Open science (and) data
IRYNA SUSHA
PhD candidate,
Department of Informatics, Örebro University
2016-07-24
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Agenda
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Introduction
Open science data
Examples
Opportunities and strengths
Weaknesses and threats
Challenges
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Introduction
outcome
• Motto of openness movement: information
and knowledge should be open to everyone!
• Open science – movement to make scientific
research, data and dissemination accessible
to all levels in the society, amateur and
professional (OKFN).
• Open knowledge – information, content, and
data which is free to use, reuse, and
redistribute without legal, social, or
technological restrictions (OKFN).
• Open data – data available for anyone to
use, reuse, and redistribute for any purpose
and at no cost.
Open
knowledge
Open data
resource
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Open
science
practice
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Open science data
Open science data – data containing observations and/or results of
scientific activities made available for anyone to analyze and reuse
(OKFN).
Data = plain representation of facts
Information = Data + meaning!
Knowledge = Information + Processed in individual’s mind!
(Same with “open”)
Open science data ≠ Open access
Machine-readable, raw datasets VS Human-readable texts,
publication
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Example 1
 Open notebook science – placing online personal observations, all
raw and processed data and other material (references, student
works, to-do lists, collaborations etc.) as this material is generated.
http://usefulchem.wikispaces.com/
Technology tools: social networks, blogs, document sharing, wikis
Open science
principles
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Access
Participation
“Socialization
of science”
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Example 2
 Citizen (crowd) science – the practice of involving the public to
participate and collaborate in scientific research.
 1st generation Volunteer distributed computing – make use of the idle
time on many individual home computers to process data in support of
large initiatives. E.g. SETI@home http://setiathome.berkeley.edu/
 2nd generation Capitalizing on human cognition – involving citizen
participants in classifications, image recognition, geo-coding etc. E.g.
Operation War Diary http://www.operationwardiary.org/
Zooniverse portal: 1 million active users, over 50 scientific publications
Citizen science games: find a new galaxy/star/planet; help predict
global warming from old weather data; solve complex puzzles by
folding proteins etc.
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Opportunities and strengths 1
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Increased return on investment of public funds by making data
outputs openly available for re-use;
Faster dissemination of research outputs including
methodologies, data, models, and scientific outcomes;
Greater academic rigor, robustness and scholarly integrity from
transparent data practices;
Efficiency gains from open research practice leading to reduced
unnecessary repetition of research activities;
Enhanced opportunities for student learning from open sharing
of experimental methods and results data;
Enhanced public engagement and understanding of science
principles and practice.
Source: Molloy, J.C. (2011). Open Data Means Better Science. Open Knowledge Foundation.
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Opportunities and strengths 2
Virtual citizen science as informal, unstructured, social learning process
Education outcomes include:
 Learning at task/game level;
 Acquiring pattern recognition skills;
 Obtaining knowledge and skills on- and off-topic;
 Improving scientific literacy;
 Driving personal development.
Source: Kloetzer et.al (2013). Learning by volunteer computing, thinking and gaming: What and how
are volunteers learning by participating in Virtual Citizen Science ? In Proceedings of 7th European
Research Conference.
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Weaknesses and threats
 Time- and resource-consuming to publish data on the research
process or results;
 Fear of misuse of data or results: deliberate or unintentional
misinterpretations or exploitation of one’s (unfinished) work;
 !! Important ethical concerns, where datasets contain personal
information and thus should comply with data protection rules;
 Need for guidelines for publishing material, standardized formats,
appropriate licenses, proper citation methods.
Source: Kraker et.al (2011). The Case for an Open Science for Technology Enhanced Learning. Int.J.
of Technology Enhanced Learning, 3(6), 643-654
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Challenges on the road to openness
 Current rewards culture in the academia:
 Citation-based merit of excellence;
 Journal publication practices do not incentivize sharing;
 Concerns about credit, attribution, trust, and intellectual
property;
 Psychological issues of exposing the making of mistakes.
 Lack of institutional readiness:
 Policies and planning enforcing open science principles;
 Organizational structures;
 Capability development;
 Support infrastructure.
Sources: Currier, S. (2011). Open science project: Final report. Commissioned by JISC, University of
Nottingham . AND Lyon, L. (2009). Open Science at Web Scale: Optimizing participation and
predictive potential. JISC report.
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Thank you for listening!
Any ideas?..
To connect: iryna.susha@oru.se
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