Results 61 to 70 of about 28,550,776 (217)

Data Science: Measuring Uncertainties

Entropy, 2020
With the increase in data processing and storage capacity, a large amount of data is available [...]
Carlos Alberto de Braganca Pereira, Adriano Polpo, Agatha Sacramento Rodrigues   +2 more
doaj   +1 more source

Perspectives on Marine Data Science as a Blueprint for Emerging Data Science Disciplines

Frontiers in Marine Science, 2021
Earth System Sciences have been generating increasingly larger amounts of heterogeneous data in recent years. We identify the need to combine Earth System Sciences with Data Sciences, and give our perspective on how this could be accomplished within the ...
Maria-Theresia Verwega, Maria-Theresia Verwega, Carola Trahms, Carola Trahms, Avan N. Antia, Thorsten Dickhaus, Enno Prigge, Martin H. U. Prinzler, Martin H. U. Prinzler, Matthias Renz, Markus Schartau, Thomas Slawig, Christopher J. Somes, Arne Biastoch, Arne Biastoch   +14 more
doaj   +1 more source

QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

, 2018
We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers.
Evan Bolyen, J. Rideout, Matthew R. Dillon, N. Bokulich, C. Abnet, Gabriel A. Al-Ghalith, Harriet Alexander, Harriet Alexander, E. Alm, Manimozhiyan Arumugam, F. Asnicar, Yang Bai, J. Bisanz, K. Bittinger, A. Brejnrod, Colin J. Brislawn, C. T. Brown, B. Callahan, A. Caraballo-Rodríguez, John H. Chase, Emily K. Cope, R. R. Silva, P. Dorrestein, G. Douglas, D. Durall, C. Duvallet, C. Edwardson, Madeleine Ernst, M. Estaki, Jennifer T. Fouquier, J. Gauglitz, D. Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin M Hillmann, S. Holmes, H. Holste, C. Huttenhower, C. Huttenhower, G. Huttley, Stefan Janssen, Alan K. Jarmusch, Lingjing Jiang, Benjamin D. Kaehler, K. Kang, K. Kang, Christopher R. Keefe, P. Keim, S. Kelley, D. Knights, I. Koester, I. Koester, T. Kosciólek, Jorden Kreps, M. Langille, Joslynn S. Lee, R. Ley, R. Ley, Yong-xin Liu, E. Loftfield, C. Lozupone, Massoud Maher, C. Marotz, Bryan D. Martin, Daniel McDonald, L. McIver, L. McIver, A. Melnik, J. Metcalf, S. C. Morgan, James T. Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Jose A Navas-Molina, Louis-Félix Nothias, Stephanie B. Orchanian, Talima R. Pearson, Samuel L. Peoples, Samuel L. Peoples, D. Petráš, M. Preuss, E. Pruesse, Lasse Buur Rasmussen, A. Rivers, Ii Michael S Robeson, P. Rosenthal, N. Segata, Michael Shaffer, A. Shiffer, R. Sinha, Se Jin Song, J. Spear, Austin D. Swafford, Luke R. Thompson, Luke R. Thompson, P. Torres, Pauline Trinh, A. Tripathi, A. Tripathi, P. Turnbaugh, Sabah Ul-Hasan, J. J. Hooft, Fernando Vargas, Y. Vázquez-Baeza, E. Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C. Weber, Kyle C. Weber, Chase Williamson, A. Willis, Z. Xu, Jesse R. Zaneveld, Yilong Zhang, R. Knight, J. Caporaso   +119 more
semanticscholar   +1 more source

Defining Data Science [PDF]

arXiv, 2015
Data science is gaining more and more and widespread attention, but no consensus viewpoint on what data science is has emerged. As a new science, its objects of study and scientific issues should not be covered by established sciences. Data in cyberspace have formed what we call datanature.
arxiv  

What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature [PDF]

Journal of Data and Information Science (2022)
This paper reviews literature pertaining to the development of data science as a discipline, current issues with data bias and ethics, and the role that the discipline of information science may play in addressing these concerns. Information science research and researchers have much to offer for data science, owing to their background as ...
arxiv   +1 more source

Data Science in 2020: Computing, Curricula, and Challenges for the Next 10 Years

Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains ...
Aimee Schwab-McCoy, Catherine M. Baker, Rebecca E. Gasper   +2 more
doaj   +1 more source

Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl

Nature Methods, 2019
Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative analysis of imaging data for biological and biomedical applications.
Juan C. Caicedo, A. Goodman, Kyle W. Karhohs, B. Cimini, Jeanelle Ackerman, Marzieh Haghighi, Cherkeng Heng, Tim Becker, M. Doan, C. McQuin, M. Rohban, Shantanu Singh, Anne E Carpenter   +12 more
semanticscholar   +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  

Starting with data: advancing spatial data science by building and sharing high-quality datasets [PDF]

arXiv, 2020
Spatial data science has emerged in recent years as an interdisciplinary field. This position paper discusses the importance of building and sharing high-quality datasets for spatial data science.
arxiv  

How sustainable is "common" data science in terms of power consumption? [PDF]

arXiv, 2022
Continuous developments in data science have brought forth an exponential increase in complexity of machine learning models. Additionally, data scientists have become ubiquitous in the private market, academic environments and even as a hobby. All of these trends are on a steady rise, and are associated with an increase in power consumption and ...
arxiv