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This DMP template has been designed to be applicable to any EPFL research project that produces, collects or processes research data that has not already a DMP from a funder or publisher. ...
Core to many scientific and analytics applications are spatial data capturing the position or shape of objects in space, and time series recording the values of a process over time. Effective analysis of such data requires a shift from confirmatory pipelin ...
The highest share of the global population lives in cities. The current configuration of the latter requires considerable amounts of resource flows causing the degradation of local and global ecosystems. To face the complexity of these challenges, scientis ...
An important prerequisite for developing trustworthy artificial intelligence is high quality data. Crowdsourcing has emerged as a popular method of data collection in the past few years. However, there is always a concern about the quality of the data thus ...
Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...
In recent years, funding agencies, governments, and international organization have issued a series of research data management and sharing policies, like the H2020 [1]. Researchers are encouraged or required to share their production in an open way, inclu ...
Despite the traction gained by the open data movement and the rise of big data and learning analytics in education, there is limited support for researchers in education to generate, access, and share experimental data using openly-available digital educat ...
Trust in the use of sensitive data is not nearly widespread. Even though there is no shortage in tools and methods to address the digitisation of our society and industries, the acquisition and access to non-open data represent the greatest challenge. In t ...
Information-intensive transformation is vital to realize the Industry 4.0 paradigm, where processes, systems, and people are in a connected environment. Current factories must combine different sources of knowledge with different technological layers. Taki ...
Purpose of ReviewData science is an exploding trans-disciplinary field that aims to harness the power of data to gain information or insights on researcher-defined topics of interest. In this paper, we review how data science can help advance environmental ...