Results 41 to 50 of about 12,687,490 (344)

Research Progress and Implementation of FAIR Principles for Scientific Data Management [PDF]

Nongye tushu qingbao xuebao, 2022
[Purpose/Significance] With the development of data-intensive scientific research paradigm, the effective discovery and reuse of scientific data is of great significance to the sharing of research results.
CHEN Shuxian, LIU Guifeng, LIU Qiong
doaj   +1 more source

ChatGPT for Teaching and Learning: An Experience from Data Science Education [PDF]

, 2023
ChatGPT, an implementation and application of large language models, has gained significant popularity since its initial release. Researchers have been exploring ways to harness the practical benefits of ChatGPT in real-world scenarios. Educational researchers have investigated its potential in various subjects, e.g., programming, mathematics, finance,
arxiv   +1 more source

Prospecting (in) the data sciences [PDF]

Big Data & Society, 2020
Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains. We call this search for data “prospecting” and argue that the dynamics of prospecting are pervasive in, even characteristic of, data science.
Stephen C Slota, Andrew S Hoffman, David Ribes, Geoffrey C Bowker   +3 more
openaire   +4 more sources

Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects [PDF]

Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 136 (November 2018), 28 pages, 2020
The trustworthiness of data science systems in applied and real-world settings emerges from the resolution of specific tensions through situated, pragmatic, and ongoing forms of work. Drawing on research in CSCW, critical data studies, and history and sociology of science, and six months of immersive ethnographic fieldwork with a corporate data science
arxiv   +1 more source

Big-Data-Driven Materials Science and its FAIR Data Infrastructure [PDF]

, 2019
This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed.
A Agrawal, A Gulans, A Jain, A Jain, A Rahman, A Seko, A Siebes, A Ziletti, AH Larsen, AK Singh, AP Bartók, AP Bartók, BJ Alder, BJ Alder, BJ Alder, BR Goldsmith, C Draxl, C Draxl, CE Calderon, Claudia Draxl, D Lazer, DL Donoho, EJ Candro, EJ Candès, EJ Candès, ER Scerri, F Faber, F Herrera, G Kresse, GE Hinton, GE Hinton, IJ Nelson, IY Zhang, J Enkovaara, J Pearl, J Pizzi, J Saal, JC Slater, JC Slater, JC Slater, JC Slater, JC Slater, JH Friedman, K Hansen, K Hansen, K Lejaeghere, K Reuter, KF Garrity, KT Schütt, L Hedin, LM Ghiringhelli, LM Ghiringhelli, LM Ghiringhelli, M Atzmueller, M Rupp, MD Wilkinson, MJ Setten van, MT Yin, N Metropolis, Nature editorial, NV Chawla, P Blaha, P Hohenberg, P Pyykkö, R Ouyang, R Tibshirani, S Curtarolo, S Lorenz, S Lorenz, TB Blank, V Blum, VL Moruzzi, W Duivesteijn, W Kohn, Y Zhang   +74 more
core   +3 more sources

Opinionated practices for teaching reproducibility: motivation, guided instruction and practice [PDF]

, 2021
In the data science courses at the University of British Columbia, we define data science as the study, development and practice of reproducible and auditable processes to obtain insight from data. While reproducibility is core to our definition, most data science learners enter the field with other aspects of data science in mind, for example ...
arxiv   +1 more source

Developing a population-scale harmonised ethnicity-spine in Wales.

International Journal of Population Data Science, 2022
The COVID-19 pandemic has placed a spotlight on existing and enduring health inequalities experienced by different ethnic groups. There has been a longstanding call to generate and improve the use of ethnicity data available across different data ...
Ashley Akbari, Stuart Bedston, Hoda Abbasizanjani, Gareth Davies, Richard Fry, Emily Lowthian, Jane Lyons, Rhiannon Owen, Fatemeh Torabi, Kamlesh Khunti, Ronan Lyons   +10 more
doaj   +1 more source

Defining data science: a new field of inquiry [PDF]

arXiv, 2023
Data science is not a science. It is a research paradigm. Its power, scope, and scale will surpass science, our most powerful research paradigm, to enable knowledge discovery and change our world. We have yet to understand and define it, vital to realizing its potential and managing its risks. Modern data science is in its infancy.
arxiv  

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 ...
Aaron Clauset, Aaron Clauset, Roberta Sinatra, Roberta Sinatra, Daniel B. Larremore   +4 more
openaire   +4 more sources

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
doaj   +1 more source