Trust in Centralized Large-Scale Data Repository: A Qualitative Analysis

Exponential increases in digital data and calls for participation in human research raise questions about when and why individuals voluntarily provide personal data. We conducted 36 in-depth interviews with ex-participants, participants, and nonparticipants in a biobank to identify key factors influencing trust in centralized large-scale data repository for human research. Our findings indicated that trust depends strongly on whether such data repository benefits the public, the interests of data collectors, the characteristics of the collected data, and application of informed consent for retaining control over personal data. Concerns about the aims and range of data repository appeared to influence withdrawal of participation. Our findings underscore ethical and practical issues relating to data collection and consent procedures in human research.

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Opportunities for Understanding MS Mechanisms and Progression With MRI Using Large-Scale Data Sharing and Artificial Intelligence

Neurology ◽

10.1212/wnl.0000000000012884 ◽

2021 ◽

pp. 10.1212/WNL.0000000000012884

Author(s):

Hugo Vrenken ◽

Mark Jenkinson ◽

Dzung Pham ◽

Charles R.G. Guttmann ◽

Deborah Pareto ◽

...

Keyword(s):

Artificial Intelligence ◽

Image Analysis ◽

Data Sharing ◽

Large Scale ◽

Personal Data ◽

Human Observer ◽

Imaging Data ◽

Large Scale Data ◽

Scale Data

Multiple sclerosis (MS) patients have heterogeneous clinical presentations, symptoms and progression over time, making MS difficult to assess and comprehend in vivo. The combination of large-scale data-sharing and artificial intelligence creates new opportunities for monitoring and understanding MS using magnetic resonance imaging (MRI).First, development of validated MS-specific image analysis methods can be boosted by verified reference, test and benchmark imaging data. Using detailed expert annotations, artificial intelligence algorithms can be trained on such MS-specific data. Second, understanding disease processes could be greatly advanced through shared data of large MS cohorts with clinical, demographic and treatment information. Relevant patterns in such data that may be imperceptible to a human observer could be detected through artificial intelligence techniques. This applies from image analysis (lesions, atrophy or functional network changes) to large multi-domain datasets (imaging, cognition, clinical disability, genetics, etc.).After reviewing data-sharing and artificial intelligence, this paper highlights three areas that offer strong opportunities for making advances in the next few years: crowdsourcing, personal data protection, and organized analysis challenges. Difficulties as well as specific recommendations to overcome them are discussed, in order to best leverage data sharing and artificial intelligence to improve image analysis, imaging and the understanding of MS.

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The Origins of Happiness

10.23943/princeton/9780691196336.001.0001 ◽

2019 ◽

Author(s):

Andrew Clark ◽

Sarah Fléche ◽

Richard Layard ◽

Nattavudh Powdthavee ◽

George Ward

Keyword(s):

Family Conflict ◽

Large Scale ◽

Well Being ◽

Key Factors ◽

Policy Changes ◽

Large Scale Data ◽

New Vision ◽

New Perspective ◽

The Life Course ◽

Scale Data

What makes people happy? This book seeks to revolutionize how we think about human priorities and to promote public policy changes that are based on what really matters to people. Drawing on a range of evidence using large-scale data from various countries, the authors consider the key factors that affect human well-being, including income, education, employment, family conflict, health, childcare, and crime. The book offers a new perspective on life satisfaction and well-being over the life course and a new vision for how we might become more healthy, happy, and whole.

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MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs

10.18653/v1/2020.acl-main.285 ◽

2020 ◽

Author(s):

Jifan Yu ◽

Gan Luo ◽

Tong Xiao ◽

Qingyang Zhong ◽

Yuquan Wang ◽

...

Keyword(s):

Large Scale ◽

Data Repository ◽

Large Scale Data ◽

Scale Data

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Beyond the Data Deluge: A Research Agenda for Large-Scale Data Sharing and Reuse

International Journal of Digital Curation ◽

10.2218/ijdc.v6i1.172 ◽

2011 ◽

Vol 6 (1) ◽

pp. 58-69 ◽

Cited By ~ 50

Author(s):

Ixchel M. Faniel ◽

Ann Zimmerman

Keyword(s):

Open Access ◽

Data Sharing ◽

Research Agenda ◽

Large Scale ◽

Scientific Data ◽

Digital Data ◽

System Level ◽

Large Scale Data ◽

Access To Data ◽

Scale Data

There is almost universal agreement that scientific data should be shared for use beyond the purposes for which they were initially collected. Access to data enables system-level science, expands the instruments and products of research to new communities, and advances solutions to complex human problems. While demands for data are not new, the vision of open access to data is increasingly ambitious. The aim is to make data accessible and usable to anyone, anytime, anywhere, and for any purpose. Until recently, scholarly investigations related to data sharing and reuse were sparse. They have become more common as technology and instrumentation have advanced, policies that mandate sharing have been implemented, and research has become more interdisciplinary. Each of these factors has contributed to what is commonly referred to as the "data deluge". Most discussions about increases in the scale of sharing and reuse have focused on growing amounts of data. There are other issues related to open access to data that also concern scale which have not been as widely discussed: broader participation in data sharing and reuse, increases in the number and types of intermediaries, and more digital data products. The purpose of this paper is to develop a research agenda for scientific data sharing and reuse that considers these three areas.

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Security

Computers and Society ◽

10.1093/oso/9780198827085.003.0013 ◽

2019 ◽

Author(s):

Ronald M. Baecker

Keyword(s):

Mobile Phones ◽

Large Scale ◽

Impact Damage ◽

Computer Systems ◽

Personal Data ◽

Sensitive Information ◽

Loss Of Life ◽

Large Scale Data ◽

Financial Losses ◽

Scale Data

Throughout history, humanity has invented valuable technologies and ways to organize society. These innovations are typically accompanied by risks. Fire cooks food, and also provides heat on cold nights. Yet, when left unchecked, fire can cause huge damage as well as loss of life. Cities enabled new forms of community and commerce. However, they brought us more thievery, and made it easier for epidemics to spread. The automobile allowed a separation of locales for work and residence; trucks allowed goods to be shipped long distances. But vehicular accidents have caused far greater injury and loss of life than did mishaps with horses and mules. Information technology, like other technologies, has potential for good and for harm. In the first six chapters, we introduced aspects of human activity, such as education, medicine, and government, in which IT has been transformative and mostly positive. The next three chapters examine areas in which the negatives of IT are dominant, in which risks seem everywhere. This chapter focuses on security. IT security flaws are exploited by outsiders for personal or political gain. In Chapter 8 we shall look at safety, where the risks are often injury or loss of life. In Chapter 9, we shall look at privacy, where the risks are exposure of private, confidential, and even sensitive information. Security is the attribute of a computer system that ensures that it can continue to function properly after an attack. Attacks against computer systems happen routinely now, are in the news almost every week, and are accelerating in numbers and in impact. Damage to both individuals and organizations—financial losses, chaos, and deteriorating morale— is severe. We shall provide a primer on the multitude of ways computer systems, from large networks to mobile phones, can be ‘hacked’ so that they no longer function properly. We shall define the most common kinds of destructive software, often called malware. We will discuss large-scale data breaches, which now happen frequently and expose the personal data of millions to billions of people. The word hackers refers to individuals who disrupt digital technologies and thereby damage the functioning of an institution or a society.

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Stakeholder perspectives on the development and implementation of approaches to municipal rat management

Journal of Urban Ecology ◽

10.1093/jue/juab013 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Michael J Lee ◽

Kaylee A Byers ◽

Susan M Cox ◽

Craig Stephen ◽

David M Patrick ◽

...

Keyword(s):

Large Scale ◽

The United States ◽

Rapid Urbanization ◽

Resource Limitations ◽

Stakeholder Perspectives ◽

Large Scale Data ◽

Municipal Management ◽

Management Approaches ◽

Depth Interviews ◽

Scale Data

Abstract Rats evoke public health and economic concern in cities globally. Rapid urbanization exacerbates pre-existing rat problems, requiring the development and adoption of more effective methods of prevention, monitoring and mitigation. While previous studies have indicated that city-wide municipal management approaches often fail, such outcomes are often left without specific explanation. To determine how municipalities could more effectively develop and implement large-scale approaches, we interviewed stakeholders in municipal rat management programs to document their opinions, recommendations and the challenges they face. Using a thematic framework method, this study collates and analyzes in-depth interviews with 39 stakeholders from seven cities across the United States. Overall, stakeholders’ recommendations for municipal rat management aligned with many conceptual attributes of effective management reported in the literature. Specifically, stakeholders highlighted the need to prioritize the reduction of resources available to sustain rat infestations (e.g. food, water and harborage), to focus on proactive (vs. reactive) measures, and to implement large-scale data collection to increase the efficiency of cross-city rat control. Stakeholders also suggested novel approaches to management, such as mitigating rat-associated risks for vulnerable populations specifically and developing tailored initiatives based on the specific needs and desires of residents. We synthesize these recommendations in light of reported barriers, such as resource limitations, and consider several opportunities that may help municipalities reconceptualize their approaches to city-wide rat management.

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Dude, Where’s My Data? The Effectiveness of Laws Governing Data Breaches in Australia

Australian Journal of Telecommunications and the Digital Economy ◽

10.18080/jtde.v9n2.381 ◽

2021 ◽

Vol 9 (2) ◽

pp. 47-68

Author(s):

Jack Hile

Keyword(s):

Large Scale ◽

Personal Data ◽

Data Breach ◽

Operational Effectiveness ◽

Data Breaches ◽

Privacy Act ◽

Large Scale Data ◽

Scale Data

The increasing prevalence of large-scale data breaches prompted Australia to strengthen the Privacy Act by enacting the Privacy Amendment (Notifiable Data Breaches) Act to regulate the behaviour of entities entrusted with personal data. However, this paper argues that these legislative instruments are ineffective when dealing with data breaches and their associated problems. In supporting this conclusion, this paper first develops a criterion for effective data breach law, and then evaluates the Australian framework against this criterion to determine its operational effectiveness. In addition, this paper analyses practical developments in the area of data-breach law to garner insights as to how the Australian framework can be made more effective. Ultimately, this paper concludes that the Australian framework is ineffective when dealing with large-scale data breaches, and recommends future legislative amendment as a means of bolstering its effectiveness.

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