Ethical Use Of Data Research Articles

Importance of Community Engagement in Data Decision Making.

Importance of Community Engagement in Data Decision Making.

CONTEXTUALIZAÇÃO DA LEI GERAL DE PROTEÇÃO DE DADOS PARA OS PEQUENOS NEGÓCIOS

The General Data Protection Law (LGPD) aims to bring greater transparency and responsibility to the use of personal data of individuals and legal entities throughout the national territory. With the advent of the Law, the processing of data that was carried out in an uncontrolled way is now regulated and with specific purposes, uniting Brazilian legislation with the global concept of data privacy. Within the scope of the business activity of micro and small companies (MSEs), compliance with the Law can be quite challenging, considering that the planned measures can generate such high costs that these companies need to paralyze their activities. Therefore, the objective of this study is to report on the challenges for the application of the Law in Brazil, with a focus on flexibility for small companies, a sector that has the greatest difficulty in adapting to the norms. And emphasize how the implementation of the Law within organizations can bring opportunities for growth, since the ethical use of data linked to a culture of good practices can increase trust between companies and customers.

Four questions to guide decision-making for data sharing and integration.

This paper presents a Four Question Framework to guide data integration partners in building a strong governance and legal foundation to support ethical data use. While this framework was developed based on work in the United States that routinely integrates public data, it is meant to be a simple, digestible tool that can be adapted to any context. The framework was developed through a series of public deliberation workgroups and 15 years of field experience working with a diversity of data integration efforts across the United States. The Four Questions-Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)?-should be considered within an established data governance framework and alongside core partners to determine whether and how to move forward when building an Integrated Data System (IDS) and also at each stage of a specific data project. We discuss these questions in depth, with a particular focus on the role of governance in establishing legal and ethical data use. In addition, we provide example data governance structures from two IDS sites and hypothetical scenarios that illustrate key considerations for the Four Question Framework. A robust governance process is essential for determining whether data sharing and integration is legal, ethical, and a good idea within the local context. This process is iterative and as relational as it is technical, which means authentic collaboration across partners should be prioritized at each stage of a data use project. The Four Questions serve as a guide for determining whether to undertake data sharing and integration and should be regularly revisited throughout the life of a project. Strong data governance has five qualities: it is purpose-, value-, and principle-driven; strategically located; collaborative; iterative; and transparent.Through a series of public deliberation workgroups and 15 years of field experience, we developed a Four Question Framework to determine whether and how to move forward with building an IDS and at each stage of a data sharing and integration project.The Four Questions-Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)?-should be carefully considered within established data governance processes and among core partners.

Systemic racism in data practices

Systemic racism in data practices

Ownership of individual-level health data, data sharing, and data governance

BackgroundThe ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership.Main bodyIn this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk mitigation, as well as technological, economic, and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks.ConclusionUndifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society.

Special issue editorial on emerging trends in internet of things for e‐health and medical supply chain systems

Special issue editorial on emerging trends in internet of things for e‐health and medical supply chain systems

Ethical Concerns About Reidentification of Individuals from MRI Neuroimages

Ethical Concerns About Reidentification of Individuals from MRI Neuroimages

Cars and distraction: How to address the limits of Driver Monitoring Systems and improve safety benefits using evidence from German young drivers

We are facing an increase in the emergence of distracting activities while driving. This is especially the case for young people who, more than other age groups, employ their cars as a place of personal fulfilment. This study proposes an interdisciplinary safe-by-design (SbD) heuristic to address this emerging risk. It harnesses a German version of the Behaviour of Young Novice Driver Scale (BYNDS) to gather representative information about young people's distracting activities. This information is then used to address to limitations of Driver Monitoring Systems (DMS) and posit safety measures in the context of young driver distraction. Our novel approach reveals three recommendations that should guide the employment of DMS in future generations of cars. We argue that the sole use of DMS Type 1 (i.e. vehicle motion data) is not sufficient to cope with the complex range of distracting activities that occur inside the car. We suggest designers and technologists employ DMS Type 2 (i.e. cameras and acoustic sensors) as this makes it possible to capture rich information about humans, objects and their interaction. In light of concerns about data privacy, policymakers must act to regulate the ethical use of data from the inside of the car and to find the necessary trade-off between data privacy and the unnecessary attrition of young human lives. This research provides a reasonable foundation for this discussion.

Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education

The purpose of this paper is to define a reference framework for introducing eLearning practices in mainly face-to-face higher education institutions. We suggest a suitable adoption and management of associated infrastructures and processes, in order to guarantee the ethical use of data in the related academic and learning analytics. A theoretical framework is proposed after years of practice and experience in the institutional government of IT processes related to learning technology. The digital transformation of teaching should imply the right technological decisions made by people and for people, in order to achieve a more inclusive, participative, and human university supported by technology. digital transformation is a social requirement of governments, companies, and institutions, and it should take into account the associated risks of the unethical use of technology, which leads to the dark side of transformation processes. eLearning approaches, especially with the influence of the COVID-19 outbreaks, are increasing the need for digital mechanisms in universities. Further, there is a need for strategical support and reference models if we are to avoid these undesired effects.

Value from health data: European opportunity to catalyse progress in digital health

Value from health data: European opportunity to catalyse progress in digital health

From Research Data Ethics Principles to Practice: Data Trusts as a Governance Tool

Artificial intelligence and data science offer tools that could advance the pace of discovery across research domains. By processing large datasets, extracting insights from new data sources, and identifying patterns or relationships that would not otherwise have been visible to researchers, these technologies can advance understandings of science and society. Achieving this potential will require that researchers have access to data that is governed in ways that respect both the benefits that data use can bring and the risks to individuals, communities and society that can follow. Recent years have seen numerous examples of the ways in which these risks can be manifest, some of which also serve to highlight the ethical implications of pursuing behavioural research using advanced data analytics. Over the same period, researchers and policymakers have been active in developing frameworks that enable ethical data use. A range of data sharing structures exist, which are differently suited to achieving different governance aims. In seeking to connect the desire to share data with concerns about individual rights, data trusts offer a promising mechanism for future development. For researchers, data trusts offer a means of accessing multiple data types in a more streamlined way than current contract-based structures allow. For research participants, they provide a route to exerting informed influence over how and for what purposes data about them is used.

Tehnološki trendovi razvoja visokog obrazovanja

The aim of this paper is to present and analyse the Internet of Things and Technology-Supported Learning Environments, which represent current technological trends of higher education development. The method used in the paper is content analysis of available scientific literature - theoretical and empirical. It is shown how the application and integration of these technologies trigger significant socio-technological changes in the conditions in which higher education operates. The results show that the application of these technologies enables material savings, that it can result in increasing of the efficiency and effectiveness of the higher education processes and in adapting of the teaching process to the individual needs of students. The paper further discusses the challenges and risks that these technological change can bring to higher education and society as a whole. In the conclusion, it is pointed out that despite the numerous advantages that are being realized, it is necessary to develop human resource competencies and find solutions related to the ethical use of data.

Communicating With Patients About Software for Enhancing Privacy in Secondary Database Research Involving Record Linkage: Delphi Study.

BackgroundThere is substantial prior research on the perspectives of patients on the use of health information for research. Numerous communication barriers challenge transparency between researchers and data participants in secondary database research (eg, waiver of informed consent and knowledge gaps). Individual concerns and misconceptions challenge the trust in researchers among patients despite efforts to protect data. Technical software used to protect research data can further complicate the public's understanding of research. For example, MiNDFIRL (Minimum Necessary Disclosure For Interactive Record Linkage) is a prototype software that can be used to enhance the confidentiality of data sets by restricting disclosures of identifying information during the record linkage process. However, software, such as MiNDFIRL, which is used to protect data, must overcome the aforementioned communication barriers. One proposed solution is the creation of an interactive web-based frequently asked question (FAQ) template that can be adapted and used to communicate research issues to data subjects.ObjectiveThis study aims to improve communication with patients and transparency about how complex software, such as MiNDFIRL, is used to enhance privacy in secondary database studies to maintain the public's trust in researchers.MethodsA Delphi technique with 3 rounds of the survey was used to develop the FAQ document to communicate privacy issues related to a generic secondary database study using the MiNDFIRL software. The Delphi panel consisted of 38 patients with chronic health conditions. We revised the FAQ between Delphi rounds and provided participants with a summary of the feedback. We adopted a conservative consensus threshold of less than 10% negative feedback per FAQ section.ResultsWe developed a consensus language for 21 of the 24 FAQ sections. Participant feedback demonstrated preference differences (eg, brevity vs comprehensiveness). We adapted the final FAQ into an interactive web-based format that 94% (31/33) of the participants found helpful or very helpful. The template FAQ and MiNDFIRL source code are available on GitHub. The results indicate the following patient communication considerations: patients have diverse and varied preferences; the tone is important but challenging; and patients want information on security, identifiers, and final disposition of information.ConclusionsThe findings of this study provide insights into what research-related information is useful to patients and how researchers can communicate such information. These findings align with the current understanding of health literacy and its challenges. Communication is essential to transparency and ethical data use, yet it is exceedingly challenging. Developing FAQ template language to accompany a complex software may enable researchers to provide greater transparency when informed consent is not possible.

Utilization of Mobility Data in the Fight Against COVID-19.

Utilization of Mobility Data in the Fight Against COVID-19.

Ethical and privacy considerations for research using online fandom data

As online fandom continues to grow, so do the public data created by fan creations and interactions. With researchers and journalists regularly engaging with those data (and not always asking permission), many fans are concerned that their content might end up in front of the wrong audience, which could lead to privacy violations or even harassment from within or outside of fandom. To better understand fan perspectives on the collection and analysis of public data as a methodology, we conducted both an interview study and a survey to solicit responses that would help provide a broader understanding of fandom's privacy norms as they relate to the ethical use of data. We use these findings to revisit and recommend best practices for working with public data within fandom.

International Trade Law Meets Data Ethics: A Brave New World

The unprecedented integration of digital technologies in the economic and social lives of human beings has led to strong concerns regarding the ethical use of data collected by such technologies. In response to these concerns, several intergovernmental and multistakeholder bodies as well as individual governments have started devising data ethics compliance frameworks. These frameworks integrate certain core principles such as human rights protection, ethical design, algorithmic accountability, and data privacy and security. Governments are now also imposing measures to achieve greater compliance with these core principles of data ethics including banning certain (especially foreign) data-driven applications and services; restricting cross-border transfers and processing of data; and imposing varied corporate compliance requirements for offering data-driven technologies. However, some measures aimed at protecting and promoting data ethics (Data Ethics-related Measures) can have the consequence of restricting cross-border trade, especially in digital and data-driven services and technologies. Against this background, this article assesses whether Data Ethics-related Measures are consistent with international trade law, looking at the treaties of the World Trade Organization (WTO) and several Preferential Trade Agreements (PTAs). It argues that certain Data Ethics-related Measures may be inconsistent with obligations contained in international trade agreements, including obligations on non-discrimination, market access, domestic regulation, and intellectual property protection. However, international trade law does not per se inhibit Data Ethics-related Measures. For instance, exceptions contained in international trade agreements can be interpreted to allow measures that support a human rights-centric approach to data governance. Further, rules on trade secret protection may be interpreted and applied meaningfully to balance commercial and critical public interests such as facilitating algorithmic accountability and ethical design in data-driven technologies. Finally, provisions on domestic regulation can potentially ensure that Data Ethics-related Measures are implemented in a fair and objective manner, and that technical standards and licensing requirements for data-driven digital services are transparent, objective, and not unnecessarily burdensome. However, given the legal, technological, and political uncertainties at hand, governments are unlikely to perceive trade rules as a foolproof mechanism to preserve their policy space for regulating data-driven technologies for ethical reasons. Therefore, this article explores new avenues in international trade law to accommodate data ethics norms. It argues that international trade institutions can better co-opt data ethics frameworks by facilitating enhanced high-level cooperation among countries on cross-border data transfer mechanisms as well as digital development and inclusion. For example, trade bodies, including the WTO, can proactively engage with other international, regional, and transnational or multistakeholder bodies involved in norm development in data ethics, especially on privacy/data protection, digital inclusion, and the ethical use of data in the designing and application of digital technologies. Further, where appropriate and necessary, international trade rules must acknowledge the prevailing global best practices in data-driven sectors, especially the role of multistakeholder and private technical standards and protocols in promoting ethical and robust data-driven technologies. One possible means to do so is adopting new rules at the WTO and through PTAs (especially for trade in services and electronic commerce) that recognize relevant technical standards, protocols and best practices developed by multistakeholder internet institutions and representative private sector bodies.

The Issue of "Context": Data, Culture, and Commercial Context in Social Media Ethics.

One of the central concerns in research ethics in recent years has been the vast amount of data available from social media platforms and the related concerns around what establishes an ethical use of data. Toward addressing these challenges, researchers have therefore called for the consideration of "context" in Internet research. However, context remains a fuzzy concept and little guidance exists on its different dimensions. In response to this issue, this article uses worked examples from three data sets to discuss three different dimensions of "context": data context, cultural context, and commercial context. The article problematizes these dimensions and offers suggestions toward creating ethical sensibility to these by drawing on two data sets from 2017: (a) climate change imagery scraped from five social platforms and (b) digital-ethnographic work at the climate summit COP23.

Navigating Institutional Culture in Ensuring the Ethical Use of Data in Support of Student Success and Institutional Effectiveness

AbstractIn this chapter, we explore the contexts within which institutional researchers must try to ensure the ethical use of data. We also identify challenges institutional research professionals can face when navigating college culture while trying to ensure the ethical use of data. Finally, we identify potential solutions for improving institutional data culture.

Africa's science academy leads push for ethical data use.

The goal is to create the continent’s first cross-disciplinary guidelines for collecting, storing and sharing data and specimens. The goal is to create the continent’s first cross-disciplinary guidelines for collecting, storing and sharing data and specimens.

Automated vehicles, big data and public health.

In this paper we focus on how automated vehicles can reduce the number of deaths and injuries in accident situations in order to protect public health. This is actually a problem not only of public health and ethics, but also of big data-not only in terms of all the different data that could be used to inform such decisions, but also in the sense of deciding how wide the scope of data should be. We identify three key different types of data, including basic data, advanced data and preference data, provide an ethical analysis of the use of these different types of data and of different ways of prioritizing between pedestrians and passengers, and propose four rules that can help set ethical priorities for ethical data use and decision making by automated vehicles.