Open Access and Implications for Scientific Practice

Ralph Schroeder & Eric T. MeyerOxford Internet Institute

University of Oxford

Overview

• Open Access, Open Science, Open Source• Changing Scientific Practices: e-Research• Social Science and the Changing Research

Landscape

Open Science, Open Access, Open Source

• Open Science as public science (David), as mode of communication (Fuchs), and

• Open Access as Publishing Model• Open Access as Strategy and as Science Policy• Open Source licensing and collaboration• Open source models of innovation (Hope)

Science, e-Research in the ChangingResearch Landscape

• e-Research programmes and infrastructures

• e-Scholarly Communication Forums• The Blurring of boundaries at the edges of

these forums (public-private, formal-informal, etc.)

• Field differences, fields similar in beingpart of an online system

How Science Communication is Moving Online

• Shift to electronic publications• Generational and disciplinary differences• ’Google Generation’ report: search Web first, but

not expert searchers• Borgman: experts can make distinctions about

good online knowledge, others may not be ableto

• Informal online science communication channels

The Digitisation of Research Materials

• Borgman: data the fastest growing part of the content layer…

• …but all online content is growing• Heterogeneity…• …but also increased reflexivity about

’access’ and via measurement

Online visibility

• Increasing importance of online ‘impact’…• …amidst the various ways it is becoming

so• Online presence and visibility within the

system of knowledge - on the producer and consumer sides

• Competition within the attention space…• …with search engines as ‘gatekeepers’

• Integration vs. fragmentation• Increasingly traditional distinctions are

becoming blurred, tools vs. resources, formal and informal, primary resources and secondary resources

• Extent of openness(?), with varied implementation

• Key challenges focused on intersection of openness, e-Research, and e-infrastructures

Challenges

Social Science Perspectives• The partiality of online only measurement…• …versus the self-reinforcing nature of

measurement, online shifts, visibility, and behaviours

• Levels include projects, distributed collaboration, disciplines, infrastructures, science policy, and the transformation of knowledge

• A Proliferation of Tools, Resources and Communication Channels versus a (large technological) “System” in-the-Making

The Significance of Online Visibility…

• Different disciplinary pathways to online knowledge

• Search engines as ‘gatekeepers’• Webometrics, server logs and other impact

measures• The various forms of e-Research (tools,

resources, infrastructures)…• …and how they support research (data

manipulation, access to sources, support of research programmes)

Online visibility and Gatekeeping

Source: Meyer, E.T., Schroeder, R. (Submitted). The World Wide Web of Research and Access to Knowledge. Submitted to Social Science Computer Review.

Terms, Definitions…

“Large-scale science carried out through distributed collaborations – often leveraging access to large-scale data and computing”(John Taylor) National Grid Service, http://www.grid-support.ac.uk and Taylor, J.M. and e-Science http://www.e-science.clrc.ac.uk and http://www.escience-grid.org.uk

“the integrated ICT-based Infrastructure” with its key components being networking infrastructure (connectivity, CPU and storage),middleware and organisation (enabling deep integration of individual components across the network, and working collaboratively), and various types of resources (research outputs)The e-IRG roadmap on Infrastructure

“At the heart of the Cyberinfrastructure vision is the development of a cultural community that supports peer-to-peer collaboration and new modes of education based upon broad and open access to leadership computing; data and information resources; online instruments and observatories; and visualization and collaboration services”NSF’s report: ‘Cyberinfrastructure vision for the 21st Century Discovery’

e-Science

e-Infrastructure

Cyberinfrastructure

Social Science Perspectives on e-Research

• Perspectives include usability, research policy, • Levels to be addressed include projects,

distributed collaboration, disciplines, infrastructures, science policy, and the transformation of knowledge

• A Proliferation of Tools, Resources and Communication Channels vs. a (large technological) “System” in-the-Making

Social Shaping of e-Research

Dutton, 2006

• National Policy and Regulation (privacy and data protection, freedom of information, …)

• Institutional Policies and Regulations (IPR, Human Subjects, … of Universities, Centres, Institutes, …)

• Multi-disciplinary Codes and Practices (Researchers, Professional Associations, …)

• Social and Cultural Constraints (Participants, …)

Ethical, Legal and Organizational Issues in e-Research

• Copyright • Intellectual Property • Legal issues must be placed in larger

context of several forces (NGOs, publishers, policymakers) in a global shift in IP regimes

Frontiers and Boundaries

• Informal science communication (blogs, Wikis, project repositories)…

• …versus formal science communication (online publishing, shared repositories, ‘open’ science)

• Restricted (IP, sensitive data, priority) versus emerging models of peer-to-peer and open collaboration

• Greater diversity or winner-takes-all?

The Data Deluge

Source: S. Wuchty et al., (2007). The Increasing Dominance of Teams in Productionof Knowledge. Science 316, 1036 -1039.

The Growth of Teams

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)

• Pooling• High-throughput Analysis• Etc.

Digital Data or other research materials

• Images• Datasets• Visualization• Text• Sensor Data• Observations• Etc.

Research output, scientific knowledge

• Catalogue• Resource• Analysis• Etc.

Research Technology

Research TechnologiesA concept for the study of e-Research

Source: Schroeder (2008). ‘e-Sciences as Research Technologies: Reconfiguring Disciplines, Globalizing Knowledge’. Social Science Information, 47(2).

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

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

SwissBioGridNovartisNovartis

SwissBioGrid: A Mixture ofClusters and PCs

UniZH Matterhorn(Sun Grid Engine)

SIB Vital-IT (Platform LSF)

ETHZ Hreidar(Sun Grid Engine)

NorduG

RID/

ARCNorduG

RID/

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

GAIN: Genetic Association

Information Network

Meyer, E.T. (2008). 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 (RoutledgeAdvances in Research Methods series). New York: Routledge.

Open Science / Science 2.0

Citizen Science

Citizen e-Science

Bossa

Idiosyncratic systems

Social Informatics / STIN Approach

• Identify relevant populations• Identify core interactor groups• Identify incentives• Identify excluded actors and undesired

interactions• Identify existing communication forums• Identify resource flows• Identify system choice points• Map choice points to socio-technical

characteristics(Kling et al., 2003, p. 57; Meyer 2006, 2007)

So what? How does this help?

Socio-technical issues are often just as thorny as the technical challenges, but are often ignored and can be the difference between success and failure

• Flexibility in Planning and Design• Unintended consequences / unintended uses

• Quality and Nature of Research• Distribution of Expertise• Ownership, IPR, and Openness• Privacy and Confidentiality• Nature and Extent of Transformations

Conclusions

• The incompleteness of social science perspectives due to disciplinary specialization, but can combine STIN, sociology of knowledge, and information science

• Three key elements: online research realm, gatekeepers and paths, user behaviours in relation to their ecology

• Concepts of attention space, visibility, and gatekeepers cut across these elements

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

• 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

Oxford Internet InstituteUniversity of Oxford

Ralph SchroederJames Martin Research Fellowralph.schroeder@oii.ox.ac.uk

http://people.oii.ox.ac.uk/schroeder

Eric T. MeyerResearch Fellow

eric.meyer@oii.ox.ac.ukhttp://people.oii.ox.ac.uk/meyer

Oxford e-Social Science Project