2. Course leader/teachers
Research librarian Mette Brandt Eriksen
Head of Institute, Kirsten Ohm Kyvik
Librarian Jens Dam
Research librarianThea M. Drachen
Head of Library Bertil F. Dorch
Extensive “adopting and adapting” from course slides by Mickey Gjerris, Lars
Holm, Bertil Dorch,AsgerV Larsen and Anders Drachen, with permission.
4. Form
Today
Lecture, buzzings and plenum discussions
Homework (approx 2 hours)
Prepare/adjust your data management plan
Discuss it with your supervisor
6. 1960s to explain some of the horrors taking place during WW2
Question:
“For how long will someone continue to give shocks to another
person if they are told to do so, even if they thought they could
be seriously hurt?” i.e. will people do morally wrong things just
because an authority figure tells them to?
The Stanley Milligram Experiment
7. ”Shock Generator” with 30 switches
Moderate (75-120V), Strong (135 – 180V),…
Danger – Severe Shock (375- 420V), XXX (435 – 450V)
40 volunteers, payment for showing up, could leave anytime
Experimenter (actor posing as distinguished professor)
Another participant (also an actor)
”Participants” drew lots about roles in the
”memory and learning experiment”
Lottery was faked, real participant always ”teacher”
9. E in same room as T
If T concerned -> E predefined ”prods”
to continue the experiment
progressively more authoritarian
L and T in radio contact
(pre-recorded audio)
e.g.
75V: ”Ugh!!!”
180V: ”Ugh!!! … Let me out of here!”
285V: Screaming
345+V: Silence
10. Thought:
only psychopaths will not stop
shocking, maybe 1-3%
Result:
all 40 gave up to 300V
25 continued to 450V
i.e. 65% never stopped…
Today not allowed:
Deceived about purpose
Not made aware of consequences
Risk of short-term emotional stress
Risk of long-term emotional stress
(independent study found no long-term effects)
11. So, as researchers we cannot do this…
but the media can!!
Experiment remade by BBC in 2009
12 subjects -> 9 went on to
administer 450V
Why?
We humans tend to do as told
especially from authority persons Appearance
Why am I telling you this
12. Content
• Integrity and conduct reg. research data
• Guidelines
• What not to do
• Data
• Data management
• Where to go with IP and Patents
• Good stuff to know
13. Referring to rules, regulations and established
comme-il-faut’s by:
•Laws
•Research councils
•Funding bodies
•National and international coda for science ethics
•Danish Standards, of which there is no current
National standard for research data but this is being
amended
Guidelines
15. • Research Councils UK (RCUK) has a policy of documentation
of research including data (April 2013)
• Welcome Trust has a policy in this area
• OECD have a policy in this area – and has had it since 2007
• NSF and NIH have policies in this area
• EU – It was a policy in FP7, that you should deliver a DMP and
there will be a policy for Horizon 2020
• European Research Council also has policies in this area.
• Nature writes: Data sets must be made freely available to
readers from the date of publication, and must be provided to
editors and peer-reviewers at submission, for the purposes of
evaluating the manuscript.
Guidelines
17. Guidelines
1. Integrity:
Researchers should take responsibility for the trustworthiness of their
research.
2. Adherence to Regulations:
Researchers should be aware of and adhere to regulations and policies
related to research.
3. Research Methods:
Researchers should employ appropriate research methods, base
conclusions on critical analysis of the evidence and report findings and
interpretations fully and objectively.
www.singaporestatement.org/
18. Guidelines
4. Research Records:
Researchers should keep clear, accurate records of all research in ways
that will allow verification and replication of their work by others.
5. Research Findings:
Researchers should share data and findings openly and promptly, as soon
as they have had an opportunity to establish priority and ownership
claims.
13. Research Environments:
Research institutions should create and sustain environments that
encourage integrity through education, clear policies, and reasonable
standards for advancement, while fostering work environments that
support research integrity.
www.singaporestatement.org/
22. Guidelines
FIVU [Uddannelses og forskningsministeriet – Ministry of Higher
Education and Science] has a group working on a proposal for a
Danish Code of Conduct for Research Integrity. As part of a
broader hearing during April/May a conference was held on 9th of
May 2014. Work ongoing.
Ministry of Higher Education and Science http://fivu.dk/forskning-og-
innovation/rad-og-udvalg/andre-udvalg-og-fonde/arbejdsgruppe-faelles-
retningslinjer-for-forskningsintegritet accessed 5th March 2014
23. No Danish research foundation has policies on data management,
but many do on Open Access, and they feel positive about sharing
data as well, for the most part and under certain conditions
(Research data project under Danmarks Elektroniske Fag og
Forskningsbibliotek (DEFF) – interviews w research funds 2013)
Guidelines
24. The Steering Committee
for
Danish National Data Management
is currently composing
a draft for
a national standard
for data management
Guidelines
25. Guidelines Sensitive data
Persondataloven – lovtekst:
https://www.retsinformation.dk/Forms/R0710.aspx?id=828
Data tilsynet - http://www.datatilsynet.dk/offentlig/kort-om-
persondataloven/
27. Univeristy of Southern Denmark
has called for a review
of how faculties handle research data
in relation to data classification
including handling of sensitive and personal information
Guidelines
28. SDUnet: God videnskabelig praksis / Good Scholarly Practice
Juridisk kontor / Legal office
http://sdunet.dk/Vaerktoejer/love_regler_aftaler/Forskning/God-
videnskabelig-praksis.aspx?contentlang=da
§ 1 Subsection 3. good scholarly practice demands moreover the
observance of good research practice.This means that scholarly
activity must be performed with respect for such practice and
observance of the universally acknowledged methodology and
ethical codes of scholarship of the relevant research field,
thereby preserving the personal and professional integrity of the
scholar concerned. Commissions or omissions which
are inconsistent with good research practice include:
Guidelines
29. § 1 Subsection 3 (cont’d)
…
2. Deliberate misrepresentation of research results or the
dissemination of misleading information about one´s own or
others´ part in the research, even though the extent and
consequences of the irregularity cannot in themselves be termed
grave.
3. Conduct which is not in conformity with the guidelines, issued
by official and/or professionally-recognised bodies, governing
good scholarly practice in the field (e.g. relating to research
protocols, data processing, documentation, declaration of
authorship, private financial backing, etc.)
...
Guidelines
32. Fabrication of data
• Inventing data-sets to support hypothesis
• Image-construction
Hard to interpret as anything but a conscious attempt to cheat
”I accidentally made up the data?”
Grey areas
Methods within statistics to deal with missing data
• Imputation (replacing missing data with substituted values)
• Extrapolating data on the basis of existing data
33. Falsification of data
• ”Tidy up” data
• Delete data that does not ”fit” – data selection
• Image-editing
• Choose methodology, equipment etc. that gives incorrect but
desired results
• Modifying (misrepresenting) results to support hypothesis
34. Buzz break
Dr. José M. is beginning his fifth year as an independent researcher.
His work is going well. He has published a number of important
articles and secured a large grant for future work. Based on this
progress, he expects his pending promotion to proceed without
problems.
Late one afternoon a graduate student hands José two papers
written by a senior colleague in his department. She has circled
graphs in each of the papers that are clearly the same but
reported as representing two different experiments.After
checking the graphs carefully and reviewing the supporting data,
José agrees that something is wrong.The senior colleague, who
will almost certainly be a member of his promotion review, has
either made a careless mistake or falsified information in a
publication.What should he do?
Case Study
From Steneck’s ”ORI Introduction to the Responsible Conduct of Research”
36. In 1998 Andrew Wakefield and
colleagues published a paper in the
Lancet claiming that the MMR
vaccine causes a series of events
that include intestinal inflammation,
loss of intestinal barrier function,
entrance into the bloodstream of
encephalopathic proteins, and
consequent development of autism.
In support of his hypothesis, Dr.Wakefield described 12 children
with neurodevelopmental delay (8 with autism).All of these
children had gastrointestinal complaints and developed autism
within 1 month of receiving MMR.
Text from American Academy of Pediatrics accessed 6 March 2014
http://www2.aap.org/immunization/families/autismwakefield.html
37. Led to a widespread scare of vaccination
– with severe direct and indirect effects
In 2010 it was found out that the paper was a result of bad
scientific practice – and it was retracted from Lancet
Although the authors claim that autism is a consequence of
gastrointestinal inflammation, gastrointestinal symptoms were
observed after, not before, symptoms of autism in all 8 cases.
Children with autism were claimed to have low levels of
circulating immunoglobulin A (IgA). However, levels reported
were within the normal range for that age group.
Text from American Academy of Pediatrics accessed 6 March 2014
http://www2.aap.org/immunization/families/autismwakefield.html
38. About 90% of children in England received
MMR at the time this paper was written.
Because MMR is administered at a time when
many children are diagnosed with autism, it
would be expected that most children with autism would have
received an MMR vaccine, and that many would have received the
vaccine recently.The observation that some children with autism
recently received MMR is, therefore, expected. However,
determination of whether MMR causes autism is best made by
studying the incidence of autism in both vaccinated and
unvaccinated children.This wasn't done.
Text from American Academy of Pediatrics accessed 6 March 2014
http://www2.aap.org/immunization/families/autismwakefield.html
41. Content
• Integrity and conduct reg. research data
• Data
• Sampling
• Analyses and statistical tests
• Fitness for purpose
• Data management
• Where you go with IP and Patents
• Good stuff to know
42. Data
Research data is data that is collected, observed, or created, for purposes of
analysis to produce original research results.
Boston University
http://www.bu.edu/datamanagement/background/whatisdata/
Oberservations (sensor data, telemetry, survey data, sample data,
neuroimages). Data captured in real-time.
Usually irreplaceable
Experimental (gene sequences, chromatograms). Data from lab equipment.
Mostly reproducible but can be expensive
Simulations (climate models, economic models). Data generated from test
models
Compiled (text and data mining, compiled database, 3D models, data gathered
from public documents).
Reproducible but very expensive
43. Data
Validity
Measure what we want to measure
Ability of a research design to test the hypothesis
it was designed to test
Results answer what we intend them to answer
Reliability
Results can be replicated by others
Generalizability
Results have a wider application than merely
the participants and the circumstances of the test
49. Data
CONSORT
Consolidated Standards of ReportingTrials
http://www.consort-statement.org/
various initiatives to alleviate the problems arising from
inadequate reporting of randomized controlled trials
53. Validity
Measure what we want to measure
Ability of a research design to test the hypothesis
it was designed to test
Results show what we intend them to show
Reliability
Results can be replicated by others
Generalizability
Results have a wider application than merely
the participants and the circumstances of the test
Buzz break
How doYOU ensure
inYOUR work?
54. Content
• Integrity and conduct reg. research data
• Data
• Data management
• Why data management
• Metadata – data about data
• Data Management Plans
• Data sharing
• Data BU & repositories
• Sensitive data
• Where to go with IP and Patents
• Good stuff to know
56. Why data management
• Meet grant and/or institutional requirements
• Documentation ensures integrity of data
• Increase your research efficiency through documentation
• Preserve your data for own (and/or others) future use
• Facilitate new discoveries (e.g. meta studies)
• Data sets can be systematically published and quoted, thus
contributing to the global impact of your research
57. Metadata
• Data about data (More than the name you give your file or the folder it is placed in)
• Different formats/standards usually coupled with the data
management service provider
• Sometimes initially cumbersome to include but it is crucial for
the (/your) future usability of the data and the inclusion process
typically lightens with more uploads
• Metadata makes data useable for others and re-useable for you
• Data Documentation Initiative (DDI) - A metadata specification
for the social and behavioral sciences
http://www.ddialliance.org/
• Dansk Data Arkiv – guidelines and specific requirements for
metadata format http://www.sa.dk/dda/
58. Data management plan
Typically asked to cover:
Description of the data
to be collected / created
Standards / methodologies
for data collection and management
Ethics and Intellectual Property
concerns or restrictions
Plans for data sharing and access
Strategy for long-term preservation
http://www.dcc.ac.uk/
59. Data Management plan
• DCC - Digital Curation Centre – UK based (JISC funded)
http://www.dcc.ac.uk/
• MANTRA – University of Edinburgh – UK Based
http://datalib.edina.ac.uk/mantra/
• Australian National Data Service (ANDS)
http://ands.edu.au/
• Stanford University – US Based
http://library.stanford.edu/research/data-management-
services/data-management-plans
67. Buzz
What metadata should your datasets contain for you to
be able to use them and share them with a collaborator
in 5 years?
Do you have a data management plan for your project?
What does it contain/describe?
68. Why data sharing
• The national bibliometric research indicator honors published
data sets and publications with associated datasets
• Increase the visibility of your research *
* Clinical trials - Piwowar, Heather A.,
Roger S. Day, og Douglas B. Fridsma.
«Sharing Detailed Research Data Is
Associated with Increased Citation
Rate». PLoS ONE 2, nr. 3 (2007):
e308.
doi:10.1371/journal.pone.0000308
* Astrophysics - Dorch, Bertil. «On the
Citation Advantage of linking to
data» (2012).
http://hprints.org/hprints-00714715
70. Data sharing
“We found that cancer clinical trials which share their
microarray data were cited about 70% more frequently
than clinical trials which do not.”
“This result held even for lower-profile publications and
thus is relevant to authors of all trials.”
72. Data BU & repositories
• Backing up data on “fællesdrevet”…
• SDU IT option of hiring serverspace
http://www.sdu.dk/Om_SDU/Faellesomraadet/IT-service/Services/Virtuelserver.aspx
• Commercial services like DropBox (primarily for BackUp, can
be used for sharing)
• Dansk Data Arkiv
Is there a repository for you? Probably.
http://www.datacite.org/repolist will show you a list.
Disciplinary or institutional repositories?
• Disciplinary: eased discovery, probably eased integration
between datasets
• Institutional: local support, branded by institution, durability
73. Data BU & repositories
http://www.sdu.dk/Om_SDU/Faellesomraadet/IT-service/Services/Datacontainer
http://sdunet.dk/Vaerktoejer/Vejledninger/IT/Datacontainer.aspx
74. Data BU & repositories
http://www.sdu.dk/en/om_sdu/institutter_centre/klinisk_institut/forskning/forskningsenh
eder/open
75. Data BU & repositories
http://www.sdu.dk/en/om_sdu/institutter_centre/klinisk_institut/forskning/forskningsenh
eder/open
OPEN is a research infrastructure
• supports clinical research in the Region of Southern Denmark
• inviting other research groups to join projects
• enrich the cohort by asking other scientific questions than
those initially raised
• often achieved simply by adding a few extra tests to the
protocol
76. Data BU & repositories
• ZENODO linked to OpenAIRE (https://www.openaire.eu/)
which is linked to EU funding
http://zenodo.org/
For researchers, scientists, EU projects and institutions to share
and showcase multidisciplinary research results (data and
publications) that are not part of existing institutional or
subject-based repositories
• DataBox
https://data.kb.dk/dvn/
(not endorsed by KU
- currently composing needs
and standards for an
institutional data repository)
77. Data BU & repositories
http://www.sdu.dk/Om_SDU/Faellesomraadet/IT-service/Services
IT services
80. Sensitive data
Retningslinjer for anmeldelse af forsker-initieret
sundhedsforskning i regionerne til Datatilsynet
http://www.regioner.dk/sundhed/kvalitet+og+forskning/forskning/retningslinjer
+for+anmeldelse+af+forsker-
initieret+sundhedsforskning+i+regionerne+til+datatilsynet
81. Content
• Integrity and conduct reg. research data
• Data
• Data management
• Where to go with IP and Patents
• Good stuff to know
82. IP and Patents
TechTrans office (in Danish)
http://www.sdu.dk/om_sdu/faellesomraadet/sdu+erhverv/teknologioverfoersel
83. IP and Patents
TechTrans office (in Danish)
http://www.sdu.dk/om_sdu/faellesomraadet/sdu+erhverv/teknologioverfoersel
(MTA) Material Transfer Agreement
no signing untill talk w TechTrans!
Patent application before publishing
84. IP and Patents
Juridisk kontor (in Danish)
http://www.sdu.dk/om_sdu/faellesomraadet/ledelsessekretariatet/juridisk+kontor
85. Buzz break
How is integrity in research monitored?
Is self-regulation of integrity in research effective?
From Steneck’s ”ORI Introduction to the Responsible Conduct of Research”
86. Content
• Integrity and conduct reg. research data
• Data
• Data management
• Where to go with IP and Patents
• Good stuff to know
87. Further knowledge and training
Research Integrity and courses
•Epigeum Research Integrity online course - UK based, but relates
to the EU (for Copenhagen University, SDU is considering)
http://researchskills.epigeum.com
•NIH ethics course
http://researchethics.od.nih.gov/
88. Further knowledge and training
Visibility of research
• Blogging
• Coordinating online profile, specifically Google Scholar
• Figshare
http://figshare.com/
get citation credit for datasets
make your research more discoverable, citable and sharable
enables you to publish negative results
• Open Access publishing (if it’s not on Google it does not exist)
89. Further knowledge and training
ORCID
http://orcid.org/
Web of Science articles by ”Hansen” published since 2000, in
science and technology, yielded more than 50.000 hits.
Problem of the who is who.
0,3 mill. Johanssons (Sweden)
2,5 mill. Smiths (USA)
10 mill. Kims (Korea)
100 mill.Wangs (China)
??? mill. Names changed by marriage, divorce, numerology, new
employment (name of organization), cultural differences in name
order?
90. Further knowledge and training
Using pictures
Store on intranet only or use permitted pictures only
97. Further knowledge and training
Linking
Can you link to copyright protected material on the internet
without ok from the copyright holder?
To legal material is ok unless you link to stuff put on the internet
without the copyrightholders accept or if copy protection has
been violated
burden of evidence…
