The five stages to data sharing: Bargaining

Applying the Kübler-Ross model[1] to researchers and data sharing, based on various attitudes and comments we have encountered over the years. Don’t take the presentation seriously, but take the content seriously. Part three in a series of…uh, five.

3. Bargaining

Symptomatic statements: “Can I have an embargo…is 30 years OK?”; “I don’t want my data misused is there some way I can screen potential users?”

The third stage involves the hope that the individual can somehow postpone or delay data sharing. Usually, the negotiation for an extended embargo is made with a higher power (i.e. funding council) in exchange for a reformed lifestyle. Psychologically, the individual is saying, “I understand I will have to share my data, but if I could just do something to buy more time to write that extra N’th publication”. People facing less serious data sharing requirements can bargain or seek to negotiate a compromise. For example, “Can I have a veto over potential users” when facing a data sharing requirement. Bargaining rarely provides a sustainable solution, especially if it’s a matter of life or death or potential top-ranking impact journal articles.

Here’s the deal.

The struggle in a research career is getting people interested: interested in reading your work, citing you, making a name for yourself and building a reputation in your field. In this respect, why not use all the tools you can to help yourself, including data sharing. Why would you want to make it difficult for people to know your work?

But what about people working with your data before you “finish” with it? Surely that’s not on.

No, it’s not. Funders and archives are sensitive to a moral right of researchers who collect data to have the opportunity of deriving publications from that data before sharing. This is done by applying an embargo to data that prevents data being available to reuse before a specified date.

Subtle, huh?

Subtle, huh?

The National Science Foundation (NSF)[2] is one of nine public funding bodies in the United States [3] that have embargo policies, of varying strength and specificity. The UK funding environment also varies in embargo policies. The main social science funder, the Economic and Social Research Council (ESRC) [PDF][4] requires data be “offered” to an archive, but does not specify embargo periods – only that data be offered (not made available) within three months of the end of the award. Compare this to, for example, the Royal Society’s specific policy [PDF][5] on astronomy data embargoes: “Access to data may be embargoed for up to a year to allow the scientists who carried out the research to have a first chance to analyse their data”. An overview of research funders open access policies is produced by SHERPA/JULIET[6].

Another area of data sharing where embargoes may apply to data availability is journal policies. Currently in the social sciences, availability of data underpinning articles is rarely tied to journal publications, either as a stated policy[7] or an enforced one[8]. Furthermore, journals do not have the resources to host long-term data storage platforms – although platforms like Dryad[9] exist to address this problem. However, the American Political Science Association is in the process of revising its Ethics Guide[10] to include more about data access. Currently, this stands at one year after publication of an article unless specified otherwise by a funder or archive holding the data.

So in social sciences, in situations where data sharing is a requirement, reasonable embargoes can be applied to allow publications to be completed before data is shared with others, reasonable being understood as a period between six to eighteen months after the end of a project.

Why is this reasonable? Well, archives, journals and funders are reluctant to grant extended embargo periods because they could be misused as unwarranted proxies to prevent reuse. Bargaining to use embargoes or screening of potential users cannot be employed as unwarranted proxies to close access to data.

Cases where sensitive data cannot be shared for ethical, commercial, security, or intellectual property reasons do exist and are recognised [PDF][11] However, the expectation is that data should be shared to the fullest extent possible unless a strong (often prospective rather than retrospective) argument as to why it cannot be shared is presented. This includes taking steps to anonymise the data, or confine use to a specified user community through restrictive licences or a secure data service. Most social science data archives have some restriction on data access and data use – data simply isn’t “on Google” and is often only available to non-commercial users who have agree to terms of usage before they are allowed access to data. In some cases where sensitivity is greater, a restrictive licence is used to place specified conditions as to who can access data and what they can do with that data; this may include only allowing access through supervised, physical site visits to an archive. Secure data services[12] or secure data centers[13] are a recent innovation in the data archive community that allow controlled access to sensitive data through virtual remote access technology that allows for analysis but prevent researchers downloading data.

[1] Adapted from http://en.wikipedia.org/wiki/K%C3%BCbler-Ross_model under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

[2] National Science Foundation (2010) “Data Management & Sharing Frequently Asked Questions (FAQs)” (Accessed September 27, 2013) http://www.nsf.gov/bfa/dias/policy/dmpfaqs.jsp#9

[3] Dietrich, D. et.al. (2012) “De-Mystifying the Data Management. Requirements of Research Funders” Issues in Science and Technology Librarianship, 70, pp.1-15. http://dx.doi.org/10.5062/F44M92G2

[4] Economic and Social Research Council (2010) “Research Data Policy” (Accessed September 27, 2013) http://www.esrc.ac.uk/about-esrc/information/data-policy.aspx

[5] The Royal Society (2012) “Science as an Open Enterprise” (Accessed September 27, 2013) http://royalsociety.org/uploadedFiles/Royal_Society_Content/policy/projects/sape/2012-06-20-SAOE.pdf

[6] SHERPA/JULIET “Research funders’ open access policies” (Accessed September 23, 2013) http://www.sherpa.ac.uk/juliet/index.php

[7] Gherghina, S., Katsanidou, A. (2013) “Data Availability in Political Science Journals” European Political Science 12(3), pp.333–349. http://dx.doi.org/10.1057/eps.2013.8

[8] Dafoe, A. (2013) “Science Deserves Better: The Imperative to Share Complete Replication Files” Available at SSRN: http://dx.doi.org/10.2139/ssrn.2318223

[9] DRYAD (2013) “Repository: Key Features” (Accessed September 23, 2013) http://datadryad.org/pages/repository

[10] American Political Science Association (2012) “Committee on Professional Ethics, Rights, and Freedoms” (Accessed September 23, 2013) http://www.apsanet.org/content_2483.cfm

[11] Economic and Social Research Council (2010) “Research Data Policy” (Accessed September 27, 2013) http://www.esrc.ac.uk/_images/Research_Data_Policy_2010_tcm8-4595.pdf p.4

[12] UK Data Service “What is Secure Access?” (Accessed September 27, 2013) http://ukdataservice.ac.uk/get-data/secure-access/about.aspx#/tab-what-is-secure-access

[11] GESIS – Leibniz Institute for the Social Sciences (2013) “The Secure Data Center” (Accessed September 27, 2013) http://www.gesis.org/unser-angebot/daten-analysieren/datenservice/secure-data-center-sdc/

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About CESSDA Training

CESSDA Training offers and coordinates training activities for CESSDA, the Consortium of European Social Science Data Archives (http://www.cessda.net/). Hosted by the GESIS - Leibniz Institute for Social Sciences, our center promotes awareness throughout the research lifecycle of good research data management practice and emphasizes the importance of long-term data curation.
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One Response to The five stages to data sharing: Bargaining

  1. Pingback: The five stages to data sharing: Depression | Archive and Data Management Training Center

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