Transcript APC Wyatt.pptx

Sally Wyatt,
Maastricht University &
e-Humanities Group, KNAW
Amsterdam Privacy Conference, 9 October 2012
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Growth of universities – of numbers of staff &
students, of (inter)disciplines
Increased accountability – for quantity &
quality of output, wider range of social actors
Success of ‘big’ science – large inter-national
& inter-disciplinary teams
Use of digital technologies in all stages of
knowledge production (and in administration)
Declining trust in/authority of science
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Self-regulation, 1945-75 – Mertonian norms
of universalism, communalism,
disinterestedness & organized scepticism
Preventing misconduct, 1975-90 – rise of
local Institutional Review Boards (in US and
some other countries – by no means all)
Promoting integrity, 1990--- new threats to
Mertonian norms from changing research
environment
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Research misconduct means fabrication,
falsification, or plagiarism in proposing,
performing, or reviewing research, or in
reporting research results.
• Fabrication is making up data or results and recording or
reporting them.
• Falsification is maniputing research materials, … or
changing or omitting data…
• Plagiarism is the appropriation of another person’s
ideas…without giving appropriate credit.
• Research misconduct does not include honest error or
differences of opinion.
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Invokes interesting object of study
Foregrounds practice of research rather than
infrastructure
Acknowledges diversity of research methods
(not only high-performance computing)
Sensitive to disciplinary practices
Evocative nature of term serves to catalyse
hope, resistance, controversy – and serves as
early warning of paradigmatic struggle,
methodological innovation & ethical reflection
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Stage in research
process
Digital application or
tool
Ethical consideration
Literature review
Search engines &
databases
Effects of (secret)
algorithms on availability
of information
Identifying
participants
Search engines, social
networking sites
Gathering information
about respondents without
their knowledge
(& respondents gathering
information about
researchers)
Data collection
From games, online
forums, web 2.0m etc.
Lurking as research
strategy, public/private,
‘contextual integrity’
Data analysis
Data mining tools,
Reducing complexity
computational methods
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Stage in research
process
Digital application or
tool
Ethical consideration
Data sharing
Distributed databases
Categorisation – making
(in)visible; intellectual
property
Data storage &
preservation
Cheap storage media;
annotation & metadata
tools
Should all (publicly
funded) research data be
preserved? Re-used?
Representation
Visualisation tools
(in)visibility of underlying
data, algorithm
(Mercator)
Authorship &
Authoring software,
acknowledgement distributed databases,
enhanced publications
Acknowledging technical
input; work & data of
online participants (are
they authors or
respondents?)
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It is publicly available – cite & acknowledge as
any other material (White 2002)
Protect privacy & anonymity of material provided
by/about (traceable) individuals (Beaulieu &
Estalella 2011)
Contextual integrity (Nissenbaum 2010)
Alienation (Bakardjieva & Feenberg 2000)
Thin identity (Carusi 2008)
Fabrication (Markham 2012)
Private-public – continuum or binary or dialectic?
What difference does it make to researchers, to
users of social media?
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Being earnestly ethical (Bakardjieva)
Doing no harm to respondents is not the only
ethical principle
Ethical obligations to other social actors:
◦ Other scholars – transparency, professional
standards
◦ Relations of trust between archivists & researchers
◦ Public – duties of openness, effective use of money
(avoid unnecessary duplication of data collection)
◦ Participants – avoid unnecessary duplication of
effort; ensure wider use (many participants do so to
‘help science’)
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