BackgroundInstitutions, funding agencies and publishers are placing increasing emphasis on good research data management (RDM). RDM lapses in medical science can result in questionable data and cause the public’s confidence in the scientific community to crumble. A fledgling medical school in a young university in Singapore has mandated every funded research project to have a data management plan (DMP). However, researchers’ adherence to their DMPs was unknown until the school embarked on routine (...) class='Hi'>data auditing. We hypothesize that research data auditing improves RDM awareness, compliance and reception in the school.MethodsWe conducted surveys with research PIs and researchers before and after data auditing to evaluate differences in self-reported RDM awareness, compliance and reception. As it is mandatory to deposit research data in a central data repository system in the school, we tracked data deposition by each laboratory from 2 weeks before to 3 months after data auditing as a marker of actual RDM compliance.ResultsResearch data auditing had an overall positive effect on self-reported RDM awareness, compliance and reception for both research PIs and researchers. Research PIs agreed more that RDM was important to scientific reproducibility, were more aware of proper RDM, had higher RDM strength in their laboratories and were more compliant with the DMP. Both research PIs and researchers believed data auditing helped them to be more compliant with data deposition in the repository. However, data auditing had no significant impact on laboratories’ data deposition rates over time, which could be due to the short sampling period.ConclusionsResearch PIs and researchers generally felt that data auditing was effective in improving RDM practices. It helped to evaluate their RDM practices objectively, propose corrective actions for RDM lapses and spread awareness of the university’s data management policies. Our findings corroborated other studies in medical research, geosciences, engineering and ethics that data auditing promotes good RDM practices. Hence, we recommend research institutions worldwide to adopt data auditing as a tool to reinforce research integrity. (shrink)

Responsible data management is a multifaceted topic involving standards within the research community regarding research design and the sharing of data as well as the collection, selection, analysis and interpretation of data. Transparency in the manipulation of images is increasingly important in order to avoid misrepresentation of research findings, and research oversight is also critical in helping to assure the integrity of the research process. Intellectual property issues both unite and divide (...) academe and industry in their approaches to data management. Central to the realization and promulgation of responsible data management is clear and careful communication of standards and expectations within the research community to trainees as well as among colleagues. These topics are examined and explored in depth in a special issue of Science and Engineering Ethics on responsible data management. (shrink)

Data management raises a number of issues, both regulatory and non-regulatory. Researchers should understand how data are defined by their particular institutions and regulatory authorities. Data are the bases of scientific communication and provide a strong defense against allegations of scientific misconduct. Authorization is often necessary before collection of data can commence. Proper handling, retention, and storage of data, especially that involving humans, are crucial for the researcher. Data ownership by the institution leads (...) to a responsibility by the institution to educate all its researchers in responsible data management practices. (shrink)

Low levels of public trust in data practices have led to growing calls for changes to data-driven systems, and in the EU, the General Data Protection Regulation provides a legal motivation for such changes. Data management is a vital component of data-driven systems, but what constitutes ‘good’ data management is not straightforward. Academic attention is turning to the question of what ‘good data’ might look like more generally, but public views are (...) absent from these debates. This paper addresses this gap, reporting on a survey of the public on their views of data management approaches, undertaken by the authors and administered in the UK, where departure from the EU makes future data legislation uncertain. The survey found that respondents dislike the current approach in which commercial organizations control their personal data and prefer approaches that give them control over their data, that include oversight from regulatory bodies or that enable them to opt out of data gathering. Variations of data trusts – that is, structures that provide independent stewardship of data – were also preferable to the current approach, but not as widely preferred as control, oversight and opt out options. These features therefore constitute ‘good data management’ for survey respondents. These findings align only in part with principles of good data identified by policy experts and researchers. Our findings nuance understandings of good data as a concept and of good data management as a practice and point to where further research and policy action are needed. (shrink)

Background There has been considerable investment and strategic planning to introduce genomic testing into Australia’s public health system. As more patients’ genomic data is being held by the public health system, there will be increased requests from researchers to access this data. It is important that public policy reflects public expectations for how genomic data that is generated from clinical tests is used. To inform public policy and discussions around genomic data sharing, we sought public opinions (...) on using genomic data contained in medical records for research purposes in the Australian state of Queensland. Methods A total of 1494 participants completed an online questionnaire between February and May 2019. Participants were adults living in Australia. The questionnaire explored participant preferences for sharing genomic data or biological samples with researchers, and concerns about genomic data sharing. Results Most participants wanted to be given the choice to have their genomic data from medical records used in research. Their expectations on whether and how often they needed to be approached for permission on using their genomic data, depended on whether the data was identifiable or anonymous. Their willingness to sharing data for research purposes depended on the type of information being shared, what type of research would be undertaken and who would be doing the research. Participants were most concerned with genomics data sharing that could lead to discrimination, data being used for marketing, data security, or commercial use. Conclusions Most participants were willing to share their genomic data from medical records with researchers, as long as permission for use was sought. However, the existing policies related to this process in Queensland do not reflect participant expectations for how this is achieved, particularly with anonymous genomics data. This inconsistency may be addressed by process changes, such as inclusion of research in addition to clinical consent or general research data consent programs. (shrink)

Since January 2016, the Mahidol Oxford Tropical Medicine Research Unit has trialled a data-sharing policy where requests to access research datasets are processed through a Data Access Committee. In this paper, we share our experiences establishing data management systems and data-sharing infrastructure including a data-sharing policy, data access committee and related procedures. We identified a number of practical and ethical challenges including requests for datasets collected without specific or broad consent to (...) data sharing and requests from pharmaceutical companies for data to support drug registration applications. We also encountered significant resource constraints which required the development of appropriate human resources and infrastructure. We suggest a research agenda to promote responsible and equitable data sharing while safeguarding the rights and interests of research participants and researchers. (shrink)

With the rapid growth of information technology and sports, analyzing sports information has become an increasingly challenging issue. Sports big data come from the Internet and show a rapid growth trend. Sports big data contain rich information such as athletes, coaches, athletics, and swimming. Nowadays, various sports data can be easily accessed, and amazing data analysis technologies have been developed, which enable us to further explore the value behind these data. In this paper, we first (...) introduce the background of sports big data. Secondly, we review sports big data management such as sports big data acquisition, sports big data labeling, and improvement of existing data. Thirdly, we show sports data analysis methods, including statistical analysis, sports social network analysis, and sports big data analysis service platform. Furthermore, we describe the sports big data applications such as evaluation and prediction. Finally, we investigate representative research issues in sports big data areas, including predicting the athletes’ performance in the knowledge graph, finding a rising star of sports, unified sports big data platform, open sports big data, and privacy protections. This paper should help the researchers obtaining a broader understanding of sports big data and provide some potential research directions. (shrink)

With the powerful analyses and resources they enable, digital humanities tools have captivated researchers from many different fields who want to use them to study science. Digital tools, as well as funding agencies, research communities, and academic administrators, require researchers to think carefully about how they conceptualize, manage, and store data, and about what they plan to do with that data once a given project is over. The difficulties of developing strategies to address these problems can prevent (...) new researchers from sticking with digital tools and flummox even experienced researchers. To help overcome the data hurdle, we present five principles to help researchers, novice and experienced alike, conceptualize and plan for their data. We illustrate the use of those principles with two digital projects from the history of science, the Embryo Project and the Marine Biological Laboratory History Project, and their associated HPS Repository for data. The principles apply beyond the digital realm, so those who collect and manage data by more traditional means will also find them useful. (shrink)

The main purpose of this study is to examine the impact of the big data management capabilities on the performance of manufacturing firms in the Asian Economy during coronavirus disease 2019. In addition to this, this study is also planned to examine the mediating role of organizational agility in the relationship between the big data management capabilities and the performance of Chinese manufacturing firms during COVID-19. Last, this study has examined the moderating role of information technology (...) capability in the relationship between the big data management capabilities and performance of Chinese manufacturing firms during COVID-19. This study adopted the quantitative method of research with a cross-sectional technique. This study employed a questionnaire to gather the data as a research instrument. This study has used the purposive sampling method by keeping in mind the context of this study. Employees of the Chinese SMEs that were at least 10 years old were the population of this study. The research model was being analyzed by employing the “partial least squares” technique through statistical software the Smart PLS version 3. The results are in line with the proposed hypothesis. This study contributed to the literature by suggesting characteristics that promote or prevent the organization from successfully implementing big data and pointed out that showing resistance in information management system implementation may have different effects on the organization. Besides, the study also discussed the relationship between such information systems and the organization. Findings of these two factors provide insights for the practitioners and researchers in assessing the success or failure of organizations for using big data. (shrink)

Making research data readily accessible during a public health emergency can have profound effects on our response capabilities. The moral milieu of this data sharing has not yet been adequately explored. This article explores the foundation and nature of a duty, if any, that researchers have to share data, specifically in the context of public health emergencies. There are three notable reasons that stand in opposition to a duty to share one’s data, relating to: (i) (...) data property and ownership, (ii) just distribution of benefits and burdens and (iii) the contemporary ethos of science. We argue each reason can be successfully met with corresponding rationale in favour of data sharing. Further support for data sharing has been echoed in policies of health agencies, funding bodies and academic institutions; in documents on the ethical conduct of biomedical research; and in discussions on the nature of public health. From this, we ascertain that sharing data is the morally sound default position. This article then highlights the key roles reciprocity and solidarity play in supporting the practice of data sharing. We conclude with recommendations to regard public health research data as a common-pool resource in order to build a framework for stable data sharing management. (shrink)

BackgroundThe widespread sharing of biological and biomedical data is recognised as a key element in facilitating translation of scientific discoveries into novel clinical applications and services. At the same time, twenty-first century states are increasingly concerned that this data could also be used for purposes of bioterrorism. There is thus a tension between the desire to promote the sharing of data, as encapsulated by the Open Data movement, and the desire to prevent this data from (...) ‘falling into the wrong hands’ as represented by ‘dual use’ policies. Both frameworks posit a moral duty for life sciences researchers with respect to how they should make their data available. However, Open data and dual use concerns are rarely discussed in concert and their implementation can present scientists with potentially conflicting ethical requirements.DiscussionBoth dual use and Open data policies frame scientific data and data dissemination in particular, though different, ways. As such they contain implicit models for how data is translated. Both approaches are limited by a focus on abstract conceptions of data and data sharing. This works to impede consensus-building between the two ethical frameworks. As an alternative, this paper proposes that an ethics of responsible management of scientific data should be based on a more nuanced understanding of the everyday data practices of life scientists. Responsibility for these ‘micromovements’ of data must consider the needs and duties of scientists as individuals and as collectively-organised groups.SummaryResearchers in the life sciences are faced with conflicting ethical responsibilities to share data as widely as possible, but prevent it being used for bioterrorist purposes. In order to reconcile the responsibilities posed by the Open Data and dual use frameworks, approaches should focus more on the everyday practices of laboratory scientists and less on abstract conceptions of data. (shrink)

We send messages as much in how we communicate as by what we communicate. Learning best practices, such as those for data management proposed in the accompanying article, are components of becoming a responsible and contributing member of the community of scholars. Not only must we teach the principles underlying best practices, we should model and teach approaches for implementing those practices and help students come to view them within the larger context of becoming members of a professional (...) community. How to collaborate across differences and how to have disputes professionally are skills all professionals need, and they should be taught along with the content itself. (shrink)

This paper provides an in-depth analysis and discussion of the key issues of quality management, evaluation, and detection contained in big data for automotive application scenarios. A generalized big data quality management model and programming framework are proposed, and a series of data quality detection and repair interfaces are built to express the processing semantics of various data quality issues. Through this data quality management model and detection and repair interfaces, users can (...) quickly build custom data quality detection and repair tasks for different data quality requirements. To improve the operational efficiency of complex data quality management algorithms in large-scale data scenarios, corresponding parallelization algorithms are studied and implemented for detection and repair algorithms with long computation time, including priority-based multiconditional function-dependent detection and repair algorithms, entity detection, and extraction algorithms based on semantic information and chunking techniques, and plain Bayesian-based missing value filling algorithms, and this paper proposes a data validity evaluation algorithm and enhances the validity of the original data in practical applications by adding temporal weights, and finally it passed the experimental validation. Through the comprehensive detection process of data importance, network busyness, duration of transmission process, and failure situation, the efficiency has been increased by 20%, and an adaptive data integrity detection method based on random algorithm and encryption algorithm is designed. After experimental verification, this method can effectively detect the integrity of the data transmission process and improve the application of data value, and the final effect is increased by 30.5%. (shrink)

A multitude of legislation impacts the use of samples and data for research in South Africa. With the coming into effect of the Protection of Personal Information Act No. 4 of 2013 in July 2021, recent attention has been given to safeguarding research participants’ personal information. The protection of participants’ privacy in research is essential, but it is not the only risk at stake in the use and sharing of personal information. Other rights and interests that (...) must also be considered and safeguarded include the right to non-discrimination, the right to dignity, and the right to enjoy the benefits of scientific progress. This can be achieved by ensuring that the ethical values and universal principles that underpin the research landscape, namely equity, reciprocity, justice and solidarity, are embedded in the regulatory framework for the management and use of personal information. This paper advocates an integrated bioethics approach to the use of personal information for research in SA. A key feature in embedding such an approach is a Data Transfer Agreement that appropriately integrates the safeguards and protections set out by our regulatory framework with bioethical rules and procedures when personal information is used and shared for research purposes. This paper thus calls for the development of a national DTA that is guided by key ethical principles when data are shared for research purposes. This paper will be followed by a webinar on 23 June 2022 hosted by the Department of Science and Innovation and the SA Medical Research Council, where the recommendations and suggestions set out herein will be unpacked, discussed and debated by relevant stakeholders. (shrink)

A course focusing on ethical issues in physics has been taught to undergraduate students at Eastern Michigan University since 1988. The course covers both responsible conduct of research and ethical issues associated with how physicists interact with the rest of society. Since most undergraduate physics majors will not have a career in academia, it is important that a course such as this address issues that will be relevant to physicists in a wide range of job situations. There is a (...) wealth of published work that can be drawn on for reading assignments. (shrink)

This article investigates dilemmas in the archiving and sharing of qualitative data in educational research, critically engaging with practices and debates from across the social sciences. Ethical, epistemological and methodological challenges are examined in reference to open access agendas, the politics of knowledge production, and transformations in research practices in the era of data management. We first consider practical and interpretive decisions in archiving qualitative data, then map current policy and regulatory frameworks governing (...) class='Hi'>research data management, taking Australia as a case-study. We argue that governance and protocols for data sharing have not attended sufficiently to the distinctive ethical and methodological dimensions and knowledge claims of qualitative research. Instead, approaches associated with quantitative data are extrapolated in ways which construct an imaginary of decontextualised data, abstracted from the conditions of its production. We further argue for more critical attention to the double-edged affordances and ambivalent effects of data sharing and openness and to how data archives are imagined, constructed and curated. This includes greater acknowledgement of the affective and temporal dynamics involved in data archiving, understanding them as practices of (re)invention that also curate ‘archives for the future’ and help to foster an historicising imaginary in educational research. (shrink)

Nowadays, the modern management is promoted to resolve the issue of unreliable information transmission and to provide work efficiency. The basic aim of the modern management is to be more effective in the role of the school to train talents and serve the society. This article focuses on the application of data mining (DM) in the development of information management system (IMS) in universities and colleges. DM provides powerful approaches for a variety of educational areas. Due (...) to the large amount of student information that can be used to design valuable patterns relevant to student learning behavior, research in the field of education is continuously expanding. Educational data mining can be used by educational institutions to assess student performance, assisting the institution in recognizing the student’s accomplishments. In DM, classification is a well-known technique that has been regularly used to determine student achievement. In this study, the process of DM and the application research of association rules is introduced in the development of IMS in universities and colleges. The results show that the curriculum covers the whole field and the minimum transaction support count be 2, minconf = 70%. The results also suggested that students who choose one course also tend to choose the other course. The application of DM theory in university information will greatly upsurge the data analysis capability of administrators and improve the management level. (shrink)

There is a growing interest in the ethics of Health Policy and Systems Research, and especially in areas that have particular ethical salience across HPSR. Hyder et al provide an initial framework to consider this, and call for more conceptual and empirical work. In this paper, we respond by examining the ethical issues that arose for researchers over the course of conducting three HPSR studies in Kenya in which health managers and providers were key participants. All three studies involved (...) qualitative work including observations and individual and group interviews. Many of the ethical dilemmas researchers faced only emerged over the course of the fieldwork, or on completion, and were related to interactions and relationships between individuals operating at different levels or positions in health/research systems. The dilemmas reveal significant ethical challenges for these forms of HPSR, and show that potential ‘solutions’ to dilemmas often lead to new issues and complications. Our experiences support the value of research ethics frameworks, and suggest that these can be enriched by incorporating careful consideration of context embedded social relations into research planning and conduct. Many of these essential relational elements of ethical practice, and of producing quality data, are given stronger emphasis in social science research ethics than in epidemiological, clinical or biomedical research ethics, and are particularly relevant where health systems are understood as social and political constructs. We conclude with practical and research implications. (shrink)

BackgroundCommunity engagement in research is valuable for instrumental and intrinsic reasons. Despite existing guidance on how to ensure meaningful CE, much of what it takes to achieve this goal differs across settings. Considering the emerging trend towards mandating CE in many research studies, this study aimed at documenting how CE is conceptualized and implemented, and then providing context-specific guidance on how researchers and research regulators in Uganda could think about and manage CE in research.MethodsWe conducted qualitative (...) interviews and focus group discussions involving forty-one respondents who were experienced in HIV/aids biomedical research involving CE. Thirty-eight of these were directly or indirectly associated with Uganda’s leading research institution in the field of HIV/aids. They included Principal Investigators, Community Liaisons Officers, Research Ethics Committee members and Community Advisory Board Members. Three respondents were from Uganda National Council for Science and Technology. Data were collected between August 2019 and August 2020, using audio-taped focus group discussions and key informant interviews, transcribed and analyzed manually to generate themes and subthemes.ResultsThree major themes emerged: goals or value of CE; the means of CE, and, the evaluation of CE. Goals or value of CE generated four subthemes representing the overarching goals of CE: Promote communities’ agency; Generate and sustain trust; Protect and promote communities’ rights and interests; and, Help studies optimize participation in the form of enrolment and retention of participants. What usually comes under the nomenclatures of methods, strategies, and approaches of CE, such as town-hall meetings, sports events, drama, and the like, should simply be understood as the means of CE, and it is not desirable to hold pre-conceived and fixed ideas about the best means to conduct CE in research since a lot depend on the context. Finally, the study found that despite CE’s critical importance, which suggests the need to track and evaluate it, CE is currently intermittently evaluated, and for inadequate motivations.ConclusionsExisting guidance on how to conduct robust CE in research is no substitute for creativity, flexibility, and reflexivity on the part of both researchers and research regulators. (shrink)

One of the insights gained from editing a journal is to see early trends in the research topics of submissions. The ethics of data management in healthcare is an issue on which we have published a...

Biobanking in Europe has made major steps towards harmonization and shared standards for the collection and processing of data and samples stored in biobanks. Still, biobanks and researchers face substantial legal difficulties in the field of data protection and sample management. Data protection law was harmonized almost 15 years ago while rights in samples fall under the competence of the Member States of the EU. Despite the Data Protection Directive the field of data protection (...) shows a substantial degree of deviation as public health was excluded from the harmonization. Biobanks seem to have substantially fewer difficulties to cope with in terms of the legal requirements in the field of sample management. This paper discusses the legal framework, experiences of different biobanks in Europe and potential ways forward. It also highlights the need for a health economic analysis of the costs and benefits of privacy protection in Europe. At the moment, policymakers seem to build their decisions on an insufficient evidence base which underestimates the potential value of biobanks for European public health. Within the past few years little progress has been achieved with regards to the development of a unified legal framework in Europe, The diversity in the legal system is also reflected in the different approaches of ethics committees towards biobanking. To secure the responsible and effective use of data and samples, more efforts are needed to come up with pathways for a solution. (shrink)

Biobanking in Europe has made major steps towards harmonization and shared standards for the collection and processing of data and samples stored in biobanks. Still, biobanks and researchers face substantial legal difficulties in the field of data protection and sample management. Data protection law was harmonized almost 15 years ago while rights in samples fall under the competence of the Member States of the EU. Despite the Data Protection Directive the field of data protection (...) shows a substantial degree of deviation as public health was excluded from the harmonization. Biobanks seem to have substantially fewer difficulties to cope with in terms of the legal requirements in the field of sample management. This paper discusses the legal framework, experiences of different biobanks in Europe and potential ways forward. It also highlights the need for a health economic analysis of the costs and benefits of privacy protection in Europe. At the moment, policymakers seem to build their decisions on an insufficient evidence base which underestimates the potential value of biobanks for European public health. Within the past few years little progress has been achieved with regards to the development of a unified legal framework in Europe, The diversity in the legal system is also reflected in the different approaches of ethics committees towards biobanking. To secure the responsible and effective use of data and samples, more efforts are needed to come up with pathways for a solution. (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)

Recent studies highlight the need for ethical and equitable digital health research that protects the rights and interests of racialized communities. We argue for practices in digital health that promote data self-determination for these communities, especially in data collection and management. We suggest that researchers partner with racialized communities to curate data that reflects their wellness understandings and health priorities, and respects their consent over data use for policy and other outcomes. These data (...) governance approach honors and builds on Indigenous Data Sovereignty (IDS) decolonial scholarship by Indigenous and non-indigenous researchers and its adaptations to health research involving racialized communities from former European colonies in the global South. We discuss strategies to practice equity, diversity, inclusion, accessibility and decolonization (EDIAD) principles in digital health. We draw upon and adapt the concept of Precision Health Equity (PHE) to emphasize models of data sharing that are co-defined by racialized communities and researchers, and stress their shared governance and stewardship of data that is generated from digital health research. This paper contributes to an emerging research on equity issues in digital health and reducing health, institutional, and technological disparities. It also promotes the self-determination of racialized peoples through ethical data management. (shrink)

Key to precision medicine is the development of expert database projects that gather data, integrate them in the pre-existing database, and publish the product of their processing for others to make use of. Increasingly, it is required that data infrastructure managers and curators pursue and lead research projects on the data so as to learn about new ways data could be used or information that could be potentially generated from them. I call these efforts “ (...) class='Hi'>data curation-research” and use the case study of COSMIC, the Catalogue of Somatic Mutations in Cancer, to analyze the contextual factors shaping the science of data curation-research. I build on March’s organizational learning categories of exploitation and exploration to place these factors within a theory of organizational change and innovation, and contribute to a richer picture of the social drivers of cancer genomics. (shrink)

The paper problematises the reliability and ethics of using social media data, such as sourced from Twitter or Instagram, to carry out health-related research. As in many other domains, the opportunity to mine social media for information has been hailed as transformative for research on well-being and disease. Considerations around the fairness, responsibilities and accountabilities relating to using such data have often been set aside, on the understanding that as long as data were anonymised, no (...) real ethical or scientific issue would arise. We first counter this perception by emphasising that the use of social media data in health research can yield problematic and unethical results. We then provide a conceptualisation of methodological data fairness that can complement data management principles such as FAIR by enhancing the actionability of social media data for future research. We highlight the forms that methodological data fairness can take at different stages of the research process and identify practical steps through which researchers can ensure that their practices and outcomes are scientifically sound as well as fair to society at large. We conclude that making research data fair as well as FAIR is inextricably linked to concerns around the adequacy of data practices. The failure to act on those concerns raises serious ethical, methodological and epistemic issues with the knowledge and evidence that are being produced. (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)

BackgroundLarge-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the (...) decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal.MethodsWe conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data.ResultsThe decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants.ConclusionsOur findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures. (shrink)

Internet recruitment methods for research are rapidly evolving as technology and participant preferences do as well. This brings data security concerns, balanced with respect to persons for research participants. Internet recruitment research strategies are still important given the importance of creating private and accessible pathways for potentially marginalized populations or people experiencing stigmatized mental health conditions to participate in research. This manuscript describes the case of social media recruitment for a mental health and racism study (...) in Fall 2022 that was infiltrated by bots. We contextualize it in the context of data quality literature, with considerations for future directions including strategies for study design and management, and further research questions. (shrink)

This study used a partial least squares structural equation modelling (PLS-SEM) to estimate curriculum management's direct and indirect effects on university graduate programmes' viability. The study also examined the role of institutional effectiveness in mediating the nexus between the predictor and response variables. This is a correlational study with a factorial research design. The study's participants comprised 149 higher education administrators (23 Faculty Deans and 126 HODs) from two public universities in Nigeria. A structured questionnaire designed by the (...) researchers was used for data collection. The questionnaire was duly validated with an acceptable scale and item content validity indices. The dimensionality of the instrument was determined using exploratory factor analysis (EFA). Convergent validity was based on Average Variance Extracted (AVE), whereas discriminant validity was based on Fornell-Lacker criteria and the Hetero-Trait Mono-Trait (HTMT) ratio. Acceptable composite reliability estimates of internal consistency were reached for the three sub-scales. Following ethical practices, the questionnaire was physically administered to respondents and retrieved afterwards. Smart PLS (version 3.2.9) and SPSS (version 26.0) programs were used for all the statistical analyses. This study uncovered significant direct and indirect effects of curriculum management on the viability of graduate programmes. Institutional effectiveness significantly impacted graduate programmes’ viability while mediating the nexus between curriculum management and graduate programmes’ viability. Curriculum management and institutional effectiveness jointly explained a significant proportion of graduate programmes’ viability variance. The result of this study proved that graduate programmes’ viability depends, to a great extent, on how much curriculum is managed and how effective institutions are with their services. The result of this study can enable institutions seeking to run viable graduate programmes to re-evaluate their curriculum management practices and the effectiveness of their services. (shrink)

With the further acceleration of urbanization in China, the proportions of both urban residents’ energy consumption and energy-consuming terminal electricity are showing an increasing trend at the same time. In view of the dynamic and time-varying complex system characteristics of power system, it is of great significance to study the impact mechanism of urbanization residents’ electricity consumption on the realization of demand-side management and environmental protection. Based on the one-year follow-up survey data obtained from household meter reading, this (...) paper studies the impact mechanism of urban residents’ electricity consumption in different seasons and terminals by descriptive analysis and multiple linear regression model. The results show that, on the whole, electricity is a necessity for urban households and does not change significantly with changes in income. At the turn of summer and autumn and the turn of winter and spring, high-income families tend to use higher levels of energy in pursuit of comfort, while low- and middle-income families do not have luxury consumption. In different seasons, the influence mechanism of household electricity consumption at different terminals is different. (shrink)

The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) class='Hi'>data collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)

Note?takers in early modern Europe mixed a number of scribal practices. Not only did they write down extracts of texts, they also collected data from observation or from accounting. Practices such as commonplacing were part of sometimes communal, rather informal personal practices that laid the foundations for personal diaries. Other note?taking was prescriptive, fact?establishing technical data entry. Yet both the personal, sentimental and technical forms of note?taking were interrelated. It was during this period that merchants, administrators, scholars and (...) scientists sought methods to transform raw information such as notes into formalized knowledge for practical use. Notes had formed a part of larger writing and archival projects since the dawn of writing and literacy, but during the seventeenth and eighteenth centuries, figures such as Bacon, Boyle and Pepys not only mixed note?taking practices from both scholarly and mercantile traditions; they also thought about the very act of note?taking and how to transform it into a tool for the management of large?scale government, industry and research. Most of all, in the seventeenth century, scholars, merchants and naturalists began thinking in formal terms about how to use notes as part of larger information systems which they called collections, compilations and even archives. (shrink)

Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work (...) efficiency and accuracy of classification and gradation. At the same time, the differences, advantages, and disadvantages of K-NN, DT, and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises. (shrink)

Multiuser fair sharing of clusters is a classic problem in cluster construction. However, the cluster computing system for hybrid big data applications has the characteristics of heterogeneous requirements, which makes more and more cluster resource managers support fine-grained multidimensional learning resource management. In this context, it is oriented to multiusers of multidimensional learning resources. Shared clusters have become a new topic. A single consideration of a fair-shared cluster will result in a huge waste of resources in the context (...) of discrete and dynamic resource allocation. Fairness and efficiency of cluster resource sharing for multidimensional learning resources are equally important. This paper studies big data processing technology and representative systems and analyzes multidimensional analysis and performance optimization technology. This article discusses the importance of discrete multidimensional learning resource allocation optimization in dynamic scenarios. At the same time, in view of the fact that most of the resources of the big data application cluster system are supplied to large jobs that account for a small proportion of job submissions, while the small jobs that account for a large proportion only use the characteristics of a small part of the system’s resources, the expected residual multidimensionality of large-scale work is proposed. The server with the least learning resources is allocated first, and only fair strategies are considered for small assignments. The topic index is distributed and stored on the system to realize the parallel processing of search to improve the efficiency of search processing. The effectiveness of RDIBT is verified through experimental simulation. The results show that RDIBT has higher performance than LSII index technology in index creation speed and search response speed. In addition, RDIBT can also ensure the scalability of the index system. (shrink)

Aiming at a better understanding of the extent to which Africa-focused research has helped develop context-bound, context-specific, and context-free knowledge, the authors present the findings from a literature review of journal articles with an African context. A systematic search resulted in 271 articles with African data and 139 Africa-focused articles published in 63 top business journals and related disciplines from 2010 onwards. The sample included all journals belonging to the University of Texas Dallas and Financial Times research (...) rankings, as well as the main international business, and business and society outlets. An in-depth analysis of the 139 Africa-focused articles shows an important imbalance in terms of publication patterns, topics covered, theoretical groundings, types of contributions, approaches to the African contexts, and empirics. Building on this exhaustive literature review, the authors provide specific suggestions regarding potential data sources and empirical strategies in African contexts, propose avenues for future research, and introduce four recent studies included in the special issue. (shrink)

The relatively recent increase in empirical research conducted in business ethics has been accompanied by a growing literature which addresses its present shortcomings and continuing challenges. Particular attention has been focused on the difficulties of obtaining valid and reliable primary data. However, little or no attention has been paid to the use of secondary data. The aim of this paper is to stimulate the interest of business ethics researchers in using secondary data, either as a substitute (...) or complement for primary data, bearing in mind both the benefits and shortcomings of doing so. It is suggested that secondary data not only offer advantages in terms of cost and effort, as conventionally described in research methods books, but also that in certain cases their use may overcome some of the difficulties that particularly afflict business ethics researchers in the gathering of primary data. In order to help business ethicists respond to this call for greater consideration of the potential offered by secondary data, the wide variety of forms that such data may take is indicated and a number of themes regarding their use discussed. (shrink)

It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been (...) introduced in recent years. In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader ‘health and wealth’ agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS. (shrink)

This research presents the results of a survey regarding scientific misconduct and questionable research practices elicited from a sample of 1215 management researchers. We find that misconduct is not encountered often by reviewers nor editors. Yet, there is a strong prevalence of misrepresentations. When it comes to potential methodological improvements, those that are skeptical about the empirical body of work being published see merit in replication studies. Yet, a sizeable majority of editors and authors eschew open (...) class='Hi'>data policies, which points to hidden costs and limited incentives for data sharing in management research. (shrink)

Background The work of Research Ethics Boards (REBs), especially when involving genetics research and biobanks, has become more challenging with the growth of biotechnology and biomedical research. Some REBs have even rejected research projects where the use of a biobank with coded samples was an integral part of the study, the greatest fear being the lack of participant protection and uncontrolled use of biological samples or related genetic data. The risks of discrimination and stigmatization are (...) a recurrent issue. In light of the increasing interest in biomedical research and the resulting benefits to the health of participants, it is imperative that practical solutions be found to the problems associated with the management of biobanks: namely, protecting the integrity of the research participants, as well as guaranteeing the security and confidentiality of the participant's information. Methods We aimed to devise a practical and efficient model for the management of biobanks in biomedical research where a medical archivist plays the pivotal role as a data-protection officer. The model had to reduce the burden placed on REBs responsible for the evaluation of genetics projects and, at the same time, maximize the protection of research participants. Results The proposed model includes the following: 1) a means of protecting the information in biobanks, 2) offers ways to provide follow-up information requested about the participants, 3) protects the participant's confidentiality and 4) adequately deals with the ethical issues at stake in biobanking. Conclusion Until a governmental governance body is established in Quebec to guarantee the protection of research participants and establish harmonized guidelines for the management of biobanks in medical research, it is definitely up to REBs to find solutions that the present lack of guidelines poses. The model presented in this article offers a practical solution on a day-to-day basis for REBs, as well as researchers by promoting an archivist to a pivotal role in the process. It assures protection of all participants who altruistically donate their samples to generate and improve knowledge for better diagnosis and medical treatment. (shrink)

The proliferation of digital data and internet-based research technologies is transforming the research landscape, and researchers and research ethics communities are struggling to respond to the ethical issues being raised. This paper discusses the findings from a collaborative project that explored emerging ethical issues associated with the expanding use of digital data for research. The project involved consulting with researchers from a broad range of disciplinary fields. These discussions identified five key sets of issues (...) and informed the development of guidelines orientated to meet the needs of researchers and ethics committee members. We argue that establishing common approaches to assessing ethical risks of research involving digital data will promote consistency in the ethical standards for research, enable the smooth functioning of ethics committees, and sustain public confidence in research. We conclude with recommendations for the development of educational resources for ethics committees, data management guidelines and further public education. (shrink)

In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data (...) quality in scientific research, whereby the quality of a dataset is dependent on the context of use of the dataset as much as the dataset itself. I exemplify the approach by discussing current critiques and debates of scientific quality, thus showcasing how data quality can be approached contextually. (shrink)

Using video to facilitate data collection has become increasingly common in health research. Using video in research, however, does raise additional ethical concerns. In this paper we utilize family therapy data to provide empirical evidence of how recording equipment is treated. We show that families made a distinction between what was observed through the video by the reflecting team and what was being recorded onto videotape. We show that all parties actively negotiated what should and should (...) not go ‘on the record’, with particular attention to sensitive topics and the responsibility of the therapist. Our findings have important implications for both clinical professionals and researchers using video data. We maintain that informed consent should be an ongoing process and with this in mind we present some arguments pertaining to the current debates in this field of health-care practice. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a (...) tool for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a (...) tool for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a (...) tool for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)