Publication

Safer Ways for Researchers to Share Sensitive Data

2025

Abstract

Sharing and analyzing data are essential for solving complicated problems, like curing diseases or protecting the environment. However, sensitive data, such as medical records or financial details, must be kept private and secure. New technologies make sharing and using sensitive data safer by creating realistic versions of data that do not contain private details or sensitive information traceable to a person. These techniques, called synthetic data and encryption, are already helping researchers study diseases, detect fraud, and prepare for rare events like natural disasters. While challenges remain, such as improving the accuracy of synthetic data and reducing the energy needed to create it, these techniques could unlock safer, faster ways to share data so that researchers all over the world can collaborate more easily.

Official source

https://infoscience.epfl.ch/entities/publication/fd28f717-3f63-45e4-9bd8-7ee72e2ba311

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2025

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/fd28f717-3f63-45e4-9bd8-7ee72e2ba311

About this result

Related concepts (32)

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

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