Related papers: Practices and challenges in clinical data sharing
The lack of user experience standards in regulations for data privacy and data portability in the health sector increases the cost of leaving a network provider while not protecting the patient's privacy, directly impacting people's health.…
The aim of this article is to introduce a reporting framework for reproducible, interactive research applied to Big Clinical Data, based on open source technologies. The framework is constituted by the following three axes: (i) data, (ii)…
Remote healthcare technology can help tackle societal issues by improving access to quality healthcare services and enhancing diagnoses through in-place monitoring. These services can be implemented through a combination of mobile devices,…
There are many initiatives of transparency reported in the access and use of government open data for different purposes. This practice reveals an important requirement to accomplish the participatory governance. The literature has reported…
Many programming frameworks have been introduced to support the development of differentially private software applications. In this chapter, we survey some of the conceptual ideas underlying these frameworks in a way that we hope will be…
Patient-controlled data-sharing systems are increasingly promoted as a way to empower patients with greater autonomy over their health data. Yet it remains unclear how different stakeholders, especially patients and health system leaders,…
Data commons collate data with cloud computing infrastructure and commonly used software services, tools and applications to create biomedical resources for the large-scale management, analysis, harmonization, and sharing of biomedical…
As Large Language Models (LLMs) become integral to scientific workflows, concerns over the confidentiality and ethical handling of confidential data have emerged. This paper explores data exposure risks through LLM-powered scientific tools,…
Social media are a rich source of insight for data mining and user-centred research, but the question of consent arises when studying such data without the express knowledge of the creator. Case studies that mine social data from users of…
Access to diverse, high-quality datasets is crucial for machine learning model performance, yet data sharing remains limited by privacy concerns and competitive interests, particularly in regulated domains like healthcare. This dynamic…
The Web community has introduced a set of standards and technologies for representing, querying, and manipulating a globally distributed data structure known as the Web of Data. The proponents of the Web of Data envision much of the world's…
As more and more data is collected for various reasons, the sharing of such data becomes paramount to increasing its value. Many applications ranging from smart cities to personalized health care require individuals and organizations to…
Public data archives are the backbone of modern biological and biomedical research. While archives for biological molecules and structures are well-established, resources for imaging data do not yet cover the full range of spatial and…
Most of our lives are conducted in the cyberspace. The human notion of privacy translates into a cyber notion of privacy on many functions that take place in the cyberspace. This article focuses on three such functions: how to privately…
Across academia, government, and industry, data stewards are facing increasing pressure to make datasets more openly accessible for researchers while also protecting the privacy of data subjects. Differential privacy (DP) is one promising…
While the entire field of privacy preserving data analytics is focused on the privacy-utility tradeoff, recent work has shown that privacy preserving data publishing can introduce different levels of utility across different population…
Data privacy has become a major concern in healthcare due to the increasing digitization of medical records and data-driven medical research. Protecting sensitive patient information from breaches and unauthorized access is critical, as…
Networking research, especially focusing on human mobility, has evolved significantly in the last two decades and now relies on collection and analyzing larger datasets. The increasing sizes of datasets are enabled by larger automated…
Digital computational outputs are now ubiquitous in the research workflow and the way in which these data are stored and cataloged is becoming more standardized across fields of research. However, even with accessible data and code, the…
The popularity of the online media-driven social network relation is proven in today's digital era. The many challenges that these emergence has created include a huge growing network of social relations, and the large amount of data which…