Suchergebnisse

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.

Between 2011 and 2013 the number of recorded malaria cases had more than doubled, and between 2009 and 2013 had increased almost 4-fold in MSF-OCA (Médecins sans Frontières - Operational Centre Amsterdam) programmes in the Democratic Republic of the Congo (DRC). The reasons for this rise are unclear. Incorrect intake of Artemisinin Combination Therapy (ACT) could result in failure to treat the infection and potential recurrence. An adherence study was carried out to assess whether patients were completing the full course of ACT. One hundred and eight malaria patients in Shamwana, Katanga province, DRC were visited in their households the day after ACT was supposed to be completed. They were asked a series of questions about ACT administration and the blister pack was observed (if available). Sixty seven (62.0%) patients were considered probably adherent. This did not take into account the patients that vomited or spat their pills or took them at the incorrect time of day, in which case adherence dropped to 46 (42.6%). The most common reason that patients gave for incomplete/incorrect intake was that they were vomiting or felt unwell (10 patients (24.4%), although the reasons were not recorded for 22 (53.7%) patients). This indicates that there may be poor understanding of the importance of completing the treatment or that the side effects of ACT were significant enough to over-ride the pharmacy instructions. Adherence to ACT was poor in this setting. Health education messages emphasising the need to complete ACT even if patients vomit doses, feel unwell or their health conditions improve should be promoted.

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for policymakers. It provides actionable information for policymakers who wish to implement the principles and priorities of data justice in their policymaking activities. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Depending on their contexts, potential impacts, and scale, data policymaking activities may be carried out in a way that involves stakeholder engagement. To facilitate this process, the next section provides an explainer of the Stakeholder Engagement Process and the steps it includes—preliminary horizon scanning, policy scoping and stakeholder analysis, positionality reflection, and establishing stakeholder engagement objectives and methods. Finally, the last section presents the guiding questions that will help policymakers address issues of data, digital infrastructures, and affected areas of civic, public, and private life, throughout the policy lifecycle and in accordance with the six pillars of data justice. ; This report was commissioned by the International Centre of Expertise in Montréal in collaboration with GPAI's Data Governance Working Group, and produced by the Alan Turing Institute. The research was supported, in part, by a grant from ESRC (ES/T007354/1), Towards Turing 2.0 under the EPSRC Grant EP/W037211/1, and from the public funds that make the Turing's Public Policy Programme ...

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for impacted communities. It provides actionable information for communities who wish to implement the principles and priorities of data justice. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Depending on their contexts, potential impacts, and scale, data activities may be carried out in a way that involves stakeholder engagement. To facilitate this process, the next section provides an explainer of the Stakeholder Engagement Process and the steps it includes—preliminary horizon scanning, policy scoping and stakeholder analysis, positionality reflection, and establishing stakeholder engagement objectives and methods. This section sets out considerations relating to internal community engagement (i.e. engagement within your community) as well as approaches to engaging external stakeholders (i.e. to inform or influence external activities). Additionally, it sets out considerations to be addressed when participating in externally-led engagement processes (e.g. where communities are invited to participate in stakeholder engagement initiated by developers or policy-makers). Finally, the last section presents the guiding questions that will help communities to address issues of data, digital infrastructures, and affected areas of civic, public, and private life, in relation to past, present and future dimensions of ...

AbstractA number of governmental and nongovernmental organizations have made significant efforts to encourage the development of artificial intelligence in line with a series of aspirational concepts such as transparency, interpretability, explainability, and accountability. The difficulty at present, however, is that these concepts exist at a fairly abstract level, whereas in order for them to have the tangible effects desired they need to become more concrete and specific. This article undertakes precisely this process of concretisation, mapping how the different concepts interrelate and what in particular they each require in order to move from being high-level aspirations to detailed and enforceable requirements. We argue that the key concept in this process is accountability, since unless an entity can be held accountable for compliance with the other concepts, and indeed more generally, those concepts cannot do the work required of them. There is a variety of taxonomies of accountability in the literature. However, at the core of each account appears to be a sense of "answerability"; a need to explain or to give an account. It is this ability to call an entity to account which provides the impetus for each of the other concepts and helps us to understand what they must each require.

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for developers and organisations, which are producing, procuring, or using data-intensive technologies. It provides actionable information for those who wish to implement the principles and priorities of data justice in their data practices and within their data innovation ecosystems. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Next, to support developers in designing, developing, and deploying responsible and equitable data-intensive and AI/ML systems, we outline the AI/ML project lifecycle through a sociotechnical lens, walking the reader through each phase and noting the ethics and governance considerations that should occur at each step of the way. This portion of the guide is intended to provide a background picture of the different stages of the lifecycle and to show how the data justice pillars can be woven into the stages and their respective sociotechnical considerations. To support the operationalisation data justice throughout the entirety of the AI/ML lifecycle and within data innovation ecosystems, we then present five overarching principles of responsible, equitable, and trustworthy data research and innovation practices, the SAFE-D principles—Safety, Accountability, Fairness, Explainability, and Data Quality, Integrity, Protection, and Privacy. These principles support and underwrite the ...

This resource is divided into two primary sections. The first is an annotated bibliography of works related to our integrated literature review on data justice, and the second is a table of organisations conducting data justice or data justice adjacent work. The annotated bibliography contains works relevant to each theme of the integrated literature review which is an accompanying document to this resource. Within each theme and sub-theme key works as well as summaries are provided to direct the reader to additional readings about the topics. This annotated bibliography is not an exhaustive resource, but rather meant to serve as a starting point for learning more about these topics. The table of organisations contains information about organisations conducting data justice or adjacent data justice work across the globe. To ensure the inclusion of a diverse set of organisations from across the globe and across relevant stakeholder groups, the team adopted a three-pronged approach to the identification of organisations. First, recommendations were taken from our existing advisory board members whose expertise on data justice within their regions of operation allowed them to identify organisations which might have been missed. Second, existing networks were examined to identify small organisations working at the intersection of datafication and social justice. This included the Association of Progressive Communications whose aim is 'empowering and supporting people working for peace, human rights, development and protection of the environment, through the strategic use of information and technologies and Privacy International who aim 'to protect democracy, defend people's dignity, and demand accountability from institutions who breach public trust'. Third, through active research and cascading search, additional organisations were identified based on prior work on datafication and social justice, previous experience of stakeholder engagement, and strong networks among relevant stakeholder groups. The table serves ...

BACKGROUND: Addressing the global burden of multidrug-resistant tuberculosis (MDR-TB) requires identification of shorter, less toxic treatment regimens. Médecins Sans Frontières (MSF) is currently conducting a phase II/III randomised controlled clinical trial, to find more effective, shorter and tolerable treatments for people with MDR-TB. Recruitment to the trial in Uzbekistan has been slower than expected; we aimed to study patient and health worker experiences of the trial, examining potential factors perceived to impede and facilitate trial recruitment, as well as general perceptions of clinical research in this context. METHODS: We conducted a qualitative study using maximum variation, purposive sampling of participants. We carried out in-depth interviews (IDIs) and focus group discussions (FGDs) guided by semi-structured topic guides. In December 2019 and January 2020, 26 interviews were conducted with patients, Ministry of Health (MoH) and MSF staff and trial health workers, to explore challenges and barriers to patient recruitment as well as perceptions of the trial and research in general. Preliminary findings from the interviews informed three subsequent focus group discussions held with patients, nurses and counsellors. Focus groups adopted a person-centred design, brainstorming potential solutions to problems and barriers. Interviews and FGDs were audio recorded, translated and transcribed verbatim. Thematic analysis, drawing on constant comparison, was used to analyse the data. RESULTS: Health system contexts may compete with new approaches especially when legislative health regulations or policy around treatment is ingrained in staff beliefs, perceptions and practice, which can undermine clinical trial recruitment. Trust plays a significant role in how patients engage with the trial. Decision-making processes are dynamic and associated with relationship to diagnosis, assimilation of information, previous knowledge or experience and influence of peers and close relations. CONCLUSIONS: This ...

International audience ; Objective Young people moving from child and adolescent mental health services (CAMHS) to adult mental health services (AMHS) are faced with significant challenges. To improve this state of affairs, there needs to be a recognition of the problem and initiatives and an urgent requirement for appropriate tools for measuring readiness and outcomes at the transfer boundary (16–18 years of age in Europe). The objective of this study was to develop and validate the Transition Readiness and Appropriateness Measure (TRAM) for assessing a young person's readiness for transition, and their outcomes at the transfer boundary. Design MILESTONE prospective study. Setting Eight European Union (EU) countries participating in the EU-funded MILESTONE study. Participants The first phase (MILESTONE validation study) involved 100 adolescents (pre-transition), young adults (post-transition), parents/carers and both CAMHS and AMHS clinicians. The second phase (MILESTONE cohort study and nested cluster randomised trial) involved over 1000 young people. Results The development of the TRAM began with a literature review on transitioning and a review of important items regarding transition by a panel of 34 mental health experts. A list of 64 items of potential importance were identified, which together comprised the TRAM. The psychometric properties of the different versions of the TRAM were evaluated and showed that the TRAM had good reliability for all versions and low-to-moderate correlations when compared with other established instruments and a well-defined factor structure. The main results of the cohort study with the nested cluster randomised trial are not reported. Conclusion The TRAM is a reliable instrument for assessing transition readiness and appropriateness. It highlighted the barriers to a successful transition and informed clinicians, identifying areas which clinicians on both sides of the transfer boundary can work on to ease the transition for the young person. Trial registration number ...

International audience ; Objective Young people moving from child and adolescent mental health services (CAMHS) to adult mental health services (AMHS) are faced with significant challenges. To improve this state of affairs, there needs to be a recognition of the problem and initiatives and an urgent requirement for appropriate tools for measuring readiness and outcomes at the transfer boundary (16–18 years of age in Europe). The objective of this study was to develop and validate the Transition Readiness and Appropriateness Measure (TRAM) for assessing a young person's readiness for transition, and their outcomes at the transfer boundary. Design MILESTONE prospective study. Setting Eight European Union (EU) countries participating in the EU-funded MILESTONE study. Participants The first phase (MILESTONE validation study) involved 100 adolescents (pre-transition), young adults (post-transition), parents/carers and both CAMHS and AMHS clinicians. The second phase (MILESTONE cohort study and nested cluster randomised trial) involved over 1000 young people. Results The development of the TRAM began with a literature review on transitioning and a review of important items regarding transition by a panel of 34 mental health experts. A list of 64 items of potential importance were identified, which together comprised the TRAM. The psychometric properties of the different versions of the TRAM were evaluated and showed that the TRAM had good reliability for all versions and low-to-moderate correlations when compared with other established instruments and a well-defined factor structure. The main results of the cohort study with the nested cluster randomised trial are not reported. Conclusion The TRAM is a reliable instrument for assessing transition readiness and appropriateness. It highlighted the barriers to a successful transition and informed clinicians, identifying areas which clinicians on both sides of the transfer boundary can work on to ease the transition for the young person. Trial registration number ...