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Purpose - Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. This paper analyzes the factors which influence data sharing by investigating journal data policies and the behavior of authors in sociology. Design/methodology/approach - The websites of 140 sociology journals were consulted to check their data policy. The results are compared with similar studies from political science and economics. A broad selection of articles published in five selected journals over a period of two years are examined to determine whether authors really cite and share their data and the factors which are related to this. Findings - Although only a few sociology journals have explicit data policies, most journals make reference to a common policy supplied by their association of publishers. Among the journals selected, relatively few articles provide data citations and even fewer make data available - this is true both for journals with and without data policy. But authors writing for journals with higher impact factors and with data policies are more likely to cite data and to make it really accessible. Originality/value - No study of journal data policies has been undertaken to date for the domain of sociology. A comparison of authors' behaviors regarding data availability, data citation, and data accessibility for journals with or without a data policy provides useful information about the factors which improve data sharing.

Discusses how to overcome EU-US tensions in the area of personal data sharing under rubric of post-9/11 counterterrorism. The politicized nature of EU integration in the fields of counterterrorism & organized crime fighting is noted, along with how the US federal structure problematizes the establishment of a coherent interagency & intergovernmental strategy for addressing that issue. Although there has been improved transatlantic cooperation, it is suggested that long-term prospects for transatlantic information sharing are not so promising. The problem of guaranteeing protection of private data is addressed before looking at the deleterious impact that the Treaty of Lisbon would have on EU security cooperation & data sharing with the US. It is then contended that proper implementation of the US-EU Agreement on Mutual Legal Assistance could substantially improve transatlantic security cooperation. It is suggested that the MLAT could provide the US with the appropriate strategic approach to counterterrorism & crime fighting. Further, MLAT can improve cooperation & set future standards of judicial cooperation internationally, while also fostering the creation of genuinely international, integrated task forces. D. Edelman

This study draws on interviews with forty-nine members of a biomedical research community in the UK that is involved in negotiating data sharing and access. During an interview, an interviewee used the words "ethical moment" to describe a confrontation between collaborators in relation to data sharing. In this article, I use this as a lens for thinking about relations between "the conceptual and the empirical" in a way that allows both analyst and actor to challenge the status quo and consider other ethical possibilities. Drawing on actor network theory (ANT), I approach "the empirical" using the concepts of controversy and ontological uncertainty as methodological tools to tackle the problem of ethics. I suggest that these concepts also provide a bridge for understanding the ontological structure of the virtual and the actual, as described in Deleuze's Difference and Repetition. While other science and technology studies scholars have sought to draw on Deleuze, this article addresses the integration of ethics and empirical research. It arises as a critical reaction to existing treatments of this problem as found in empirical ethics, especially in the sociology of bioethics, and indirectly in ANT texts.

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher's point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients . Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded a knowledge commons, but research policies that better incentivize data sharing are needed to improve the quality of research results and foster scientific progress.

This issue of the Journal of Empirical Research on Human Research Ethics highlights the ethical issues that arise when researchers conducting projects in low- and middle-income countries seek to share the data they produce. Although sharing data is considered a best practice, the barriers to doing so are considerable and there is a need for guidance and examples. To that end, the authors of this article reviewed the articles in this special issue to identify challenges common to the five countries and to offer some practical advice to assist researchers in navigating this "uncharted territory," as some termed it. Concerns around informed consent, data management, data dissemination, and validation of research contributions were cited frequently as particularly challenging areas, so the authors focused on these four topics with the goal of providing specific resources to consult as well as examples of successful projects attempting to solve many of the problems raised.

Data is an important business resource. It forms the basis for various digital technologies such as artificial intelligence or smart services. However, access to data is unequally distributed in the market. Hence, some business ideas fail due to a lack of data sources. Although many governments have recognised the importance of open data and already make administrative data available to the public on a large scale, many companies are still reluctant to share their data among other firms and competitors. As a result, the economic potential of data is far from being fully exploited. Against this background, we analyse current developments in the area of open data. We compare the characteristics of open governmental and open company data in order to define the necessary framework conditions for data sharing. Subsequently, we examine the status quo of data sharing among firms. We use a qualitative analysis of survey data of European companies to derive the sufficient conditions to strengthen data sharing. Our analysis shows that government data is a public good, while company data can be seen as a club or private good. Latter frequently build the core for companies' business models and hence are less suitable for data sharing. Finally, we find that promoting legal certainty and the economic impact present important policy steps for fostering data sharing.

The current emphasis on broad sharing of human genomic data generated in research in order to maximize utility and public benefit is a significant legacy of the Human Genome Project. Concerns about privacy and discrimination have led to policy responses that restrict access to genomic data as the means for protecting research participants. Our research and experience show, however, that a considerable number of research participants agree to open access sharing of their genomic data when given the choice. General policies that limit access to all genomic data fail to respect the autonomy of these participants and, at the same time, unnecessarily limit the utility of the data. We advocate instead a more balanced approach that allows for individual choice and encourages informed decision making, while protecting against the misuse of genomic data through enhanced legislation.

Context and aims Researchers increasingly need to share their data. This requires both adherence to Australia's robust privacy legislation and preparation of comprehensive data management plans. This paper outlines the data-sharing issues managed by IMPACT, a 6-site Canadian-Australian collaborative research program designed to improve access to primary health care for vulnerable individuals. Each site used a common protocol to evaluate its own intervention, with the aim of pooling data across the sites. Ethics applications were submitted in each site.MethodsConsultations were conducted with key informants within one Australian university (UNSW Sydney) and external informants to develop a data sharing plan. The authors reflect upon the process and have identified lessons for others wanting to share data.Findings Data sharing for a multi-site multi-country study was complex. University policies and infrastructure have been changing, not all sharing tools were available and support personnel were still learning how to implement policies related to data sharing. Furthermore, site-specific ethics applications did not specify that the data was part of a larger study. Consequently, the other 5 sites were deemed as external.We needed multiple consultations with ethics, IT, and data governance units to understand data classification (patient data is inherently sensitive), who needed access, and how access could be enabled. Bringing these support units together assisted a common understanding – this had not been previous practice. Innovative contribution to policy, practice and/or researchEarly consultations with university ethics and data governance units is recommended for planning data sharing – particularly for patient data and complex projects.

This article addresses the role of pharmacoepidemiology in patient safety and the crucial role of data sharing in ensuring that such activities occur. Against the backdrop of proposed reforms of European data protection legislation, it considers whether the current legislative landscape adequately facilitates this essential data sharing. It is argued that rather than maximising and promoting the benefits of such activities by facilitating data sharing, current and proposed legislative landscapes hamper these vital activities. The article posits that current and proposed data protection approaches to pharmacoepidemiology — and more broadly, re-uses of data — should be reoriented towards enabling these important safety enhancing activities. Two potential solutions are offered: 1) a dedicated working party on data reuse for health research and 2) the introduction of new, dedicated legislation.

A model of cloud services is emerging whereby a few trusted providers manage the underlying hardware and communications whereas many companies build on this infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS applications. From the start, strong isolation between cloud tenants was seen to be of paramount importance, provided first by virtual machines (VM) and later by containers, which share the operating system (OS) kernel. Increasingly it is the case that applications also require facilities to effect isolation and protection of data managed by those applications. They also require flexible data sharing with other applications, often across the traditional cloud-isolation boundaries; for example, when government, consisting of different departments, provides services to its citizens through a common platform. These concerns relate to the management of data. Traditional access control is application and principal/role specific, applied at policy enforcement points, after which there is no subsequent control over where data flows;a crucial issue once data has left its owner's control by cloud-hosted applications andwithin cloud-services. Information Flow Control (IFC), in addition, offers system-wide, end-To-end, flow control based on the properties of the data. We discuss the potential of cloud-deployed IFC for enforcing owners' data flow policy with regard to protection and sharing, aswell as safeguarding against malicious or buggy software. In addition, the audit log associated with IFC provides transparency and offers system-wide visibility over data flows. This helps those responsible to meet their data management obligations, providing evidence of compliance, and aids in the identification ofpolicy errors and misconfigurations. We present our IFC model and describe and evaluate our IFC architecture and implementation (CamFlow). This comprises an OS level implementation of IFC with support for application management, together with an IFC-enabled middleware.