Results 1 to 10 of about 28,511,988 (353)
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
openaire +8 more sources
Re-engineering Clinical Trial Management System Using Blockchain Technology
Blockchain in Healthcare Today, 2022 The annual ConV2X is a leading international health tech symposium driving real world evidence, strategy, research, operations and trends to create a blueprint for a new digital health era.
Yan Zhuang, PhD, National Institute of Health Data Science, Peking University +2 more
doaj +1 more source
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
openaire +4 more sources
Data Science — definition and structural representation
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2021 This article is a continuation of the discussion on the existing meanings and formalization of the definition of “Data Science” as an autonomous discipline, field of knowledge, clarification of its defining components, integration, and interaction ...
Pavlo Maslianko, Yevhenii Sielskyi
doaj +1 more source
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.
Padhraic Smyth, David M. Blei
openaire +2 more sources
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
openaire +3 more sources
Big Data and Cognitive Computing, 2023 ChatGPT, a conversational AI interface that utilizes natural language processing and machine learning algorithms, is taking the world by storm and is the buzzword across many sectors today.
Hossein Hassani, E. Silva
semanticscholar +1 more source
Journal of Statistics and Data Science Education, 2023 ChatGPT is one of many generative artificial intelligence (AI) tools that has emerged recently, creating controversy in the education community with concerns about its potential to be used for plagiarism and to undermine students’ ability to think ...
Amanda R. Ellis, E. Slade
semanticscholar +1 more source
Designing Data Science Workshops for Data-Intensive Environmental Science Research
Journal of Statistics and Data Science Education, 2021 Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs.
Allison S. Theobold +2 more
doaj +1 more source
Journal of Data Science and Intelligent Systems, 2023 This paper investigates the significance of data science as an indispensable instrument for decision-making across multiple domains. The study examines the history, concepts, methods, and applications of data science, as well as its impact on numerous ...
Narender Chinthamu, Manideep Karukuri
semanticscholar +1 more source