The Global Brain: Digital Transformations of Research

Eric T. Meyer and Ralph Schroeder

The OeSS Project 2005-2011

Oxford e-Social Science Project

OxfordInternetInstitute

Oxforde-Research

Centre

Institute for Science, Innovation

and Society at

Saïd Business School

OeSS

Researc

her

Dis

cip

lin

es

Visualization Source: Boyack, Klavens & Borner (2005) Mapping the Backbone of Science. Scientometrics 64(3): 351-374.

Oxford

CollaborativeLinks

Empirical Social Science Approaches

Case studies

Spanning types of data and tools

Spanning disciplines: (Social) sciences and humanities

Issue-based studies

Privacy and data protection

Institutional Infrastructures

E-Research ethics, and …

Survey research

Online survey of e-Research:Bottom-up practices, proximity and cohorts

Scientometrics and webmetrics:Global visibility and output

Longitudinal ethnographies Contexts of research innovation

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

Digital Data or other research materials Types of research material:

• Images

• Datasets

• Visualization

• Text

• Sensor Data

Research output, scientific knowledge • Type:

• Catalogue

• Resource

• Analysis

• ?

Research Technology

Macro:

Grids, Shared Computing

Social:

Programmes

Technical:

Networks

Meso:

Institutional

Social:

Disciplines, interorganizational collaboration

Technical:

Discipline or project specific networked tools

Micro:

Users and their Tools

Social:

Research organizations

Technical:

Interfaces and locally accessible resources

Aggregation

Disembedding

Infrastructure

Reembedding

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

Vis

ibili

ty

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?

CasesSPLASH: 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

UniZH Matterhorn(Sun Grid Engine)

SIB Vital-IT (Platform LSF)

ETHZ Hreidar(Sun Grid Engine)

NorduGRID/

ARC

NorduGRID/

ARC

CSCS - Ticino Cluster (Itanium, LSF) - Terrane Cluster (PS 5, PBS) - Sun Cluster (PBS)

UniBS/FMI PC farms

ProtoGRIDMetascheduler

UniBS BC2 cluster(Platform LSF)

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

Community Acitivity

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Pynchon- l mailinglist messages Against the day Wiki edits

Anticipation

Annotation

And what’s next?

Weisenburger vs. the Wiki on Pynchon

Annotation Size

(no. of words)

Entries (topical

+ alphabetical+ page-by-page) Contributors

Book Form Annotation: Weisenburger’s

Gravity’s Rainbow162000 904 1 (22)

Wiki: Against the Day 455057

120 + 1358 + 4067

235

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

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page-by-page

alphabetical

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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 ResearchNature of Research: Artisan or

Knowledge Worker; Embedded or Mediated Observer

Privacy and ConfidentialityOwnership, IPR, and OpennessDistribution of Expertise: Greater

Diversity or a Winner-Takes-All?

Observation Measures

Direct Mediated

Scale

Small Interviews Virtual Ethnography

Large Webometrics Surveys

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.

Oxford e-Social Science Project

http://www.oii.ox.ac.uk/microsites/oess/

O e S S

Oxford Internet InstituteUniversity of Oxford

Eric T. Meyereric.meyer@oii.ox.ac.uk

http://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