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Visualization in data science [PDF]
IEEE Computer Graphics and Applications, 2019 This Special Issue of IEEE Computer Graphics and Applications highlights six papers from the Symposium on Visualization in Data Science (VDS) held in Berlin, Germany in October 2018. VDS brought together hundreds of domain scientists and methods researchers (including visualization, usability and HCI, data management, statistics, machine learning, and ...
Adam, Perer, Shixia, Liu
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Proceedings of the ACM on Programming Languages, 2020 Data science is increasingly important and challenging. It requires computational tools and programming environments that handle big data and difficult computations, while supporting creative, high-quality analysis. The R language and related software play a major role in computing for data science.
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ACM Computing Surveys, 2017 The 21st century has ushered in the age of big data and data economy, in which data DNA , which carries important knowledge, insights, and potential, has become an intrinsic constituent of all data-based organisms. An appropriate understanding of data DNA and its organisms relies on the new field of data
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Data-driven predictions in the science of science
Science, 2017 The desire to predict discoveries—to have some idea, in advance, of what will be discovered, by whom, when, and where—pervades nearly all aspects of modern science, from individual scientists to publishers, from funding agencies to hiring committees. In this Essay, we survey the emerging and interdisciplinary field of the “science of science” and what ...
Clauset, Aaron +2 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.
Andrienko, Gennady +2 more
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Data Science and Prediction [PDF]
SSRN Electronic Journal, 2012 Big data promises automated actionable knowledge creation and predictive models for use by both humans and computers.
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Mechanism Design for Data Science
, 2014 Good economic mechanisms depend on the preferences of participants in the mechanism. For example, the revenue-optimal auction for selling an item is parameterized by a reserve price, and the appropriate reserve price depends on how much the bidders are ...
Chawla, Shuchi +2 more
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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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ICSU and the Challanges of Data and Information Management for International Science
Data Science Journal, 2013 The International Council for Science (ICSU) vision explicitly recognises the value of data and information to science and particularly emphasises the urgent requirement for universal and equitable access to high quality scientific data and information ...
Peter Fox, Ray Harris
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Activities of the Polar Environment Data Science Center of ROIS-DS, Japan
Data Science Journal, 2022 The Polar Environment Data Science Center (PEDSC) is one of the centers of the Joint Support-Center for Data Science Research (DS) of the Research Organization of Information and Systems (ROIS), which was established in 2017.
Akira Kadokura +4 more
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