Results 21 to 30 of about 13,729,805 (320)

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

Risk Assessment for Scientific Data

Data Science Journal, 2020
Ongoing stewardship is required to keep data collections and archives in existence. Scientific data collections may face a range of risk factors that could hinder, constrain, or limit current or future data use.
Matthew S. Mayernik, Kelsey Breseman, Robert R. Downs, Ruth Duerr, Alexis Garretson, Chung-Yi (Sophie) Hou, Environmental Data Governance Initiative (EDGI) and Earth Science Information Partners (ESIP) Data Stewardship Committee   +6 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

Data Science and Earth System Science

, 2022
AbstractData-driven science has turned into a fourth fundamental paradigm of performing research. Earth System Science, following a holistic approach in unraveling the complex network of processes and interactions shaping system Earth, particularly profits from embracing data-driven approaches next to observation and modeling.
zu Castell, Wolfgang, Ruhnke, Roland, Bouwer, Laurens M., Brix, Holger, Dietrich, Peter, Dransch, Doris, Frickenhaus, Stephan, Greinert, Jens, Petzold, Andreas   +8 more
openaire   +4 more sources

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
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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

Microbiome data science

Journal of Biosciences, 2019
Best practices from open data science are spreading across research fields, providing new opportunities for research and education. Open data science emphasizes the view that digitalization is enabling new forms of resource sharing, collaboration and outreach.
Shetty, Sudarshan A., Lahti, Leo
openaire   +3 more sources

A Data Science Course for Undergraduates: Thinking with Data [PDF]

, 2015
Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly ...
Baumer, Ben
core   +3 more sources