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Data science: connotation, methods, technologies, and development

Data Science and Management, 2021
The rapid development of big data breeds data science. Understanding and mastering the internal pattern of the value generation of big data is important for improving digitization and the covergence of data science with management science, computer ...
Zongben Xu, Niansheng Tang, Chen Xu, Xueqi Cheng   +3 more
doaj   +1 more source

Data Science and Big Data in Energy Forecasting [PDF]

, 2018
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal.
Martínez Álvarez, Francisco, Riquelme Santos, José Cristóbal, Troncoso Lora, Alicia   +2 more
core   +1 more source

Population Data Science: The science of data about people

International Journal of Population Data Science, 2018
Introduction Societal and individual benefits of data-intensive science are substantial but raise challenges of balancing individual privacy and public good, while building appropriate governance and socio-technical systems to support data-intensive ...
Kim McGrail, Kerina Jones
doaj   +1 more source

Spatial Data Science

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, Maribel Yasmina Santos, Martin Behnisch   +2 more
doaj   +1 more source

Data Science Ethos Lifecycle: Interplay of Ethical Thinking and Data Science Practice

Journal of Statistics and Data Science Education, 2022
This article presents the Data Science Ethos Lifecycle, a tool for engaging responsible workflow developed by an interdisciplinary team of social scientists and data scientists working with the Academic Data Science Alliance. The tool uses a data science
Margarita Boenig-Liptsin, Anissa Tanweer, Ari Edmundson   +2 more
doaj   +1 more source

Thoughts on Starting the CODATA Data Science Journal

Data Science Journal, 2023
This essay discusses some of the considerations that led to the founding of the [CODATA] Data Science Journal. Three factors were most relevant to the founding.
John Rumble
doaj   +1 more source

Human Data Science

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
doaj   +1 more source

Looking Back to the Future: A Glimpse at Twenty Years of Data Science

Data Science Journal, 2023
This paper carries out a lightweight review to explore the potentials of data science in the last two decades and especially focuses on the four essential components: data resources, technologies, data infrastructures, and data education. Considering the
Lili Zhang
doaj   +1 more source

Curriculum Guidelines for Undergraduate Programs in Data Science [PDF]

, 2017
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science.
Agarwal, Mahesh, Averett, Maia, Baumer, Benjamin, Bray, Andrew, Bressoud, Thomas, Bryant, Lance, Cheng, Lei, De Veaux, Richard, Francis, Amanda, Gould, Robert, Kim, Albert Y., Kretchmar, Matt, Lu, Qin, Moskol, Ann, Nolan, Deborah, Pelayo, Roberto, Raleigh, Sean, Sethi, Ricky J., Sondjaja, Mutiara, Tiruviluamala, Neelesh, Uhlig, Paul, Washington, Talitha, Wesley, Curtis, White, David, Ye, Ping   +24 more
core   +3 more sources

Towards Data Science

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
doaj   +1 more source