Access and licencing of data

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Workshop for Doctoral Students RESEARCH DATA MANAGEMENT AND OPEN DATA 6th October 2015 University of Manchester

Transcript of Access and licencing of data

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Workshop for Doctoral Students

RESEARCH DATA MANAGEMENT AND OPEN DATA

6th October 2015

University of Manchester

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ACCESS AND LICENCING

OF DATAIrena Vipavc Brvar, Social Science Data Archives

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Content

Why share:

• Fraud and Misuse

• Making it visible – Founders / Publishers requirements

Licensing:

• Intellectual Property Rights

• Conditions / Requests

• Different Regulations

Accessing

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Frauds and Misuse

• „Considerable hard data have emerged on the scale of

misconduct. A metastudy (D. Fanelli PLoS ONE 4, e5738;

2009) and a detailed screening of all images in papers

accepted by The Journal of Cell Biology (M. Rossner The

Scientist 20 (3), 24; 2006) each suggest that roughly 1%

of published papers are fraudulent. That would be about

20,000 papers worldwide each year.“

• The U.S. National Science Foundation defines three

types of research misconduct: fabrication, falsification,

and plagiarism.

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National Science Foundation: RESEARCH

MISCONDUCT

(1) Fabrication means making up data or results and

recording or reporting them.

(2) Falsification means manipulating research materials,

equipment, or processes, or changing or omitting data

or results such that the research is not accurately

represented in the research record.

(3) Plagiarism means the appropriation of another

person’s ideas, processes, results or words without

giving appropriate credit.(http://www.nsf.gov/oig/regulations/)

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Slovenian Case

• Renown professor / a lot of publications and projects

• In one of the latest analysis: „Slovenian journalists and

audiences about the use of Twitter: between political

propaganda and trustworthy reporting“ she claimed to

conduct interviews with 50 journalists

• Delo (the biggest Slovenian daily newspaper) noticed the

article and started to investigate: 2 journalists and 3

editors of Delo should be interviewed according to the

analysis – which was not the case

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In 2013 Journal of Language, Identity &

Education retracted her article

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Licensing data for re-use

Think about how you want

others to use it.

L. Horton, 2015

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License: Clarify Intellectual Property

ownership

• You can only archive data you own

(or if you have permission)

• If you create it, check you own it

L. Horton, 2015

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License: Clarify funder expectations

Funder expectations: data to be as open as possible

L. Horton, 2015

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License: Clarify journal expectations

Funder expectations: data to be as open as possible

PLOS journals require authors to make all data

underlying the findings described in their manuscript

fully available without restriction, with rare exception.

When submitting a manuscript online, authors must provide

a Data Availability Statement describing compliance with

PLOS's policy. If the article is accepted for publication, the

data availability statement will be published as part of the

final article.

Refusal to share data and related metadata and methods in

accordance with this policy will be grounds for rejection. Plos; / Recomended Repositories

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Open Access

- Deposit your research data at the same time as publication

- Repositories might be institutional or subject based- They curate data and provide identifiers (DOI, URN)

data can be cited

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Where to publish

• Be aware of Hijacked journals

A case where researchers published at one of this

journals, not knowing the difference -> habilitation

issues.

Ask librarians!!!!

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Original

Hijacked journal

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License: Do you want to allow adaptation

and modification?

• Is format and design

intrinsic to the work?

• Does the work need to be

used in its entirety?

L. Horton, 2015

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License: Do you want to allow commercial

re-use

• Is there a contractual

reason for preventing

commercial use?

• Will you or your work

benefit from or be

harmed by commercial

usage

L. Horton, 2015

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Choosing a Creative Commons Licence

http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/RDM/sharing/licen

singDataReuse.aspx

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Licensing

• data available to the widest audience possible

• the widest range of uses possible

• reasons to limit both audience and usage

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Ethical and Legal Compliance

Before collecting data:

• prepare informed consent: information about research, data sharing and preservation

After collecting data:

• protect identities: anonymisation, avoid collecting personal data if not needed

• regulate access where needed: by group, users, time period…

1) personal data – data that allows living individuals to be identified legal aspect: data protection / privacy legislation (data about living individuals)

2) confidential information - information given in confidence, agreed to be kept confidential (secret) between two partieslegal: duty of confidentiality

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Ethical and Legal Compliance: relevant

questions• 3.1 How will you manage any ethical issues?

• Have you gained consent for data preservation and sharing?

• How will you protect the identity of participants if required?

e.g. via anonymisation

• How will sensitive data be handled to ensure it is stored and

transferred securely?

• 3.2 How will you manage copyright and Intellectual Property

Rights (IPR) issues?

• Who owns the data?

• How will the data be licensed for reuse?

• Are there any restrictions on the reuse of third-party data?

• Will data sharing be postponed / restricted e.g. to publish

or seek patents?

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Where can you put data?

• UK Data Service ReShare

• GESIS – Leibniz Institute for the Social Sciences datorium

• ADP – Slovene Social Science Data Archives

• Zenodo

• Figshare

• The Dataverse Project

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Managing access to data

• available for download/online access under open licence without any registration

Open

• available for download/online access to logged-in users who have registered and agreed to an End User Licence

Safeguarded

• available for remote or safe room access to authorised and authenticated users whose research proposal has been and who have received training

Controlled

Veerle Van den Eynden, 2015

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Regulate access where needed (all or part of

data) by group, use, time period

Open access

- survey description –

metadata,

- related materials and

publications,

- questionnaire,

- frequency and descriptive

analysis - summary

statistics

Registration needed

- On-line analyzes (Nesstar)

- Download of data

- Special conditions apply

for access to more

restricted datasets (Safe-

room environment)