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Australasian Human Research Ethics Consultancy Services Pty Ltd (AHRECS)

Integrating the Management of Personal Data Protection and Open Science with Research Ethics (Papers: David Lewis, et al | 2017)0

Posted by Admin in on June 22, 2017


This paper examines the impact of the EU General Data Protection Regulation, in the context of the requirement from many research funders to provide open access research data, on current practices in Language Technology Research. We analyse the challenges that arise and the opportunities to address many of them through the use of existing open data practices for sharing language research data. We discuss the impact of this also on current practice in academic and industrial research ethics.

Fatema, K., Lewis, D., & Moorkens, J. (2017). Integrating the Management of Personal Data Protection and Open Science with Research Ethics. Ethics in Natural Language Processing. A Workshop at EACL 2017 4.April.2017 Valencia, Spain​​​

What Constitutes Peer Review of Data? A Survey of Peer Review Guidelines – Scholarly Kitchen (Todd A Carpenter | April 2017)0

Posted by Admin in on June 13, 2017

The sharing of research data has exploded in the past decade, and a variety of publications and organizations are putting policies in place that require data publication in some form. Over the past decade, the number of journals that accept data has increased, as have the number and scope of repositories collecting and sharing research data. Prior to 2010, data sharing was quite limited in scholarly publishing. A 2011 study of 500 papers that were published in 2009 from 50 top-ranked research journals showed that only 47 papers (9%) of those reviewed had deposited full primary raw data online. During the intervening years, the pace of data publishing increased rapidly. As another study notes, the number of datasets being shared annually has increased by more than 400% from 2011 to 2015, and this pace will likely continue. A culture of data sharing is developing, and researchers are responding to data sharing requirements, the efficacy of data sharing, and its growing acceptance as a scientific norm in many fields.

With the increased publication of datasets (partly in response to the policies of research funding bodies, and partly in response to the policies of journal publishers), what constitutes peer review of those datasets? This Scholarly Kitchen discussion piece from April 2017 examines the policies of the key publishers.

The process is driven in part by both funding and publication policies, which have been encouraging data sharing. The number of titles that explicitly require such sharing in some form is also increasing rapidly. In the past few years, PLOS, AGU, SpringerNature, and the American Economic Association, to highlight just a few, have each put forward policies about data sharing. In addition, data access has been the focus of other efforts, such as the COPDESS Statement of Commitment, which has 43 signatories. A variety of funding agencies, such as the Wellcome Trust, the Gates Foundation, and the Arnold Foundation now include data sharing as part of their funding policies, and a variety of government agencies are covered by the 2013 OSTP memo on increasing access to federally funded research.
A core element of what distinguishes scholarly publishing from trade publishing is the peer review process. As the availability of research data is increasing, it is important to ask how much of this data is peer reviewed. In a 2014 Study of 4,000 researchers by David Nicholas et al, “[i]t was generally agreed that data should be peer reviewed.” But what constitutes peer review of research data? What are existing practices related to peer review of research datasets? Since a number of journals specifically focus on the review and publication of datasets, reviewing their policies seems an appropriate place to start in assessing what existing practice looks like in the “real world” of reviewing and publishing data.


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Beyond open data: realising the health benefits of sharing data – theBMJ (Elizabeth Pisani, et al September 2016)0

Posted by Admin in on December 14, 2016

Accessible data are not enough. We need to invest in systems that make the information useful, say Elizabeth Pisani and colleagues

As little as a decade ago, many researchers working in global health recoiled at the idea that they should openly share individual patient data with one another. Now, data sharing is being herded into the mainstream by pioneering researchers, with added pressure from funders, medicine regulatory authorities, public health agencies, and medical journals.1 2 3 4 5 6 But even those researchers most willing to share data are given little guidance on how that should happen, and the practice is still unusual, especially in low and middle income countries.

Concerns continue to be raised that data sharing will lead to data being analysed by rich institutions in industrialised countries while researchers in poorer countries with the highest burdens of infectious disease will lose control of their data and get little in return. Some fear that data sharing might harm patients and communities by breaching confidentiality, that the infrastructure is not up to it, and there is nowhere safe to put shared data.7

Our group includes researchers working for academic and humanitarian organisations, as well as public, charitable, and industry funders of data sharing efforts. Although we have raised concerns in the past,8 9 10 11 12 13 we are now involved in sharing information collected in low and middle income settings, including demographic surveillance data and the records of individual patients in clinical trials. We examine the extent to which the fears about data sharing have been realised in our work and what is needed to get the most value out of shared data.

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How researchers lock up their study data with sharing fees – STAT (Ivan Oransky September 2016)0

Posted by Admin in on November 2, 2016

Chris Ferguson, a psychology researcher at Stetson University in DeLand, Fla., wanted to study how prolonged exposure to violent media affects kids and young adults. Not having access to his own long-term data on the subject, he turned to Brigham Young University, in Utah, where another group had recently published a similar study on the subject.

The response: Sure, you can share our data — but you’ll have to pay for it. It would cost $450 for the 1.5 hours it would take the institution to prepare the file. Lacking the cash but not wanting to abandon his project, Ferguson did what many people seeking funding do nowadays: He opened a GoFundMe page. Within two weeks, thanks to donations ranging from $10 to $300, he’d exceeded his goal.

Unfortunately, that still hasn’t opened up the data to him. “The contract they sent me I think was super restrictive — read literally, I don’t think even if I had found they had miscalculated a variable that I could recalculate it or report the error without their permission,” he told STAT. He and the school are trying to reach a deal.

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