute of Bioinformatics, Novartis, Swiss National Supercomputing Centre<br />Using the spare capacity of Linux clusters and PCs<br />
    73. 73. SwissBioGrid: A Mixture ofClusters and PCs<br />ETHZ Hreidar<br />(Sun Grid Engine)<br />SIB Vital-IT (Platform LSF)<br /> NorduGRID/<br /> ARC<br />UniZH Matterhorn<br />(Sun Grid Engine)<br />UniBS BC2 cluster<br />(Platform LSF)<br />ProtoGRID<br />Metascheduler<br />UniBS/FMI PC farms<br />CSCS <br /> - Ticino Cluster (Itanium, LSF) <br /> - Terrane Cluster (PS 5, PBS)<br /> - Sun Cluster (PBS)<br />
    74. 74. SwissBioGrid<br />Working across the academic – commercial divide<br />Demonstrates that PC clusters can usefully be deployed in biomedicine…<br />…but a challenge to embed shared computing resources without a larger national Grid<br />Reshapes how data is analysed<br />
    75. 75. A Collaborative Wiki for Literary Annotation: The Pynchon Wiki<br />
    76. 76. The Pynchon Wiki<br />A Wiki for annotating a contemporary American novel<br />A 1085 page novel is annotated between November 2006 and early 2007<br />The equivalent single author annotation in book form takes longer than a decade<br />A flexible, highly motivating, distributed collaborative effort – a model for other forms of online collaboration?<br />
    77. 77. The Pynchon Wiki<br />A notoriously reclusive novelist;<br />Author of<br />Gravity’s Rainbow, annotated in book form<br />Against the Day, annotated in Wiki form<br />Arcana integral to story-lines<br />
    78. 78.
    79. 79.
    80. 80. The Pynchon Wiki:Charting Pynchon Online Activity<br />Anticipation<br />Annotation<br />And what’s next?<br />
    81. 81. Weisenburger vs. the Wiki on Pynchon<br />Comparison of book and wiki annotation efforts<br />Source: Schroeder, R., & Besten, M. D. (2008). Literary Sleuths Online: e-Research collaboration on the Pynchon Wiki. Information, Communication & Society, 11(2), 167 - 187.<br />
    82. 82. The Pynchon Wiki:Wiki Edits over Time<br />
    83. 83. The Pynchon Wiki<br />A race to finish the ‘detective work’<br />Encouraging amateur contribution and learning from other contributors<br />A model for self-organized collaboration?<br />‘Finalization’ of reference work or endless discussion?<br />Reshaping how scholarly resources are distributed, and how we collaborate<br />
    84. 84. e-Research as research technologies?<br />Universality in the ’adoption by an end-user audience of a generic instrument entails the audience’s integration of protocols which make the instrument effective’ (middleware? Metadata? Users?...)<br />Momentum at the policy level, at the infrastructure level, at the level of ’passports’, or end-user adoption <br />An ’openness’ movement<br />Resources or tools?<br />Will e-Research become ’invisible’ (but also higher ’visibility’ when scientific output is increasingly online)<br />
    85. 85. Implications of Research Technologies<br />Tools drive science, but they impose new practices on researchers (collaboration, digitization, tool use)<br />Aim is to enhance systems? or to advance our understanding of innovation and science?<br />e-Research has different levels – with different forms of momentum and barriers<br />
    86. 86. Design and Policy Implications I <br />plan user requirements and user uptake before embarking on system development<br />ensure that infrastructure and resources are in place to sustain project beyond system completion<br />interoperability and standards for software, resources and tools<br />motivate and reward contributions to shared resources and tools<br />are efforts being duplicated, and is there a sufficient user base for all systems?<br />
    87. 87. Design and Policy Implications II<br />identify a niche where research technologies are likely to act as ‘passports’ between disciplines and applications<br />collaborative agreements are in place, and project management<br />Ethical and legal issues in data, resource and tool use and sharing (including IP issues) <br />Visibility and transparency <br />Open access strategy<br />
    88. 88. So what?<br />Quality of Research<br />Nature of Research: Artisan or Knowledge Worker; Embedded or Mediated Observer<br />Privacy and Confidentiality<br />Ownership, IPR, and Openness<br />Distribution of Expertise: Greater Diversity or a Winner-Takes-All?<br />
    89. 89. Quality of Research<br />Intermediation and Disintermediation<br />Intermediation<br />Disintermediation<br />
    90. 90. Source: Meyer & Schroeder (2009). The World Wide Web of Research and Access to Knowledge. Journal of Knowledge Management Research and Practice 7 (3):218-233.<br />
    91. 91. O e S S<br />Oxford e-Social Science Project<br />http://www.oii.ox.ac.uk/microsites/oess/<br />
    92. 92. Oxford Internet InstituteUniversity of Oxford<br />Eric T. Meyereric.meyer@oii.ox.ac.ukhttp://people.oii.ox.ac.uk/meyer <br />Ralph Schroederralph.schroeder@oii.ox.ac.uk http://people.oii.ox.ac.uk/schroeder<br />Oxford e-Social Science Project<br />
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