In Australia research projects proposing the use of linked data require approval by a Human Research Ethics Committee . A sound evaluation of the ethical issues involved requires understanding of the basic mechanics of data linkage, the associated benefits and risks, and the legal context in which it occurs. The rapidly increasing number of research projects utilising linked data in Australia has led to an urgent need for enhanced capacity of HRECs to review research applications involving (...) this emerging research methodology. The training described in this article was designed to respond to an identified need among the data linkage units in the Australian Population Health Research Network and HREC members in Australia. (shrink)

A key ethical issue arising in data linkage research relates to consent requirements. Patients’ consent preferences in the context of health research have been explored but their consent preferences regarding data linkage specifically have been under-explored. In addition, the views on data linkage are often those of patient groups. As a result, little is known about lay people’s views and their preferences about consent requirements in the context of data linkage. This study (...) explores lay people’s views and justifications regarding the acceptability of conducting data linkage research without obtaining consent. (shrink)

Linkage of population-based administrative data is a valuable tool for combining detailed individual-level information from different sources for research. While not a substitute for classical studies based on primary data collection, analyses of linked administrative data can answer questions that require large sample sizes or detailed data on hard-to-reach populations, and generate evidence with a high level of external validity and applicability for policy making. There are unique challenges in the appropriate research use of linked (...) administrative data, for example with respect to bias from linkage errors where records cannot be linked or are linked together incorrectly. For confidentiality and other reasons, the separation of data linkage processes and analysis of linked data is generally regarded as best practice. However, the ‘black box’ of data linkage can make it difficult for researchers to judge the reliability of the resulting linked data for their required purposes. This article aims to provide an overview of challenges in linking administrative data for research. We aim to increase understanding of the implications of the data linkage environment and privacy preservation; the linkage process itself and linkage quality and potential bias in linked data. We draw on examples from a number of countries to illustrate a range of approaches for data linkage in different contexts. (shrink)

This open access book provides the first systematic overview of existing challenges and opportunities for responsible data linkage, and a cutting-edge assessment of which steps need to be taken to ensure that plant data are ethically shared and used for the benefit of ensuring global food security – one of the UN’s Sustainable Development Goals. The volume focuses on the contemporary contours of such challenges through sustained engagement with current and historical initiatives and discussion of best practices (...) and prospective future directions for ensuring responsible plant data linkage. The volume is divided into four sections that include case studies of plant data use and linkage in the context of particular research projects, breeding programs, and historical research. It address technical challenges of data linkage in developing key tools, standards and infrastructures, and examines governance challenges of data linkage in relation to socioeconomic and environmental research and data collection. Finally, the last section addresses issues raised by new data production and linkage methods for the inclusion of agriculture’s diverse stakeholders. This book brings together leading experts in data curation, data governance and data studies from a variety of fields, including data science, plant science, agricultural research, science policy, data ethics and the philosophy, history and social studies of plant science. (shrink)

This chapter provides a framing for this volume by reviewing the significance and the organisational, technical and social opportunities and challenges related to plant data linkage. We review what “responsible practice” means in relation to the plant environments being documented, the infrastructures used to circulate data, the institutions involved in data governance and the communities involved in plant data work. We show how, across these domains, responsible plant data linkage involves consideration of technical, (...) legal, ethical and conceptual dimensions, thereby: (1) creating and maintaining digital infrastructures, technical standards and discussion venues focused on critical data reuse; (2) developing adequate legal and institutional frameworks that work transnationally; (3) identifying and implementing guidelines for what constitutes acceptable data use, together with systems to monitor and allocate responsibility for breaches and mistakes; and (4) considering the variety of views on what constitutes agricultural development in the first place and how plant research can sustainably, reliably and responsibly contribute to achieving food security. The production of sustainable, responsible and reliable agricultural solutions in the face of climatic and political change depends on the flourishing of transnational, interdisciplinary collaborations such as those represented in this volume. (shrink)

Introduction No consent for health and medical research is appropriate when the criteria for a waiver of consent are met, yet some ethics committees and data custodians still require informed consent. Methods A single-blind parallel-group randomised controlled trial: 1129 families of children born at a South Australian hospital were sent information explaining data linkage of childhood immunisation and hospital records for vaccine safety surveillance with 4 weeks to opt in or opt out by reply form, telephone or (...) email. A subsequent telephone interview gauged the intent of 1026 parents (91%) in relation to their actions and the sociodemographic differences between participants and non-participants in each arm. Results The participation rate was 21% (n=120/564) in the opt-in arm and 96% (n=540/565) in the opt-out arm (χ2 (1 df) = 567.7, p<0.001). Participants in the opt-in arm were more likely than non-participants to be older, married/de facto, university educated and of higher socioeconomic status. Participants in the opt-out arm were similar to non-participants, except men were more likely to opt out. Substantial proportions did not receive, understand or properly consider study invitations, and opting in or opting out behaviour was often at odds with parents' stated underlying intentions. Conclusions The opt-in approach resulted in low participation and a biased sample that would render any subsequent data linkage unfeasible, while the opt-out approach achieved high participation and a representative sample. The waiver of consent afforded under current privacy regulations for data linkage studies meeting all appropriate criteria should be granted by ethics committees, and supported by data custodians. Trial registration number Australian New Zealand Clinical Trials Registry ACTRN12610000332022. (shrink)

This paper draws upon the history of scientific studies of inheritance in Mendel’s best-remembered model organism, the garden pea, as a source of two parables – one pessimistic, the other optimistic – on the challenges of data linkage in plants. The moral of the pessimistic parable, from the era of the biometrician-Mendelian controversy, is that the problem of theory-ladenness in data sets can be a major stumbling block to making new uses of old data. The moral (...) of the optimistic parable, from the long-run history of studies at the John Innes Centre of aberrant or “rogue” pea varieties, is that an excellent guarantor of the continued value of old data sets is the availability of the relevant physical materials – in the first instance, the plant seeds. (shrink)

In today’s online data-driven world, people constantly shed data and deposit digital footprints. When individuals access health services, governments and health providers collect and store large volumes of health information about people that can later be retrieved, linked and analysed for research purposes. This can lead to new discoveries in medicine and healthcare. In addition, when securely stored and de-identified, the privacy risks are minimal and manageable. In many jurisdictions, ethics committees routinely waive the requirement for researchers to (...) obtain consent from data subjects before using and linking these datasets in an effort to balance respect for individuals with research efficiency. In this paper, I explore the ethical justification for using routinely collected health data for research without consent. I conclude that, not only is this morally justified but also that data subjects have a moral obligation to contribute their data to such research, which would obviate the need for ethics committees to consider consent waivers. In justifying this argument, I look to the duty of easy rescue, distributive justice and draw analogies with vaccination ethics. (shrink)

Research Ethics, Volume 18, Issue 2, Page 151-162, April 2022. In today’s online data-driven world, people constantly shed data and deposit digital footprints. When individuals access health services, governments and health providers collect and store large volumes of health information about people that can later be retrieved, linked and analysed for research purposes. This can lead to new discoveries in medicine and healthcare. In addition, when securely stored and de-identified, the privacy risks are minimal and manageable. In many (...) jurisdictions, ethics committees routinely waive the requirement for researchers to obtain consent from data subjects before using and linking these datasets in an effort to balance respect for individuals with research efficiency. In this paper, I explore the ethical justification for using routinely collected health data for research without consent. I conclude that, not only is this morally justified but also that data subjects have a moral obligation to contribute their data to such research, which would obviate the need for ethics committees to consider consent waivers. In justifying this argument, I look to the duty of easy rescue, distributive justice and draw analogies with vaccination ethics. (shrink)

Purpose This paper aims to discuss characteristics of Korea’s system responses with a research framework of the structure, conduct and performance theory and explain the role of information, communication technologies (ICT) and Big Data from a technology-mediated control (TMC) perspective. Design/methodology/approach This study examines the contextual nature of Korea’s diagnostic, preventive and treatment efforts. Particular attention is paid to issues related to the effective use of Big Data analytics and its applications, reporting mechanisms and public safety measures. The (...) research model defines key factors in assessing the effectiveness of Korea’s responses. Findings Findings of this research suggest: effective strategic planning and operational execution use well-tested and designed crisis-responsive manuals; linkage role of ICT/Big Data is prominent in trace, test and treat and participation (3T + P); and aggressive epidemic investigations require synergistic efforts of national and local government units, broad societal support and participation and contribution of global firms offering their domestic and global supply chain network capabilities. Research limitations/implications The Korean Government's effective response experiences suggest the synergy of political, social, cultural and technological factors. Future studies may explore how personal privacy and public safety are both achieved in different social–cultural–political contexts (Ahn et al., 2020; Delgado et al., 2020; Sharma and Bashir, 2020). Other emerging organizational issues and international comparative studies are worth further investigation in future studies. Practical implications This case study suggests how to apply ICT capabilities for organizing a national response to the coronavirus pandemic (COVID-19) pandemic. Public and private partnership in the framework of sociotechnological synergy (i.e. integration of ICT and social orchestration) is essential for the 3T process. In support of public policy initiatives, global firms share their IT infrastructure and supply chain integration experiences to accommodate global-level crises like the COVID-19 pandemic. Social implications This study extends the TMC framework to a national level. In the adapted TMC framework, the control source, control target and linkage mechanism are specified. Using TMC, this shows the dynamic roles of ICT/Big Data in Korea’s COVID-19 response experiences. Originality/value The impacts of the COVID-19 are rapid and enormous. Despite the controversial early policy decisions and the rapid rise of confirmed patients, the world has recognized Korea’s effective responses to the COVID-19 pandemic. (shrink)

BackgroundThe past 10 years have witnessed a significant growth in sharing of health data for secondary uses. Alongside this there has been growing interest in the public acceptability of data sharing and data linkage practices. Public acceptance is recognised as crucial for ensuring the legitimacy of current practices and systems of governance. Given the growing international interest in this area this systematic review and thematic synthesis represents a timely review of current evidence. It highlights the key (...) factors influencing public responses as well as important areas for further research.MethodsThis paper reports a systematic review and thematic synthesis of qualitative studies examining public attitudes towards the sharing or linkage of health data for research purposes. Twenty-five studies were included in the review. The included studies were conducted primarily in the UK and North America, with one study set in Japan, another in Sweden and one in multiple countries. The included studies were conducted between 1999 and 2013. The qualitative methods represented in the studies included focus groups, interviews, deliberative events, dialogue workshops and asynchronous online interviews.ResultsKey themes identified across the corpus of studies related to the conditions necessary for public support/acceptability, areas of public concern and implications for future research. The results identify a growing body of evidence pointing towards widespread general—though conditional—support for data linkage and data sharing for research purposes. Whilst a variety of concerns were raised in cases where participants perceived there to be actual or potential public benefits from research and had trust in the individuals or organisations conducting and/or overseeing data linkage/sharing, they were generally supportive. The studies also find current low levels of awareness about existing practices and uses of data.ConclusionsWhilst the results indicate widespread public support for data sharing and linkage for research purposes, a range of concerns exist. In order to ensure public support for future research uses of data greater awareness raising combined with opportunities for public engagement and deliberation are needed. This will be essential for ensuring the legitimacy of future health informatics research and avoiding further public controversy. (shrink)

Health‐related data uses and data sharing have been in the spotlight for a while. Since the beginning of the big data era, massive data mining and its inherent possibilities have only increased the debate about what the limits are. Data governance is a relevant aspect addressed in ethics guidelines. In this context, the European project BRIDGE Health (BRidging Information and Data Generation for Evidence‐based Health policy and research) strove to achieve a comprehensive, integrated and (...) sustainable EU health‐information system. One of the aims of the project was to evaluate the requirements to construct a data‐linkage infrastructure for the secure management of health information. In a blueprint provided for this infrastructure, the topics ethics and the intimately related governance occupied a whole section, where the recent ethics guidelines by the Council for International Organizations of Medical Sciences (CIOMS) and the World Medical Association (WMA) were referenced. We explore what has changed in the latest versions of the ethics documents adopted by CIOMS and WMA regarding the management of health data and human tissues, the appropriateness of their application in new forms of research and infrastructures as the proposed in the BRIDGE Health project, and whether society should be so concerned about this topic, in the digital era of social exchange. (shrink)

In the contemporary world, frugal innovation is the most discussed area to enhance corporate sustainable performance in manufacturing firms. The knowledge management process is also a key determinant of FI. Existing literature is limited to knowledge management and its impact on CSP. This study aims to determine the effect of the KMP on sustainable corporate performance with the association of FI. The survey method was used to collect data from 356 small and medium enterprises in China. Structure equation modeling (...) was applied to obtain the results of collected data. Results show that all three dimensions of KM have a significant impact on CSP. Furthermore, FI also has a significant and positive impact on CSP. Results further show that FI partially mediates the relationship of the knowledge dissemination, knowledge application and sustainable corporate performance but no mediation role FI was found between knowledge acquisition and CSP. The findings of this study will provide useful insights for experts and manufacturers. It will help to understand the role of KM in their organizational behavior by being an economical manufacturing process. This study underscored the importance of the KMP to policymakers. In countries such as China that have global orders, KM is an essential determinant of FI. KM is a tool used to achieve CSP goals inside and outside of an enterprise, thus the development firms need to focus on KM. (shrink)

Background Record linkage is a useful tool for health research. Potential benefits aside, its use raises discussions on privacy issues, such as whether a written informed consent for access to health records and linkage should be obtained. The authors aim to systematically review studies that assess consent proportions to record linkage. Methods 8 databases were searched up to June 2011 to find articles which presented consent proportions to record linkage. The screening, eligibility and inclusion of articles (...) were conducted by two independent reviewers. The authors carried out meta-regression, subgroup and sensitivity analyses to assess heterogeneity. Results Of the 141 studies identified, only 11 presented empirical consent proportions and were included in the systematic review. The consent proportion varied widely from 39% to 97%. Seven studies presented consent proportions of 88% or higher, one of 72%, and only three presented consented proportion equal to or lower than 53%. None of the studies' characteristics evaluated explained heterogeneity. Conclusion The results of this review show that, in general, individuals tend to consent to the use of their data for record linkage, with exceptions in specific populations or minorities. The authors believe that this, as well as the cited literature, lends support to policies that, while keeping relevant ethical controls in place, do not require individual informed consent for each and every study that relies on secondary data. (shrink)

Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the (...) context of their collection. The case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy. (shrink)

Data heterogeneity is the obstacle for the resource sharing on Semantic Web, and ontology is regarded as a solution to this problem. However, since different ontologies are constructed and maintained independently, there also exists the heterogeneity problem between ontologies. Ontology matching is able to identify the semantic correspondences of entities in different ontologies, which is an effective method to address the ontology heterogeneity problem. Due to huge memory consumption and long runtime, the performance of the existing ontology matching techniques (...) requires further improvement. In this work, an extended compact genetic algorithm-based ontology entity matching technique is proposed, which uses both the compact encoding mechanism and linkage learning approach to match the ontologies efficiently. Compact encoding mechanism does not need to store and maintain the whole population in the memory during the evolving process, and the utilization of linkage learning protects the chromosome’s building blocks, which is able to reduce the algorithm’s running time and ensure the alignment’s quality. In the experiment, ECGA-OEM is compared with the participants of ontology alignment evaluation initiative and the state-of-the-art ontology matching techniques, and the experimental results show that ECGA-OEM is both effective and efficient. (shrink)

BackgroundData processing of health research databases often requires a Data Protection Impact Assessment to evaluate the severity of the risk and the appropriateness of measures taken to comply with the European Union General Data Protection Regulation. We aimed to define and apply a comprehensive method for the evaluation of privacy, data governance and ethics among research networks involved in the EU Project Bridge Health.MethodsComputerised survey among associated partners of main EU Consortia, using a targeted instrument designed by (...) the principal investigator and progressively refined in collaboration with an international advisory panel. Descriptive measures using the percentage of adoption of privacy, data governance and ethical principles as main endpoints were used for the analysis and interpretation of the results.ResultsA total of 15 centres provided relevant information on the processing of sensitive data from 10 European countries. Major areas of concern were noted for: data linkage, access and accuracy of personal data and anonymisation procedures. A high variability was noted in the application of privacy principles.ConclusionsA comprehensive methodology of Privacy and Ethics Impact and Performance Assessment was successfully applied at international level. The method can help implementing the GDPR and expanding the scope of Data Protection Impact Assessment, so that the public benefit of the secondary use of health data could be well balanced with the respect of personal privacy. (shrink)

Large-scale linkage of international clinical datasets could lead to unique insights into disease aetiology and facilitate treatment evaluation and drug development. Hereto, multi-stakeholder consortia are currently designing several disease-specific translational research platforms to enable international health data sharing. Despite the recent adoption of the EU General Data Protection Regulation, the procedures for how to govern responsible data sharing in such projects are not at all spelled out yet. In search of a first, basic outline of an (...) ethical governance framework, we set out to explore relevant ethical principles and norms. We performed a systematic review of literature and ethical guidelines for principles and norms pertaining to data sharing for international health research. We observed an abundance of principles and norms with considerable convergence at the aggregate level of four overarching themes: societal benefits and value; distribution of risks, benefits and burdens; respect for individuals and groups; and public trust and engagement. However, at the level of principles and norms we identified substantial variation in the phrasing and level of detail, the number and content of norms considered necessary to protect a principle, and the contextual approaches in which principles and norms are used. While providing some helpful leads for further work on a coherent governance framework for data sharing, the current collection of principles and norms prompts important questions about how to streamline terminology regarding de-identification and how to harmonise the identified principles and norms into a coherent governance framework that promotes data sharing while securing public trust. (shrink)

Precision medicine is an emerging approach to treatment and disease prevention that relies on linkages between very large datasets of health information that is shared amongst researchers and health professionals. While studies suggest broad support for sharing precision medicine data with researchers at publicly funded institutions, there is reluctance to share health information with private industry for research and development. As the private sector is likely to play an important role in generating public benefits from precision medicine initiatives, it (...) is important to understand what the concerns are and how they might be mitigated. This study reports outcomes of a deliberative method of citizen engagement in Singapore that asked whether sharing precision medicine data with private industry would be permissible, and if so, under what circumstances. Findings from this citizens’ jury suggest sharing with industry would be permissible under certain conditions that are set out in nine recommendations. Implications of the recommendations and their underlying assumptions for policy decision makers are discussed. This study aligns with prior international studies which found conditional acceptance for data sharing with private industry, a public benefit requirement, specific reluctance to share with insurance companies and an emphasis on accountability and transparency to demonstrate trustworthiness. However, our results differ from prior studies in that opt-in consent did not dominate the deliberations as jurors were able to set it aside as an assumed prerequisite for participation in a precision medicine programme. (shrink)

One of the key features of the contemporary data economy is the widespread circulation of data and its interoperability. Critical data scholars have analysed data repurposing practices and other factors facilitating the travelling of data. While this approach focused on flows provides great potential, in this article we argue that it tends to overlook questions of attachment and belonging. Drawing upon ethnographic fieldwork within a Danish data-linkage infrastructure, and building upon insights from archival (...) science, we discuss the work of data practitioners enabling the repurposing of pathology samples extracted from patients for the conduct of ‘personal medicine’ – our term to discuss the so-called old-fashioned treatment of patients – towards personalised medicine. This first involves ‘getting to know’ the tissues and unpacking their previous uses and meanings, then detaching them from their original source to extract data from such tissues and making them flow towards a new container where they can be worked on and connected with other data. As data practitioners make these tissues travel, transforming them into research data, they organise the attachments of data to new agendas, persons and places. Crucially, in our case, we observe the prominence of national attachments, whereby managing tissues and data in and out of containers involves tying them to the nation to serve its interests. We thus expose how the building of data linkage infrastructures entails more than the accumulation and curation of data, but also involves crafting meanings, futures and belonging to specific communities and territories. (shrink)

The diversity of state confidentiality laws governing public health data presents a significant challenge for public health initiatives. This challenge is further complicated by the array of confidentially laws that are relevant within a state as disclosure and usage standards vary depending upon data holder, type, and source. These laws often have not been updated to address modern confidentiality risks such as unlawful data linkage or breach, leaving many public health organizations without clear guidance in the (...) contentious area of individual privacy. To address these challenges, public health organizations have increasingly turned to the science of de-identification, but whether de-identification adequately meets the many and varied state confidentiality legal requirements remains an unanswered question. (shrink)

The aim of UK-REACH (“The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers”) is to understand if, how, and why healthcare workers (HCWs) in the United Kingdom (UK) from ethnic minority groups are at increased risk of poor outcomes from COVID-19. In this article, we present findings from the ethical and legal stream of the study, which undertook qualitative research seeking to understand and address legal, ethical, and social acceptability issues around data protection, privacy, and (...) information governance associated with the linkage of HCWs’ registration data and healthcare data. We interviewed 22 key opinion leaders in healthcare and health research from across the UK in two-to-one semi-structured interviews. Transcripts were coded using qualitative thematic analysis. Participants told us that a significant aspect of Big Data research in public health is varying drivers of mistrust—of the research itself, research staff and funders, and broader concerns of mistrust within participant communities, particularly in the context of COVID-19 and those situated in more marginalised community settings. However, despite the challenges, participants also identified ways in which legally compliant and ethically informed approaches to research can be crafted to mitigate or overcome mistrust and establish greater confidence in Big Data public health research. Overall, our research indicates that a “Big Data Ethics by Design” approach to research in this area can help assure (1) that meaningful community and participant engagement is taking place and that extant challenges are addressed, and (2) that any new challenges or hitherto unknown unknowns can be rapidly and properly considered to ensure potential (but material) harms are identified and minimised where necessary. Our findings indicate such an approach, in turn, will help drive better scientific breakthroughs that translate into medical innovations and effective public health interventions, which benefit the publics studied, including those who are often marginalised in research. (shrink)

Following the rediscovery of Mendelian genetics, food supply pressures and the rapid expansion of crop varieties with defined performance characteristics, international systems were set up throughout the 20 C to regulate the trade of seed, the protection of intellectual property and the sale of productive varieties of key agricultural crops. These systems are a highly connected but largely linear set of processes. System changes are slow to be adopted due to the cascade of effects that structural alteration would have globally. (...) Multi-omic technologies and the subsequent proliferation of data types used within modern breeding, offer the possibility to gain deeper insights into the performance characteristics of varieties. Current integration of data, standards and ownership structures limit their applications for wider purposes, both private and public. We explore how data within and between breeding programmes and the varietal approval and monitoring processes could be made FAIR. We examine what role expanded or aligned programmes of data collection and expanded trait evaluation at the point of varietal registration and evaluation, as well as on farm could have in ensuring the best linkage of public and private data to address some of the challenges society faces over the next 30 years with the required, rapid transition to sustainable agricultural systems. (shrink)

Implementing the “hierarchical diagnosis and treatment” system highlights the important role of general practitioners as “residents’ health gatekeepers.” Still, the low level of career growth always limits the realization of their service value. Inertial thinking uses a single factor to explain the complexity of career growth in previous studies; in fact, it isn’t easy to assess whether the factor is a sufficient and necessary condition for a high level of career growth. Herein, we have used a set theory perspective to (...) analyze the mechanism of influencing high-level career growth by combining psychological and organizational factors. This research aims to analyze causal complexity relationship between these conditions and results is analyzed in detail. We choose fuzzy-set qualitative comparative analysis with a sample of 407 GPs to test 5 antecedent conditional variables that can affect their career growth. The variables include professional identity, self-efficacy, achievement motivation, training mechanism, and incentive mechanism. To ensure the universality and diversity of data, the samples were selected from community medical institutions in different regions of China. The results show that three pathways can affect the high career growth of GPs, and the optimal pathway A2 is the linkage matching of high incentive mechanism, high professional identity, high achievement motivation, and high self-efficacy. At the same time, we find that professional identity plays an alternative role in the three pathways. When professional identity is at a high level, as long as achievement motivation and self-efficacy are superior, or achievement motivation, self-efficacy, and achievement motivation are superior, a high level of career growth can be achieved. We broke the shackles of previous studies that only focused on the impact of single factors on the career growth of GPs. From the perspective of set theory, we use configurational thinking to construct Influential pathways of high career growth of GPs by integrating antecedents. The results can provide effective support for improving GPs’ service ability and realizing their service value to protect residents’ health. (shrink)

Linkage (or genetic) maps are graphs, which are intended to represent the linear ordering of genes on the chromosomes. They are constructed on the basis of statistical data concerning the transmission of genes. The invention of this technique in 1913 was driven by Morgan's group's adoption of a set of hypotheses concerning the physical mechanism of heredity. These hypotheses were themselves grounded in Morgan's defense of the chromosome theory of heredity, according to which chromosomes are the physical basis (...) of genes. In this paper, I analyze the 1919 debate between William Castle and Morgan's group, about the construction of genetic maps. The official issue of the debate concerns the arrangement of genes on chromosomes. However, the disputants tend to carry out the discussions about how one should model the data in order to draw predictions concerning the transmission of genes; the debate does not bear on the data themselves, nor does it focus on the hypotheses explaining these data. The main criteria that are appealed to by the protagonists are simplicity and predictive efficacy. However, I show that both parties' assessments of the simplicity and predictive efficacy of different ways of modeling the data themselves depend on background theoretical positions. I aim at clarifying how preference for a given model and theoretical commitments articulate. (shrink)

Discussion of uses of biomedical data often proceeds on the assumption that the data are generated and shared solely or largely within the health sector. However, this assumption must be challenged because increasingly large amounts of health and well-being data are being gathered and deployed in cross-sectoral contexts such as social media and through the internet of things and wearable devices. Cross-sectoral sharing of data thus refers to the generation, use and linkage of biomedical (...) class='Hi'>data beyond the health sector. This paper considers the challenges that arise from this phenomenon. If we are to benefit fully, it is important to consider which ethical values are at stake and to reflect on ways to resolve emerging ethical issues across ecosystems where values, laws and cultures might be quite distinct. In considering such issues, this paper applies the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research to the domain of cross-sectoral big data. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. (shrink)

Although similar environmental issues are present across the globe, residents of different countries vary in the extent to which they are concerned about and act upon these issues. Drawing on data from the 2010 Environment module of the International Social Survey Programme, this study tests the structural comparability of environmental attitudes across 32 countries and examines how pro-environmental behaviours are linked to relevant attitudes. A confirmatory factor analysis from structural equation modelling helps identify three latent constructs of environmental attitudes: (...) willingness to sacrifice, biospheric orientation and environmental scepticism. Further regression analyses reveal that the linkages between pro-environmental behaviours and the constructs of environmental attitudes converge in some countries but are less consistent in others. The findings help pinpoint signs of global convergence and national disparities, which merit more extensive analyses amid the recent surge in the availability of diverse empirical data from around the world. (shrink)

The use of big data to investigate the spread of infectious diseases or the impact of the built environment on human wellbeing goes beyond the realm of traditional approaches to epidemiology, and includes a large variety of data objects produced by research communities with different methods and goals. This paper addresses the conditions under which researchers link, search and interpret such diverse data by focusing on “data mash-ups”—that is the linking of data from epidemiology, biomedicine, (...) climate and environmental science, which is typically achieved by holding one or more basic parameters, such as geolocation, as invariant. We argue that this strategy works best when epidemiologists interpret localisation procedures through an idiographic perspective that recognises their context-dependence and supports a critical evaluation of the epistemic value of geolocation data whenever they are used for new research purposes. Approaching invariants as strategic constructs can foster data linkage and re-use, and support carefully-targeted predictions in ways that can meaningfully inform public health. At the same time, it explicitly signals the limitations in the scope and applicability of the original datasets incorporated into big data collections, and thus the situated nature of data linkage exercises and their predictive power. (shrink)

The collapse of confidence in anonymization as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left in its wake. In the latter category, and in large part due to the growth of Big Data–driven biomedical research, falls a growing chorus of calls for criminal and penal offences to sanction wrongful re-identification of “anonymized” data. This (...) chorus cuts across the fault lines of polarized privacy law scholarship that at times seems to advocate privacy protection at the expense of Big Data research or vice versa. Focusing on Big Data in the context of biomedicine, this article surveys the approaches that criminal or penal law might take toward wrongful re-identification of health data. It contextualizes the strategies within their respective legal regimes as well as in relation to emerging privacy debates focusing on personal data use and data linkage and assesses the relative merit of criminalization. We conclude that this approach suffers from several flaws and that alternative social and legal strategies to deter wrongful re-identification may be preferable. (shrink)

Previous studies have proposed a virtuous circle between corporate social performance (CSP) and corporate financial performance (CFP). However, a key challenge researchers face when empirically examining this virtuous circle is endogeneity. In this paper, we apply a well-developed method—dynamic panel data (DPD) estimation—to account for endogeneity and conduct two studies to reexamine the causal relationship between CSP and CFP. Study 1 relies on KLD ratings from 1997 to 2012 as the measure of CSP. According to the results of Study (...) 1, although CFP measured as ROE may have a causal impact on CSP, it is doubtful whether there is a causal influence of CSP on CFP. Study 2 relies on the sustainability scores provided by Sustainalytics from 2009 to 2018 as the measure of CSP. Study 2 reports that CSP does not causally influence CFP and that CFP does not have a causal impact on CSP. Together, Study 1 and Study 2, using different measures for CSP, suggest that a virtuous circle between CSP and CFP may not exist. Our study suggests that doing good may not necessarily lead to doing well and that doing well may not naturally result in doing good. Thus, our study implies that future studies should seriously consider the causal mechanisms through which CSP may influence or may be influenced by CFP. Our paper also discusses the implications for CSP research and for management and organization research. The limitations of applying DPD estimation to empirically examine the causal relationship between CSP and CFP are also discussed. (shrink)

This chapter argues for the importance of considering conceptual and normative commitments when addressing questions of responsible practice in data-intensive agricultural research and development. We consider genetic gain-focused plant breeding strategies that envision a data-intensive mode of breeding in which genomic, environmental and socio-economic data are mobilised for rapid crop variety development. Focusing on socio-economic data linkage, we examine methods of product profiling and how they accommodate gendered dimensions of breeding in the field. Through a (...) comparison with participatory breeding methods, we argue that the conceptual commitments underpinning current methods of integrating socioeconomic data into calculations of genetic gain can preclude the achievement of key social development goals, and that better engagement with participatory approaches can help address this problem. We conclude by identifying three key avenues towards a data-intensive approach to plant breeding that utilises the diverse sources of relevant evidence available, including socio-economic data, and maximises the chance of developing sustainable and responsible strategies and research practices in this domain: (1) reliable, long-term management of data infrastructures; (2) ongoing critical analysis of the conceptual foundations of specific strategies; and (3) regular transdisciplinary consultations including expertise in the social studies of agricultural science as well as participatory breeding techniques. (shrink)

Smartphones with Global Positioning System (GPS) apps offer simple and accurate tools to collect data on human mobility. However, their associated ethical challenges remain to be assessed. We used the Emanuel framework to assess the ethical concerns of using smartphone GPS to record mobility patterns of young adults in rural South Africa for a larger study on mobility and HIV risk (Sesikhona). We conducted four focus groups (FGDs) with individuals eligible for the Sesikhona study. FGD data were coded (...) using the Emanuel framework. Participants perceived use of smartphone GPS to study human mobility and HIV risk as valuable. They raised concerns about invasion of privacy and confidentiality. Also mentioned were risk/benefit ratio, informed consent and ongoing respect. Concerns expressed provided a useful evidence-base for the development of a guide to inform future participants about ethical issues arising in the use of GPS technology to track mobility and health-related issues. (shrink)

The use of big data to investigate the spread of infectious diseases or the impact of the built environment on human wellbeing goes beyond the realm of traditional approaches to epidemiology, and includes a large variety of data objects produced by research communities with different methods and goals. This paper addresses the conditions under which researchers link, search and interpret such diverse data by focusing on “data mash-ups”—that is the linking of data from epidemiology, biomedicine, (...) climate and environmental science, which is typically achieved by holding one or more basic parameters, such as geolocation, as invariant. We argue that this strategy works best when epidemiologists interpret localisation procedures through an idiographic perspective that recognises their context-dependence and supports a critical evaluation of the epistemic value of geolocation data whenever they are used for new research purposes. Approaching invariants as strategic constructs can foster data linkage and re-use, and support carefully-targeted predictions in ways that can meaningfully inform public health. At the same time, it explicitly signals the limitations in the scope and applicability of the original datasets incorporated into big data collections, and thus the situated nature of data linkage exercises and their predictive power. (shrink)

An individual's health, genetic, or environmental-exposure data, placed in an online repository, creates a valuable shared resource that can accelerate biomedical research and even open opportunities for crowd-sourcing discoveries by members of the public. But these data become “immortalized” in ways that may create lasting risk as well as benefit. Once shared on the Internet, the data are difficult or impossible to redact, and identities may be revealed by a process called data linkage, in which (...) online data sets are matched to each other. Reidentification, the process of associating an individual's name with data that were considered deidentified, poses risks such as insurance or employment discrimination, social stigma, and breach of the promises often made in informed-consent documents. At the same time, re-ID poses risks to researchers and indeed to the future of science, should re-ID end up undermining the trust and participation of potential research participants. The ethical challenges of online data sharing are heightened as so-called big data becomes an increasingly important research tool and driver of new research structures. Big data is shifting research to include large numbers of researchers and institutions as well as large numbers of participants providing diverse types of data, so the participants’ consent relationship is no longer with a person or even a research institution. In addition, consent is further transformed because big data analysis often begins with descriptive inquiry and generation of a hypothesis, and the research questions cannot be clearly defined at the outset and may be unforeseeable over the long term. In this article, we consider how expanded data sharing poses new challenges, illustrated by genomics and the transition to new models of consent. We draw on the experiences of participants in an open data platform—the Personal Genome Project—to allow study participants to contribute their voices to inform ethical consent practices and protocol reviews for big-data research. (shrink)

BackgroundThe rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the use (...) of a social licence for achieving such ethical governance.Main textWe performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence.ConclusionsThere are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance. (shrink)

The European Union Data Protection Regulation will have profound implications for public health, health services research and statistics in Europe. The EU Commission's Proposal was a breakthrough in balancing privacy rights and rights to health and healthcare. The European Parliament, however, has proposed extensive amendments. This paper reviews the amendments proposed by the European Parliament Committee on Civil Liberties, Justice and Home Affairs and their implications for health research and statistics. The amendments eliminate most innovations brought by the Proposal. (...) Notably, derogation to the general prohibition of processing sensitive data shall be allowed for public interests such as the management of healthcare services, but not health research, monitoring, surveillance and governance. The processing of personal health data for historical, statistical or scientific purposes shall be allowed only with the consent of the data subject or if the processing serves an exceptionally high public interest, cannot be performed otherwise and is legally authorised. Research, be it academic, government, corporate or market research, falls under the same rule. The proposed amendments will make difficult or render impossible research and statistics involving the linkage and analysis of the wealth of data from clinical, administrative, insurance and survey sources, which have contributed to improving health outcomes and health systems performance and governance; and may illegitimise efforts that have been made in some European countries to enable privacy-respectful data use for research and statistical purposes. If the amendments stand as written, the right to privacy is likely to override the right to health and healthcare in Europe. (shrink)

According to the hierarchy of models (HoM) account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics (HEP) experiments. I argue that even though the HoM account aims to (...) characterize experimentation as a model-based activity, it does not involve a modeling concept for the process of data acquisition, and it thus fails to provide a model-based characterization of the theory-experiment relationship underlying this process. In order to characterize the foregoing relationship, I propose the concept of a model of data acquisition and illustrate it in the case of the ATLAS experiment at CERN’s Large Hadron Collider, where the Higgs boson was discovered in 2012. I show that the process of data acquisition in the ATLAS experiment is performed according to a model of data acquisition that specifies and organizes the experimental procedures necessary to select the data according to a predetermined set of selection criteria. I also point out that this data acquisition model is theory-laden, in the sense that the underlying data selection criteria are determined by considering the testable predictions of the theoretical models that the ATLAS experiment is aimed to test. I take this sense of theory-ladenness to indicate that the relationship between the procedures of the ATLAS experiment and the theoretical models of the phenomena of interest is first established, prior to the formation of data models, through the data acquisition model of the experiment, thus not requiring the intermediary of other types of models as suggested by the HoM account. I therefore conclude that in the context of present-day HEP experiments, the HoM account does not consistently extend to the process of data acquisition so as to include models of data acquisition. (shrink)

According to the hierarchy of models account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics experiments. I argue that even though the HoM account aims to characterize experimentation (...) as a model-based activity, it does not involve a modeling concept for the process of data acquisition, and it thus fails to provide a model-based characterization of the theory-experiment relationship underlying this process. In order to characterize the foregoing relationship, I propose the concept of a model of data acquisition and illustrate it in the case of the ATLAS experiment at CERN’s Large Hadron Collider, where the Higgs boson was discovered in 2012. I show that the process of data acquisition in the ATLAS experiment is performed according to a model of data acquisition that specifies and organizes the experimental procedures necessary to select the data according to a predetermined set of selection criteria. I also point out that this data acquisition model is theory-laden, in the sense that the underlying data selection criteria are determined by considering the testable predictions of the theoretical models that the ATLAS experiment is aimed to test. I take this sense of theory-ladenness to indicate that the relationship between the procedures of the ATLAS experiment and the theoretical models of the phenomena of interest is first established, prior to the formation of data models, through the data acquisition model of the experiment, thus not requiring the intermediary of other types of models as suggested by the HoM account. I therefore conclude that in the context of present-day HEP experiments, the HoM account does not consistently extend to the process of data acquisition so as to include models of data acquisition. (shrink)

This paper examines classification practices in the domain of plant data semantics, and particularly methods used to label plant traits to foster the collection, management, linkage and analysis of data about crops across locations—which crucially inform research and interventions on plants and agriculture. The efforts required to share data place in sharp relief the forms of diversity characterizing the systems used to capture the biological and environmental characteristics of plant variants: particularly the biological, cultural, scientific and (...) semantic diversity affecting the identification and description of plant traits, the methods used to generate and process data, and the goals and skills of those with relevant expertise—including farmers and breeders. Through a study of the Crop Ontology (which explicitly recognizes and negotiates diversity) and its application to cassava breeding, I argue for a process-sensitive approach to the naming of plant traits that focuses on documenting environmental processes instead of biological products. I claim that this approach can foster reliable linkage and robust re-use of plant data, while at the same time facilitating dialogue between data scientists, plant researchers, breeders, and other relevant experts in ways that crucially inform agricultural interventions. I conclude that the study of data semantics and related descriptors constitutes a productive and underexplored way to think about the epistemic import of naming traits within plant science. The effort to articulate semantic differences among plant varieties and methods of data processing can generate newly inclusive ways to develop and communicate biological knowledge. In turn, such practices have the potential to defy existing understandings of systematisation and hierarchies of expertise in biology, thus bolstering the extent to which plant science can support biodiversity and sustainable agriculture. (shrink)

ObjectiveWe wished to explore Parkinson's disease subtypes by clustering analysis based on the multimodal magnetic resonance imaging indices amplitude of low-frequency fluctuation and gray matter volume. Then, we analyzed the differences between PD subtypes.MethodsEighty-six PD patients and 44 healthy controls were recruited. We extracted ALFF and GMV according to the Anatomical Automatic Labeling partition using Data Processing and Analysis for Brain Imaging software. The Ward linkage method was used for hierarchical clustering analysis. DPABI was employed to compare differences (...) in ALFF and GMV between groups.ResultsTwo subtypes of PD were identified. The “diffuse malignant subtype” was characterized by reduced ALFF in the visual-related cortex and extensive reduction of GMV with severe impairment in motor function and cognitive function. The “mild subtype” was characterized by increased ALFF in the frontal lobe, temporal lobe, and sensorimotor cortex, and a slight decrease in GMV with mild impairment of motor function and cognitive function.ConclusionHierarchical clustering analysis based on multimodal MRI indices could be employed to identify two PD subtypes. These two PD subtypes showed different neurodegenerative patterns upon imaging. (shrink)

Starting from the observation that data sharing in general and sharing of reusable behavioral data in particular is still scarce in psychology, we set out to develop a curation standard for behavioral psychological research data rendering data reuse more effective and efficient. Specifically, we propose a standard that is oriented toward the requirements of the psychological research process, thus considering the needs of researchers in their role as data providers and data users. To this (...) end, we suggest that researchers should describe their data on three documentation levels reflecting researchers’ central decisions during the research process. In particular, these levels describe researchers’ decisions on the concrete research design that is most suitable to address the corresponding research question, its operationalization as well as a precise description of the subsequent data collection and analysis process. Accordingly, the first documentation level represents, for instance, researchers’ decision on the concrete hypotheses, inclusion/exclusion criteria and the number of measurement points as well as a conceptual presentation of all substantial variables included in the design. On the second level these substantial variables are presented within an extended codebook allowing for the linkage between the conceptual research design and the actually operationalized variables as presented within the data. Finally, the third level includes all materials, data preparation and analyses scripts as well as a detailed procedure graphic that allows the data user to link the information from all three documentation levels at a single glance. After a comprehensive presentation of the standard, we will offer some arguments for its integration into the psychological research process. (shrink)

Background The opioid epidemic has enabled rapid and unsurpassed use of big data on people with opioid use disorder to design initiatives to battle the public health crisis, generally without adequate input from impacted communities. Efforts informed by big data are saving lives, yielding significant benefits. Uses of big data may also undermine public trust in government and cause other unintended harms. Objectives We aimed to identify concerns and recommendations regarding how to use big data on (...) opioid use in ethical ways. Methods We conducted focus groups and interviews in 2019 with 39 big data stakeholders who had interest in or knowledge of the Public Health Data Warehouse maintained by the Massachusetts Department of Public Health. Results Concerns regarding big data on opioid use are rooted in potential privacy infringements due to linkage of previously distinct data systems, increased profiling and surveillance capabilities, limitless lifespan, and lack of explicit informed consent. Also problematic is the inability of affected groups to control how big data are used, the potential of big data to increase stigmatization and discrimination of those affected despite data anonymization, and uses that ignore or perpetuate biases. Participants support big data processes that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions. Recommendations for ethical big data governance offer ways to narrow the big data divide, enact shared data governance, cultivate public trust and earn social license for big data uses, and refocus ethical approaches. Conclusions Using big data to address the opioid epidemic poses ethical concerns which, if unaddressed, may undermine its benefits. Findings can inform guidelines on how to conduct ethical big data governance and in ways that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions. (shrink)

Hunt and Vitell''s General Theory (1992) is used in a cross-cultural comparison of U.S. and Taiwanese business practitioners. Results indicate that Taiwanese practitioners exhibit lower perceptions of an ethical issue in a scenario based on bribery, as well as milder deontological evaluations and ethical judgments relative to their U.S. counterparts. In addition, Taiwan respondents showed higher likelihood of making the payment. Several of the paths between variables in the theory are confirmed in both U.S. and Taiwan samples, with summary (...) class='Hi'>data suggesting the Hunt and Vitell theory performs well in both U.S. and Taiwan. Some unanticipated linkages within the model were uncovered in the samples. Results and implications are discussed. (shrink)

Contemporary Information Systems management incorporates the need to make explicit the links between semiotics, meaning-making and the digital age. This focus addresses, at its core, pure rationality, that is, the capacity of human interpretation and of human inscription upon reality. Creating the new real, that is the motto. Humans are intrinsically semiotic creatures. Consequently, semiotics is not a choice or an option but something that works like a second skin, establishing limits and permeable linkages between: human thought and human's infinite (...) world of imagination; and human action, with its correspondent infinite world of intentionality, of desire and of unexplored possibilities. Two instances are contrasted as two reading lenses of current business reality: IS governance and industry 4.0. These phenomena correspond to the need to take accountability, transparency and responsibility into account, when designing IS and when using such systems through the ecology of connectivity, Big Data and the Internet of Things. Political, social and cultural dimensions are brought into the equation, when addressing the question of the relevance and adequateness of IS theory and practice to respond to contemporary challenges. The message is that what has already been achieved is but a shadow, a pale vision, of what might be achieved in the age of the new Renaissance. (shrink)

Research has shown that paternal involvement positively impacts on child health and development. We aimed to develop a conceptual model of dimensions of fatherhood, identify and categorise methods used for linking fathers with their children in administrative data, and map these methods onto the dimensions of fatherhood. We carried out a systematic scoping review to create a conceptual framework of paternal involvement and identify studies exploring the impact of paternal exposures on child health and development outcomes using administrative (...) class='Hi'>data. We identified four methods that have been used globally to link fathers and children in administrative data based on family or household identifiers using address data, identifiable information about the father on the child's birth registration, health claims data, and Personal Identification Numbers. We did not identify direct measures of paternal involvement but mapping linkage methods to the framework highlighted possible proxies. The addition of paternal National Health Service numbers to birth notifications presents a way forward in the advancement of fatherhood research using administrative data sources. (shrink)

Baumard proposes a model to explain the dramatic rise in innovation that occurred during the Industrial Revolution, whereby rising living standards led to slower life history strategies, which, in turn, fostered innovation. We test his model explicitly using time series data, finding limited support for these proposed linkages. Instead, we find evidence that rising living standards appear to have a time-lagged bidirectional relationship with increasing innovation.