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 “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)

Those who wish to deny some instance of environmental injustice often attempt to place inappropriate evidentiary burdens on scientists who show disproportionate pollution effects on vulnerable populations. One such evidentiary standard is the epidemiological-evidence rule (EER). According to EER, legitimate causal inferences about pollution-related harm (and actions to reduce probable environmental injustice) require human-epidemiological data, not merely good animal or laboratory data. This article summarizes the grounds for supporting EER, evaluates central scientific problems with EER, assesses key ethical (...) difficulties with EER, then concludes that EER ought not be used either to deny otherwise-probable environmental injustice or to delay possible action to correct well-documented pollution-related harms. (shrink)

Data Transfer Service (DTS) is an open-source project that is developing a document-centric message model for describing a bulk data transfer activity, with an accompanying set of loosely coupled and platform-independent components for brokering the transfer of data between a wide range of (potentially incompatible) storage resources as scheduled, fault-tolerant batch jobs. The architecture scales from small embedded deployments on a single computer to large distributed deployments through an expandable ‘worker-node pool’ controlled through message-orientated middleware. Data (...) access and transfer efficiency are maximized through the strategic placement of worker nodes at or between particular data sources/sinks. The design is inherently asynchronous, and, when third-party transfer is not available, it side-steps the bandwidth, concurrency and scalability limitations associated with buffering bytes directly through intermediary client applications. It aims to address geographical–topological deployment concerns by allowing service hosting to be either centralized (as part of a shared service) or confined to a single institution or domain. Established design patterns and open-source components are coupled with a proposal for a document-centric and open-standards-based messaging protocol. As part of the development of the message protocol, a bulk data copy activity document is proposed for the first time. (shrink)

This article analyzes the experiences of ecologists who used data they did not collect themselves. Specifically, the author examines the processes by which ecologists understand and assess the quality of the data they reuse, and investigates the role that standard methods of data collection play in these processes. Standardization is one means by which scientific knowledge is transported from local to public spheres. While standards can be helpful, the results show that knowledge of the local context (...) is critical to ecologists' reuse of data. Yet, this information is often left behind as data move from the private to the public world. The knowledge that ecologists acquire through fieldwork enables them to recover the local details that are so critical to their comprehension of data collected by others. Social processes also play a role in ecologists' efforts to judge the quality of data they reuse. (shrink)

Social media commentary, satellite imagery and GPS data are a part of ‘alternative data’, that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management and algorithmic trading industries. Drawing on interviews with people working in investment management and (...) algorithmic trading firms utilizing alternative data, as well as firms providing and sourcing such data, we emphasize social media-based sentiment analytics as one manifestation of how alternative data are deployed for stock price prediction purposes. This demonstrates both how sentiment analytics are developed and subsequently utilized by investment management firms. We argue that ‘alternative data’ are an open-ended placeholder for every data source potentially relevant for investment management purposes and harnessing these disparate data sources requires certain standardization efforts by different market participants. Besides showing how market participants understand and use alternative data, we demonstrate that alternative data often undergo processes of prospecting and assetization. We further contend that the widespread embracement of alternative data in investment management and trading encourages a financialization process at the data level which raises new governance issues. (shrink)

The aim of this work is to identify and analyze a set of challenges that are likely to be encountered when one embarks on fieldwork in linguistic communities that feature small, young, and/or non-standard languages with a goal to elicit big sets of rich data. For each challenge, we (i) explain its nature and implications, (ii) offer one or more examples of how it is manifested in actual linguistic communities, and (iii) where possible, offer recommendations for addressing it effectively. (...) Our list of challenges involves static characteristics (e.g., absence of orthographic conventions and how it affects data collection), dynamic processes (e.g., speed of language change in small languages and how it affects longitudinal collection of big amounts of data), and interactive relations between non-dynamic features that are nevertheless subject to potentially rapid change (e.g., absence of standardized assessment tools or estimates for psycholinguistic variables). The identified challenges represent the domains of data collection and handling, participant recruitment, and experimental design. Among other issues, we discuss population limits and degree of power, inter- and intraspeaker variation, absence of metalanguage and its implications for the process of eliciting acceptability judgments, and challenges that arise from absence of local funding, conflicting regulations in relation to privacy issues, and exporting large samples of data across countries. Finally, the ten experimental challenges presented cover a broad typological spectrum, encompassing both spoken and sign, extant and nearly extinct languages. (shrink)

Benchmarks against which healthcare ethics consultation (HCEC) services can assess their performance are needed. As first-generation benchmarks continue to be developed, it is the obligation of the field to continually evaluate how these measures reflect the performance of any single HCEC service. This will be possible only with widespread reporting of standardized data points. In their article in this issue of The Journal of Clinical Ethics, Glover and colleagues provide a valuable preliminary approach for assessing appropriate consult volumes for (...) a HCEC service. The limitations of their study read as a call to action for the field of clinical ethics to expand and standardize data reporting so that more robust metrics can be developed. In response to this call by Glover and colleagues, the Cleveland Clinic HCEC service provides consult data from 2015 through 2019 for one of its medical centers, and offers an additional volumebased metric, consult-to-ICU-to-bed ratio (CiBR), that may add nuance to any normative assessment of HCEC service consult volume. Given that volume-based metrics are the native language of the clinical environment, efforts to improve such metrics in the field through transparency and standardization are warranted. However, the expositive power of volume-based metrics is limited; additional domains related to quality and outcomes are needed. (shrink)

In Roper v. Simmons (2005) the United States Supreme Court announced a paradigm shift in jurisprudence. Drawing specifically on mounting scientific evidence that adolescents are qualitatively different from adults in their decision-making capacities, the Supreme Court recognized that adolescents are not adults in all but age. The Court concluded that the overwhelming weight of the psychological and neurophysiological data regarding brain maturation supports the conclusion that adolescents are qualitatively different types of agents than adult persons. The Supreme Court further (...) solidified its position regarding adolescents as less than fully mature and responsible decisionmakers in Graham v. Florida (2010) and Miller v. Alabama (2012). In each case, the Court concluded that the scientific evidence does not support the conclusion that children under 18 years of age possess adult capacities for personal agency, rationality, and mature choice. This study explores the implications of the Supreme Court decisions in Roper v. Simmons, Graham v. Florida, and Miller v. Alabama for the “mature minor” standard for medical decision making. It argues that the Supreme Court’s holdings in Roper, Graham, and Miller require no less than a radical reassessment of how healthcare institutions, courts of law, and public policy are obliged to regard minors as medical decisionmakers. The “mature minor” standard for medical decision making must be abandoned. (shrink)

We construct novel measures to assess (i) the extent to which European Union member states are using common standards in recognizing asylum seekers and (ii) the extent to which the responsibilities for asylum applications, acceptances and refugee populations are equally shared among the member states, taking into account population size, gross domestic product (GDP) and GDP expressed in purchasing power parity (GDP-PPP). We track the progression of these measures since the implementation of the Treaty of Amsterdam (1999). These measures (...) display divergent trends and we try to provide an interpretation of the dynamics that are constitutive of these trends. (shrink)

Definition of the problem In medicine, as well as in other disciplines, computer science expertise is becoming increasingly important. This requires a culture of interdisciplinary assessment, for which medical ethics committees are not well prepared. The use of big data and artificial intelligence (AI) methods (whether developed in-house or in the form of “tools”) pose further challenges for research ethics reviews. Arguments This paper describes the problems and suggests solving them through procedural changes. Conclusion An assessment that is interdisciplinary (...) from the outset appears to be more suitable than having two commissions with different expertise. However, this would require that the composition of medical ethics committees be altered. In addition, the article recommends initial measures to be taken during research ethics reviews of big data and AI projects in order to consolidate the review process and ensure standardization of the criteria. (shrink)

Surveillance in public health is the means by which people who are responsible for preventing or controlling threats to health get the timely, ongoing, and reliable information they need about the occurrence, antecedents, time course, geographic spread, consequences, and nature of these threats among the populations they serve. “Policy surveillance” is the ongoing, systematic collection, analysis, and dissemination of information about laws and other policies of health importance.

First-person data have been both condemned and hailed because of their alleged privacy. Critics argue that science must be based on public evidence: since first-person data are private, they should be banned from science. Apologists reply that first-person data are necessary for understanding the mind: since first-person data are private, scientists must be allowed to use private evidence. I argue that both views rest on a false premise. In psychology and neuroscience, the subjects issuing first-person reports (...) and other sources of first-person data play the epistemic role of a (self-) measuring instrument. Data from measuring instruments are public and can be validated by public methods. Therefore, first-person data are as public as other scientific data: their use in science is legitimate, in accordance with standard scientific methodology. (shrink)

Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to (...) work on and likely will help to restore plausibility to social sciences research. Therefore, I feel it likely that the triplet of open data, open review and open dialogue will gradually emerge to become policy requirements regardless of the research funding source. (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)

This work tests two conflicting views about double standards: whether they reflect evolved sex differences in behavior or a manipulative morality serving male interests. Two questionnaires on jealous reactions to mild (flirting) and serious (cheating) sexual transgressions were randomly assigned to 172 young women and men. One questionnaire assessed standards for appropriate behavior and perceptions of how young women and men usually react. The second asked people to report how they had reacted or, if naive, how they would (...) react. The questions concerned anger at and blame of partner and rival and the self-oriented responses of loss of self-esteem, feelings of hurt, and fear of losing the partner. As predicted by the idea of manipulative morality, both sexes advanced sets of double standards that serve the interests of their own sex at the expense of the opposite sex. Much of the data contradict the idea of a match between double standards and evolved sex differences. First, subjects who set self-serving double standards did not perceive gender differences in jealous reactions. Second, there were few gender differences in judgments regarding jealous responses. Third, in contrast with the familiar double standard, women were more aggressively reactive to a flirting rival than men. Fourth, self-reports of the strength of aggressive jealous reactions suggest that women’s behavior is stronger than the prescriptions for it. These data suggest that double standards represent a communication strategy which assists men’s control of women. The data on jealous reactions were interpreted in terms of the degree of threat to fitness posed by infidelity in different situations. (shrink)

The practice of research is full of ethical challenges, many of which might be addressed through the teaching of responsible conduct of research . Although such training is increasingly required, there is no clear consensus about either the goals or content of an RCR curriculum. The present study was designed to assess community standards in three domains of research practice: authorship, collaboration, and data management. A survey, developed through advice from content matter experts, focus groups, and interviews, was (...) distributed in November 2010 to U.S. faculty from 50 graduate programs for each of four different disciplines: microbiology, neuroscience, nursing, and psychology. The survey addressed practices and perceived standards, as well as perceptions about teaching and learning. Over 1,300 responses yielded statistically significant differences in responses to nearly all questions. However the magnitude of these differences was typically small, leaving little reason to argue for community consensus on standards. For nearly all questions asked, the clear finding was that there was nothing approaching consensus. These results may be useful not so much to teach what the standards are, but to increase student awareness of the diversity of those standards in reported practice. (shrink)

This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.

Teaching of responsible conduct of research is largely predicated on the assumption that there are accepted standards of conduct that can be taught. However there is little evidence of consensus in the scientific community about such standards, at least for the practices of authorship, collaboration, and data management. To assess whether such differences in standards are based on disciplinary differences, a survey, described previously, addressing standards, practices, and perceptions about teaching and learning was distributed in (...) November 2010 to US faculty from 50 graduate programs for the biomedical disciplines of microbiology, neuroscience, nursing, and psychology. Despite evidence of statistically significant differences across the four disciplines, actual differences were quite small. Stricter measures of effect size indicated practically significant disciplinary differences for fewer than 10 % of the questions. This suggests that the variation in individual standards of practice within each discipline is at least as great as variation due to differences among disciplines. Therefore, the need for discipline-specific training may not be as important as sometimes thought. (shrink)

This thesis provides an introduction to the physics of the Standard Model and beyond, and to the methods used to analyse Large Hadron Collider (LHC) data. The 'hierarchy problem', astrophysical data and experiments on neutrinos indicate that new physics can be expected at the now accessible TeV scale. This work investigates extensions of the Standard Model with gravitons and gravitinos (in the context of supergravity). The production of these particles in association with jets is studied as one of (...) the most promising avenues for researching new physics at the LHC. Advanced simulation techniques and tools, such as algorithms allowing the computation of Feynman graphs and helicity amplitudes are first developed and then employed. (shrink)

SummaryNormative data are reported for intelligence, height and head circumference for a sample of 1553 6- to 15-year-olds in Saudi Arabia, and for the correlations between these variables. Intelligence was tested with the Standard Progressive Matrices, on which the Saudi sample obtained a British IQ of 76.2. There were no significant differences in means between boys and girls and differences in variability were inconsistent. The heights of the Saudi sample were generally lower than those of the American norms. The (...) differences in head circumferences between the Saudi children and the American norms were inconsistent. Correlations between IQ and height were weaker than those found in other studies but correlations between IQ and head circumference were positive. (shrink)

We present in this article a compression system that uses STEP compliant standards for the compression and design review visualization of large CAD data sets. Our approach is orthogonal to the traditional techniques applied in the field, as we complement previous works by introducing semantic criteria along with algorithms for the categorization, simplification and user-oriented adaptation of the engineering components described by domain-specific standards. As an example, we have implemented two test cases in two specific domains – (...) ISO-STEP 13013-AP227 in the case of industrial Plant Design, and CIS/2 in the case of Steel Detailing Design (Structures Design). (shrink)

The starting point of this work is the gap between two distinct traditions in information engineering: knowledge representation and data - driven modelling. The first tradition emphasizes logic as a tool for representing beliefs held by an agent. The second tradition claims that the main source of knowledge is made of observed data, and generally does not use logic as a modelling tool. However, the emergence of fuzzy logic has blurred the boundaries between these two traditions by putting (...) forward fuzzy rules as a Janus-faced tool that may represent knowledge, as well as approximate non-linear functions representing data. This paper lays bare logical foundations of data - driven reasoning whereby a set of formulas is understood as a set of observed facts rather than a set of beliefs. Several representation frameworks are considered from this point of view: classical logic, possibility theory, belief functions, epistemic logic, fuzzy rule-based systems. Mamdani's fuzzy rules are recovered as belonging to the data - driven view. In possibility theory a third set-function, different from possibility and necessity plays a key role in the data - driven view, and corresponds to a particular modality in epistemic logic. A bi-modal logic system is presented which handles both beliefs and observations, and for which a completeness theorem is given. Lastly, our results may shed new light in deontic logic and allow for a distinction between explicit and implicit permission that standard deontic modal logics do not often emphasize. (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)

Data exclusivity is a temporary exclusive user right on the clinical data that need to be submitted to the regulatory authorities to prove that a new drug is safe and effective. For the pharmaceutical industry, data exclusivity is an important addition to the patent system, as data exclusivity will de facto delay the market entry of generic drugs until after the exclusive user rights on the clinical data have expired. In order to assess the normative (...) legitimacy of the industry’s demand to include minimum standards for data exclusivity in international agreements, this chapter evaluates the three justifications that have frequently been advanced, depicting data exclusivity as an essential policy tool to promote innovation, a mechanism to prevent the generic industry from ‘free-riding,’ and a legal instrument to protect the industry’s property rights in clinical data. (shrink)

Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value (...) of missing data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms. (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 literacy – the ability to analyze, interpret, evaluate, and use data and data visualizations – has become increasingly important for understanding and communicating information in the discipline of history. In the United States, curricular standards and standardized assessments already reflect this importance, but educators lack a clear picture of how students use data visualizations when reasoning about the past. How do students use data visualizations when reasoning about a historical question? To what degree (...) does using data visualizations enhance students’ historical reasoning? What challenges do students face when attempting to use data visualizations? This study addresses these questions, investigating how fifth-grade, eighth-grade, and high school students use data visualizations from typical school textbooks. Twenty-seven students were interviewed, surveyed, and asked to think aloud about a historical question while using a textbook entry that included a data visualization. Results from qualitative and quantitative analyses highlight the potential for data visualizations to enhance historical reasoning. However, results also indicate that students are unlikely to read data visualizations on their own, underscoring the importance of providing targeted data literacy instruction. (shrink)

Abstract When new methods of generating information about individuals leave the confined space of research application the possibility of morally dubious application arises. The current propagation of neuroscientific diagnostics leads to new possibilities of misuse and accordingly new needs for the protection of individual privacy emerge. While most current privacy discussion focuses on sensationalist applications which aim/claim to gather information about psychological traits or even the content of thoughts, the more sober but much more realistic endeavour to gather health (...) class='Hi'>data from research or medical imaging studies is widely neglected. I will try to answer the question if and in how far data from neuroscientific imaging technologies require special protection. Two developments form the background of the ethical discussion: the increased diagnostic power of neuroimaging techniques and the wider distribution of this technology beyond specialized medical offices and clinics. The first development is likely to broaden the scope of data, which are considered relevant for health care and related decisions. The latter is likely to widen the scope of persons who might have access to diagnostic results without at the time taking the role of a doctor towards the person diagnosed. I will argue that neuroimaging data are currently primarily medical data and that the associated standards of consent and confidentiality are worth protecting. Even nonmedical applications of neuroimaging technology inherit too much of the diagnostic power for which they were originally invented, for it to be advisable to drop the accompanying consent and confidentiality requirements. (shrink)

Clinicians sometimes disagree about how much to honor surrogates’ deeply held cultural values or traditions when they differ from those of the host country. Such a controversy arose when parents requested a cultural accommodation to let their infant die by withdrawing life saving care. While both the parents and clinicians claimed to be using the Best Interests Standard to decide what to do, they were at an impasse. This standard is analyzed into three necessary and jointly sufficient conditions and used (...) to resolve the question of how much to accommodate cultural preferences and how to treat this infant. The extreme versions of absolutism and relativism are rejected. Properly understood, the Best Interests Standard can serve as a powerful tool in settling disputes about how to make good decisions for those who cannot decide for themselves. (shrink)

In light of arguments that citizen science has the potential to make environmental knowledge and policy more robust and democratic, this article inquires into the factors that shape the ability of citizen science to actually influence scientists and decision makers. Using the case of community-based air toxics monitoring with ‘‘buckets,’’ it argues that citizen science’s effectiveness is significantly influenced by standards and standardized practices. It demonstrates that, on one hand, standards serve a boundary-bridging function that affords bucket monitoring (...) data a crucial measure of legitimacy among experts. On the other hand, standards simultaneously serve a boundary-policing function, allowing experts to dismiss bucket data as irrelevant to the central project of air quality assessment. The article thus calls attention to standard setting as an important site of intervention for citizen science-based efforts to democratize science and policy. (shrink)

Big data represents a significant challenge for the social sciences. From a philosophy-of-science perspective, it is important to reflect on related theories and processes for developing them. In this paper, we start by examining different views on the role of theories in big data-related social research. Then, we try to show how big data is related to standards for evaluating theories. We also outline how big data affects theory- and data-based research approaches and the (...) process of theory building. Discussions include a summary of lines of reasoning, limitations, and a proposal for future developmental steps. (shrink)

The expansion of research on deep brain stimulation (DBS) and adaptive DBS (aDBS) raises important neuroethics and policy questions related to data sharing. However, there has been little empirical research on the perspectives of experts developing these technologies. We conducted semi-structured, open-ended interviews with aDBS researchers regarding their data sharing practices and their perspectives on ethical and policy issues related to sharing. Researchers expressed support for and a commitment to sharing, with most saying that they were either sharing (...) their data or would share in the future and that doing so was important for advancing the field. However, those who are sharing reported a variety of sharing partners, suggesting heterogeneity in sharing practices and lack of the broad sharing that would reflect principles of open science. Researchers described several concerns and barriers related to sharing, including privacy and confidentiality, the usability of shared data by others, ownership and control of data (including potential commercialization), and limited resources for sharing. They also suggested potential solutions to these challenges, including additional safeguards to address privacy issues, standardization and transparency in analysis to address issues of data usability, professional norms and heightened cooperation to address issues of ownership and control, and streamlining of data transmission to address resource limitations. Researchers also offered a range of views on the sensitivity of neural activity data (NAD) and data related to mental health in the context of sharing. These findings are an important input to deliberations by researchers, policymakers, neuroethicists, and other stakeholders as they navigate ethics and policy questions related to aDBS research. (shrink)

Universities are specialized units aimed to deliver quality education and shaping future leadership to provide competent professionals to the industry. The establishment of ORIC in universities and significant increase in academia-industry linkage activities is strategic move towards achievement of the mentioned objectives. Bridging up the gap between academia and industry by adopting such strategies defines the successful role of HEIs. In view of increasing number of universities and continuous outflow of graduates it seems imperative to analyze and capitalize their potential (...) towards the growth of economy. However, the unemployment ratio and limited growth in SME sector reflect the insignificant absorption of graduates in corporate sector. The study aims to determine the factors that serve as barriers in achieving goals of HEIs by understanding the problems faced by university students in general and business graduates in particular on the basis of data gathered from 100 students from different universities present in Karachi. It shall also assists the policy makers in devising policy as per market demands, level of quality attained by universities, their involvement with corporate sector and in turn need of the industry to keep both parties at par in the fluctuating and contemporary era. (shrink)

BackgroundWhenever South African research institutions share human biological material and associated data for health research or clinical trials they are legally compelled to have a material transfer agreement in place that uses as framework the standard MTA newly gazetted by the South African Minister of Health.Main bodyThe article offers a legal analysis of the SA MTA and focuses on its substantive fit with the broader legal environment in South Africa, and the clarity and practicality of its terms. The following (...) problematic aspects of the SA MTA are highlighted: Where only data and no human biological material are transferred, the SA MTA does not apply, leaving a lacuna; Health Research Ethics Committees are required to be parties to a MTA despite it being outside their legal mandate and undermining their oversight function; the SA MTA’s consent provisions are not aligned with extant law; and, similarly, its provision on donor ownership is misaligned with extant law; its creation of fictitious performance can only cause frustration on the part of an injured party; its benefit-sharing provision is vague and will have little practical effect; its dispute-resolution provisions fail to adequately protect South African research institutions and research participants; it fails to provide substantive guidance regarding intellectual property as its provisions relating to intellectual property may cause practical problems; and, finally, its data privacy provision is insufficiently specific, is overbroad, and fails to provide terms that in general would facilitate the international sharing of human biological material and associated data in terms of existing privacy law.ConclusionsWhile some of the problematic aspects of the SA MTA are intricate and require consultative processes with stakeholders and others, to develop comprehensive solutions, most of the problematic aspects can be resolved immediately through amendments by the South African Minister of Health. The formulation of such amendments is proposed and, where possible, interim measures are suggested that may ameliorate the problems presented by the SA MTA. (shrink)

In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that (...) can impede informed consent with respect to Big data use. First, we discuss the transparency (or explanation) problem. Second, we discuss the re-repurposed data problem. Third, we discuss the meaningful alternatives problem. In the final section of the paper, we suggest some solutions to these problems. In particular, we propose that the use of personal data for commercial and administrative objectives could be subject to a ‘soft governance’ ethical regulation, akin to the way that all projects involving human participants (e.g., social science projects, human medical data and tissue use) are regulated in Australia through the Human Research Ethics Committees (HRECs). We also consider alternatives to the standard consent forms, and privacy policies, that could make use of some of the latest research focussed on the usability of pictorial legal contracts. (shrink)

The executive board of the Academy for Ethics in Medicine and two AEM working groups formulated standards and recommendations for clinical ethics consultation in 2010, 2011, and 2013. These guidelines comply with the international standards like those set by the American Society for Bioethics and Humanities. There is no empirical data available yet that could indicate whether these standards and recommendations have been implemented in German hospitals. This desideratum is addressed in the present study. We contacted (...) 1.858 German hospitals between September 2013 and January 2014. A follow-up survey was conducted between October 2014 and January 2015. The data of the initial survey and the follow-up survey were merged and evaluated. The statements of the participants were compared with the standards and recommendations. The standards of the AEM concerning the tasks of clinical ethics consultation are employed by a majority of participants of the study. Almost all of these participants document their consultation activities by means of protocols or entries in the patient file. There are deviations from the recommendations of the AEM working groups regarding the drafting of statutes, activity reports, and financial support. The activities of clinical ethics consultation predominantly comply with the standards of the AEM and recommendations for the documentation. The recommendations for evaluation should be improved in practice. This applies particularly for activity reports in order to evaluate the activities. Internal evaluation could take place accordingly. (shrink)

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data (...) in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities. (shrink)

This paper draws attention to an increasingly common method of using computer simulations to establish evidential standards in physics. By simulating an actual detection procedure on a computer, physicists produce patterns of data (‘signatures’) that are expected to be observed if a sought-after phenomenon is present. Claims to detect the phenomenon are evaluated by comparing such simulated signatures with actual data. Here I provide a justification for this practice by showing how computer simulations establish the reliability of (...) detection procedures. I argue that this use of computer simulation undermines two fundamental tenets of the Bogen–Woodward account of evidential reasoning. Contrary to Bogen and Woodward’s view, computer-simulated signatures rely on ‘downward’ inferences from phenomena to data. Furthermore, these simulations establish the reliability of experimental setups without physically interacting with the apparatus. I illustrate my claims with a study of the recent detection of the superfluid-to-Mott-insulator phase transition in ultracold atomic gases. (shrink)

n the analytic tradition, the appeal to intuition has been a common philosophical practice that supposedly provides us with epistemic standards. The authoress argues that the high epistemological standards of traditional analytic philosophy cannot be pursued by this method. Perhaps within a naturalistic, reliable frame intuitions can be evoked more coherently. Philosophers can use intuition as scientists do, in hypothesis- construction or data- collection. This is an ironic conclusion: Traditional analytic epistemologists rely on the appeal to intuition, (...) but cannot justify it. Naturalists, on the other hand, are not those who need such a method; yet they can better accommodate it within their view. (shrink)

As we move our social institutions from paper and ink based operations to the electronic medium, we invisibly create a type of surveillance society, a panopticon society. It is not the traditional surveillance society in which government officials follow citizens around because they are concerned about threats to the political order. Instead it is piecemeal surveillance by public and private organizations. Piecemeal though it is, It creates the potential for the old kind of surveillance on an even grander scale. The (...) panopticon is the prison environment described by Foucault in which prison cells are arranged in a large circle with the side facing the inside of the circle open to view. The guard tower is placed in the middle of the circle so that guards can see everything that goes on in every cell. When we contemplate all the electronic data that is now gathered about each of us as we move through our everyday lives --- intelligent highway systems, consumer transactions, traffic patterns on the internet, medical records, financial records, and so on --- there seems little doubt that we are moving into a panopticon. The social issues that arise from this are too numerous to detail here, but data retention is an important part of it. In the paper-and-ink world, documents are filed, files are boxed, boxes are put away or thrown away. The capacity for data retrieval and manipulation is, thereby, limited by the sheer difficulty and cost of storing, finding, searching, and manipulating large numbers of paper files. This inconvenience functions as a mechanism whereby the system forgets past information, not unlike the way we ourselves forget. However, the story is very different in the digital world; digital information is easy to store, easy to search and manipulate, and inexpensive to keep over extensive periods of time. Digitalized information systems tend, therefore, to collect extensive ancillary information and to retain this information indefinitely. Such lack of forgetfulness is likely to hamper the ability of individuals to shed their past, and start over with a clean slate. Concerns about data retention were expressed in the early literature on the social impact of computing, but for the most part the issue has dropped from sight. Rarely, has the social good of discarding accumulated personal data been addressed. In this paper, we want to make the case by examining diverse cases in which retention of information by either business or governmental institutions hinders the ability of individuals to start over or to act autonomously. We hope our argument for the good of forgetfulness will challenge the standard framework in which such issues have traditionally been debated. The privacy debate exemplifies the traditional framework insofar as it has been characterized as involving an inherent tension between, on the one hand, the needs of organizations and institutions for more accurate and efficient information systems so as to further their goals and, on the other hand, the desire of individuals to have information about them kept private. Regan argues against this framing of the privacy issue in favor of one that recognizes the social importance of personal privacy. We will examine the non-forgetfulness of information systems as a problem threatening not just individual interests but social good as well. Cryptography is often cited as the technology that will give us privacy and mediate against surveillance. One of the uses of cryptography, encryption, will allow us, some hope, to create confidentiality and relationships of trust that will facilitate many of the social arrangements we now have and perhaps make them even more secure than they are now. Electronic cash, for example, could be created in such a form that it would have the anonymity associated now with hard cash Others are less optimistic of the potential for cryptography to re-create relationships of trust in the new medium. One important point that already seems clear is that even if encryption technology will protect the confidentiality and integrity of electronic transactions and data, it will NOT stop the observation of traffic patterns on networks. This seems an important distinction to put on the table. Our patterns of communication will continue to be available, no matter what is encrypted, and an amazing amount of information can be gleaned from this data. In a sense, it means content integrity but no anonymity. This will indubitably impact how we interact and with whom we interact. (shrink)

The re-use of publicly available (personal) data for originally unanticipated purposes has become common practice. Without such secondary uses, the development of many AI systems like large language models (LLMs) and ChatGPT would not even have been possible. This chapter addresses the ethical implications of such secondary processing, with a particular focus on data protection and privacy issues. Legal and ethical evaluations of secondary processing of publicly available personal data diverge considerably both among scholars and the general (...) public. While some of these uses are met with opposition and criticism, others are quite unanimously viewed as unproblematic. Often, proponents and opponents of such practices invoke the same ethical and legal standards for their opposite conclusions. This state of affairs shows that other considerations besides the public availability of data must play a role. It calls for a theoretical clarification of the additional criteria that should guide decisions about the (legally informed) ethical acceptability of re-processing practices. In order to make a contribution towards this goal, the present chapter maps the ongoing debate and systematises the existing contributions around three lines of argument: a consent-centred position, an approach that focuses on the distinction between data and information, and finally a line of argument that focuses on the contextual norms that govern the flows of information. The chapter further relates these arguments to three underlying conceptions of privacy and data protection: rights-based, structural and contextual, and discusses the advantages and disadvantages of each position in the light of concrete examples. It concludes by arguing for a mixed approach that combines core elements of the structural and contextual approaches. The chapter aims to contribute to existing research in the fields of data, AI and research ethics, and to reconnect the debate with ethical and legal scholarship on privacy and data protection. In doing so, it aims to make a theoretical contribution towards refining existing conceptions of privacy and data protection in order to make them more fit to ‘drive our digital world’ as far as the use of publicly available data is concerned. (shrink)

Statistical tests of the primality of some numbers look similar to statistical tests of many nonmathematical, clearly empirical propositions. Yet interpretations of probability prima facie appear to preclude the possibility of statistical tests of mathematical propositions. For example, it is hard to understand how the statement that n is prime could have a frequentist probability other than 0 or 1. On the other hand, subjectivist approaches appear to be saddled with ‘coherence’ constraints on rational probabilities that require rational agents to (...) assign extremal probabilities to logical and mathematical propositions. In the light of these problems, many philosophers have come to think that there must be some way to generalize a Bayesian statistical account. In this article I propose that a classical frequentist approach should be reconsidered. I conclude that we can give a conditional justification of statistical testing of at least some mathematical hypotheses: if statistical tests provide us with reasons to believe or bet on empirical hypotheses in the standard situations, then they also provide us with reasons to believe or bet on mathematical hypotheses in the structurally similar mathematical cases. (shrink)

Law wrangles with setting and applying standards for the practice of medicine in many different arenas. One of the most prominent is medical malpractice litigation in which the trial process examines a physician's performance and measures it against the standard of care. The profession's prevailing custom, with some substantial tolerance for “respectable minority” views, has been the gold standard for scrutinizing physician practice and treatment decisions in the malpractice context. Using the profession's custom as the measure against which a (...) physician's performance is judged defers to the expertise of medicine. Deference to the medical profession is attractive as a tool for reining in law. Reliance on customary practice is criticized, however, for driving physicians to the relative safety of the middle of the herd. Creating such a strong incentive for compliance with customary practice can dampen medical innovation and the diffusion of new clinical knowledge. The safety of the herd can also deprive individual patients of the best care in their particular circumstances.Several current trends are strengthening claims that professional practice patterns are an inappropriate tool for distinguishing between high‐quality and substandard care. In particular, advocacy for evidence‐based medicine aggressively asserts that the traditional way of making medical treatment decisions is largely untethered from scientific method or data, rendering professional judgment, even in the aggregate, suspect. (shrink)