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Security of Data Science and Data Science for Security [PDF]
, 2019 In this chapter, we present a brief overview of important topics regarding the connection of data science and security. In the first part, we focus on the security of data science and discuss a selection of security aspects that data scientists should consider to make their services and products more secure.
Tellenbach, Bernhard +2 more
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ISPRS International Journal of Geo-Information, 2020 The field of data science has had a significant impact in both academia and industry, and with good reason [...]
Fernando Bacao +2 more
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Science and data science [PDF]
Proceedings of the National Academy of Sciences, 2017 Data science has attracted a lot of attention, promising to turn vast amounts of data into useful predictions and insights. In this article, we ask why scientists should care about data science. To answer, we discuss data science from three perspectives: statistical, computational, and human.
David M. Blei, Padhraic Smyth
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Open Science and Data Science [PDF]
Data Intelligence, 2021 Data Science (DS) as defined by Jim Gray is an emerging paradigm in all research areas to help finding non-obvious patterns of relevance in large distributed data collections. “Open Science by Design” (OSD), i.e., making artefacts such as data, metadata, models, and algorithms available and re-usable to peers and beyond as early as possible, is a pre ...
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Proceedings of the National Academy of Sciences, 2020 Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data ...
Yu, Bin, Kumbier, Karl
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Diversifying the genomic data science research community [PDF]
, 2022 Over the past 20 years, the explosion of genomic data collection and the cloud computing revolution have made computational and data science research accessible to anyone with a web browser and an internet connection.
Genomic Data Science Community Network, .
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The science is in the data [PDF]
IUCrJ, 2017 Understanding published research results should be through one's own eyes and include the opportunity to work with raw diffraction data to check the various decisions made in the analyses by the original authors. Today, preserving raw diffraction data is technically and organizationally viable at a growing number of data archives, both centralized and ...
John R. Helliwell +3 more
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The Computer Journal, 2016 The field of Data Science concerns techniques for extracting knowledge from diverse data, with a particular focus on ‘big’ data exhibiting ‘V’ attributes such as volume, velocity, variety, value and veracity. The field of data science is becoming increasingly influential in the public, private and voluntary sectors, with its overarching aim of ...
Maneth, Sebastian +1 more
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IEEE Computer Graphics and Applications, 2017 Data science methods and approaches address all stages of transition from data to knowledge and action. Visualization of this data is essential for human understanding of the subject under study, analytical reasoning about it, and generating new knowledge.
Gennady L. Andrienko +2 more
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