OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
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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.

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

OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder Presentation Transcript

  • The Global Brain: Digital Transformations of Research
    Eric T. Meyer and Ralph Schroeder
  • The OeSS Project 2005-2011
    Oxford e-Social Science Project
    Oxford
    Internet
    Institute
    Oxford
    e-Research
    Centre
    Institute for
    Science, Innovation
    and Society
    at
    Saïd Business School
  • OeSS Researcher Disciplines
    Visualization Source: Boyack, Klavens & Borner (2005) Mapping the Backbone of Science. Scientometrics 64(3): 351-374.
  • Collaborative
    Links
    Oxford
  • Empirical Social Science Approaches
  • Reconfiguring Access
    Source: Dutton (2010). Reconfiguring Access in Research: Information.
    Expertise, and Experience. In Dutton & Jeffreys (eds) World Wide Research:
    Reshaping the Sciences and Humanities. The MIT Press.
  • Why is science and research growing more collaborative?
  • Is technology driving it?
  • Or are there big scientific questions that cannot be answered otherwise?
  • 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
  • Novel Features of the Online System
    • 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 knowledge
    • 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) by means of scientometrics and web presence
    • 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
  • Novel Features of the Online System
    • 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 knowledge
    • 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) by means of scientometrics and web presence
    • 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
  • The importance of research technologies
    Technological instruments drive scientific advance (not the other way around)
    research technologies are ‘generic’, ‘open-ended general purpose devices’
    e-Research provides examples of tools shared between disciplines and with globalizing ambitions
    Networked tools and digitized research materials combine to produce manipulated data and resources as output
  • Networked Computing (shared, collaborative tools)
    Types of Manipulation performed:
    • Pooling computing power
    • High-throughput Analysis
    • Resource repositories
    Research output, scientific knowledge
    • Type:
    • Catalogue
    • Resource
    • Analysis
    • ?
    Research Technology
    Digital Data or other research materials
    Types of research material:
    • Images
    • Datasets
    • Visualization
    • Text
    • Sensor Data
  • Social:
    Programmes
    Technical:
    Networks
    Macro:
    Grids, Shared Computing
    Aggregation
    Disembedding
    Social:
    Disciplines, interorganizational collaboration
    Technical:
    Discipline or project specific networked tools
    Meso:
    Institutional
    Social:
    Research organizations
    Technical:
    Interfaces and locally accessible resources
    Micro:
    Users and their Tools
    Infrastructure
    Reembedding
  • 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.
  • 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
  • Visibility
    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.
  • 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.
  • 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).
  • 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.
  • 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.
  • 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
  • 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.
  • 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.
  • Source: S. Wuchty et al., (2007). The Increasing Dominance of Teams in Production of Knowledge. Science 316, 1036 -1039.
    The Growth of Teams
  • Or are there big scientific questions that cannot be answered otherwise?
  • Cases
    SPLASH: Structure of Populations, Levels of Abundance, and Status of Humpbacks
    GAIN: Genetic Association Information Network
    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.
  • Photo-identification
    Humpback whales
  • GAIN:
    Genetic Association
    Information Network
  • Data needed to answer key questions for the scientists
    • 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?
  • Particle Physics and EGEE: The world’s largest e-Science collaboration
  • EGEE
    Enabling Grids for e-Science
    CERN
    ’Big Science’
    100+ research groups from many scientific domains
    User forums
    A ’project’, a – or the – European and global infrastructure?
    A federation of projects
  • Particle Physics and EGEE
    LHC computing grid highly distributed and multi-tiered
    Petabytes of data, 100,000s CPUs
    Memoranda of understanding about the uses of computing resources
  • Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203
  • Source: CERN, CMS-PHO-GEN-2007-031-1, http://cdsweb.cern.ch/record/1274849
  • Particle Physics and EGEE
    The Large Hadron Collider, the most powerful particle accelerator
    Searching for Higgs Boson
    The largest e-Science collaboration worldwide, organizationally and technically
    Enabling Grids for E-Science (EGEE): a European Grid moves beyond Europe and beyond physics
    Does the model of physics transfer to other forms of research collaboration?
    Reshapes the nature of collaboration
  • EGEE
    Other disciplines: a need for high-performance computing and shared computing resources (processing vs. storing)
    A common middleware (gLite)?
    A common organizational model (MOU’s, how to share data for publishing)
    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)
  • e-Research in Sweden – New ways of sharing data in the social and health sciences
  • e-Research in Sweden
    Sweden has a major e-Research initiative
    ’Universal’ personal identification
    Uniquely powerful datasets (e.g. twin registry)
    UK (ID cards, NHS) and US parallels?
    Significance: If Swedes can’t do it, no one can?
    Future possibilities: public health via mobile phones?
  • Preventing Flu via Mobile Phones?
  • e-Research in Sweden
    Use of population data in a ’transparent’ society with high trust between people, authorities and researchers…
    …but, implementation of secure distributed access and ’incidents’ creating public concerns
    Reshapes how data are collected
  • SwissBioGrid - Shared computing power for biomedicine
  • SwissBioGrid
    Aims: high throughput analysis of proteomics data, virtual screening of possible drugs for dengue fever
    Collaborators: Swiss Institute of Bioinformatics, Novartis, Swiss National Supercomputing Centre
    Using the spare capacity of Linux clusters and PCs
  • SwissBioGrid: A Mixture ofClusters and PCs
    ETHZ Hreidar
    (Sun Grid Engine)
    SIB Vital-IT (Platform LSF)
    NorduGRID/
    ARC
    UniZH Matterhorn
    (Sun Grid Engine)
    UniBS BC2 cluster
    (Platform LSF)
    ProtoGRID
    Metascheduler
    UniBS/FMI PC farms
    CSCS
    - Ticino Cluster (Itanium, LSF)
    - Terrane Cluster (PS 5, PBS)
    - Sun Cluster (PBS)
  • SwissBioGrid
    Working across the academic – commercial divide
    Demonstrates that PC clusters can usefully be deployed in biomedicine…
    …but a challenge to embed shared computing resources without a larger national Grid
    Reshapes how data is analysed
  • A Collaborative Wiki for Literary Annotation: The Pynchon Wiki
  • The Pynchon Wiki
    A Wiki for annotating a contemporary American novel
    A 1085 page novel is annotated between November 2006 and early 2007
    The equivalent single author annotation in book form takes longer than a decade
    A flexible, highly motivating, distributed collaborative effort – a model for other forms of online collaboration?
  • The Pynchon Wiki
    A notoriously reclusive novelist;
    Author of
    Gravity’s Rainbow, annotated in book form
    Against the Day, annotated in Wiki form
    Arcana integral to story-lines
  • The Pynchon Wiki:Charting Pynchon Online Activity
    Anticipation
    Annotation
    And what’s next?
  • Weisenburger vs. the Wiki on Pynchon
    Comparison of book and wiki annotation efforts
    Source: Schroeder, R., & Besten, M. D. (2008). Literary Sleuths Online: e-Research collaboration on the Pynchon Wiki. Information, Communication & Society, 11(2), 167 - 187.
  • The Pynchon Wiki:Wiki Edits over Time
  • The Pynchon Wiki
    A race to finish the ‘detective work’
    Encouraging amateur contribution and learning from other contributors
    A model for self-organized collaboration?
    ‘Finalization’ of reference work or endless discussion?
    Reshaping how scholarly resources are distributed, and how we collaborate
  • e-Research as research technologies?
    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?...)
    Momentum at the policy level, at the infrastructure level, at the level of ’passports’, or end-user adoption
    An ’openness’ movement
    Resources or tools?
    Will e-Research become ’invisible’ (but also higher ’visibility’ when scientific output is increasingly online)
  • Implications of Research Technologies
    Tools drive science, but they impose new practices on researchers (collaboration, digitization, tool use)
    Aim is to enhance systems? or to advance our understanding of innovation and science?
    e-Research has different levels – with different forms of momentum and barriers
  • Design and Policy Implications I
    plan user requirements and user uptake before embarking on system development
    ensure that infrastructure and resources are in place to sustain project beyond system completion
    interoperability and standards for software, resources and tools
    motivate and reward contributions to shared resources and tools
    are efforts being duplicated, and is there a sufficient user base for all systems?
  • Design and Policy Implications II
    identify a niche where research technologies are likely to act as ‘passports’ between disciplines and applications
    collaborative agreements are in place, and project management
    Ethical and legal issues in data, resource and tool use and sharing (including IP issues)
    Visibility and transparency
    Open access strategy
  • So what?
    Quality of Research
    Nature of Research: Artisan or Knowledge Worker; Embedded or Mediated Observer
    Privacy and Confidentiality
    Ownership, IPR, and Openness
    Distribution of Expertise: Greater Diversity or a Winner-Takes-All?
  • Quality of Research
    Intermediation and Disintermediation
    Intermediation
    Disintermediation
  • 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.
  • O e S S
    Oxford e-Social Science Project
    http://www.oii.ox.ac.uk/microsites/oess/
  • Oxford Internet InstituteUniversity of Oxford
    Eric T. Meyereric.meyer@oii.ox.ac.ukhttp://people.oii.ox.ac.uk/meyer
    Ralph Schroederralph.schroeder@oii.ox.ac.uk http://people.oii.ox.ac.uk/schroeder
    Oxford e-Social Science Project