Results 11 to 20 of about 13,846,560 (292)
Data Science Journal, 2015 Currently, a huge amount of data is being rapidly generated in cyberspace. Datanature (all data in cyberspace) is forming due to a data explosion. Exploring the patterns and rules in datanature is necessary but difficult.
Yangyong Zhu, Yun Xiong
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Patterns, 2020 Most data science is about people, and opinions on the value of human data differ. The author offers a synthesis of overly optimistic and overly pessimistic views of human data science: it should become a science, with errors systematically studied and ...
DL Oberski
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CoRR, 2015 Data Science---Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow.
Plaat, Aske
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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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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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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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Why geographic data science is not a science [PDF]
Geography Compass, 2020 Abstract “Data Science” has taken many disciplines by storm. And for a good reason: New forms and unseen quantities of data enter nearly every scientific field, substantially changing the ways how scientists do science, and potentially allowing them to answer old questions or to pose them in novel ways.
Scheider, Simon +3 more
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