SCIENCE DIRECT DATABASE:
Adams, James B. “Improving the Education of Computational Materials Scientists and Physicists.” Computational Material Scientists, vol. 2, no. 1, Jan. 1994, https://doi.org/10.1016/0927-0256(94)90062-0.
This source was written by a professor in the department of Material Science and Engineering at the University of Illinois. It details an account of concerns with the training of material scientists and lists not having a comprehensive detail on the computational side of that field to be a problem and having a computer science course as being needed.
INTERNET WEBSITE:
“Advances in Computational Research Transform Scientific Process and Discovery”. NSF. U.S National Science Foundation, 25 Mar. 2013, Advances in Computational Research Transform Scientific Process and Discovery | NSF - National Science Foundation.
This source was written by the U.S. National Science Foundation, an independent federal agency that supports research and education across many STEM fields. This article gives an overview of specific breakthroughs that the use of supercomputers in research have made in fields such as biology, medicine, and geology.
SCIENCE DIRECT DATABASE:
Arya, Resham, et al. “A Survey of Multidisciplinary Domains Contributing to Affective Computing.” Computer Science Review, vol. 40, May 2021, https://doi.org/10.1016/j.cosrev.2021.100399.
This source was written by professors in computer science and engineering at Chitkara University. It gives perspective on how use of computing in other disciplines is used to advance technology in affective computing.
INTERNET WEBSITE:
Brandel, Mary. “When Art Meets Science.” Computerworld, vol. 40, no. 38, Sept. 2006, pp. 50–52. EBSCOhost, research.ebsco.com/linkprocessor/plink?id=92710db7-39ad-32e7-a238-85b1097db94f.
This source was written by an executive editor at Triangle Publishing Services and a Contributing editor at Cognizant Technology Solutions. The article provides insight on how business analysts have an increasing need for effective computing skills.
O'REILY TECHNICAL EBOOKS:
Elngar, Ahmed, et al. Applications of Computational Intelligence in Multi-Disciplinary Research. Academic Press, 2022, https://doi.org/10.1016/C2020-0-01066-2.
This source was written by many academics in computing including areas such as informatics, applied software, and artificial intelligence at institutions including the Beni-Suef University, University of Sharjah, University of Arad, and Mansoura University. This source gives an in-depth look at how computation is applied in research fields and how barriers are navigated and pushed in this way.
PLOS COMPUTATIONAL BIOLOGY DATABASE:
Gallagher, Kit, et al. “Ten Simple Rules for Training Scientists to Make Better Software.” PLoS Computational Biology, 12 Sept. 2008, https://doi.org/10.1371/journal.pcbi.1012410.
This source was conducted by specialists in computer science and statistics at the University of Oxford. It gives insight on how computation can present limits in preserving the quality of research because of its lack of reproducibility.
ACADEMIC SEARCH COMPLETE DATABASE:
Horstman, Klasien, et al. “Walking the Line between Lab and Computation: The ‘Moist’ Zone.” BioScience, vol. 58, no. 8, Sept. 2008, pp. 747–55. EBSCOhost, https://doi.org/10.1641/B580811.
This source was written by professors of biomedicine and public health at Maastricht University. This provides insight into the mixing of wet and dry sciences and how downfalls can include miscommunication and conflicting priorities. It also provides information on how these can be remedied.
CREDO REFERENCE INFOBASE:
Reilly, Edwin, et al. “Limits of Computation.” Encyclopedia of Computer Science, 4th ed., Wiley, 2003. Credo Reference, https://search.credoreference.com/articles/Qm9va0FydGljbGU6MTY2NTUyMQ==?aid=102912.
This source was composed by professors of computer science at the State University of New York. It gives a look at how computation can be physically limited when it comes to working with extremely large and complex datasets.
INTERNET WEBSITE:
Singh, Nisha. “The Metamorphosis from a Wet to Dry Lab Researcher: A Journey of Grit and Fervor.” IndiaBioscience, IndiaBioscience, 3 Feb. 2023, The metamorphosis from a wet to a dry lab researcher - a journey of grit and fervour - IndiaBioscience.
This source was written by an assistant professor of bioinformatics at Gujrat Biotechnology University. It includes a firsthand account of a researcher going through the shift between wet (physical science) and dry lab (computational science) sciences.
SCIENCE DIRECT DATABASE:
Story, Veda, and Richard Baskerville. “Digitalization of the Natural Sciences: Design Science Research and Computational Science.” Decision Support Systems, vol. 189, Feb. 2025, https://doi.org/10.1016/j.dss.2024.114368.
This article was written by professors of computer information systems and computer science at Georgia State University. It gives insight into the systems, devices, and software that need to be implemented and developed in order to keep up with the digitization of science.
SCIENCE DIRECT DATABASE:
“The Carbon Footprint of Computational Research.” Nature Computational Science, vol. 3, 17 Aug. 2023, https://doi.org/10.1038/s43588-023-00506-2.
This source was conducted by the Natural Science Computation, a journal that is focused on the fundamental and applied sciences. It provides information on the implications of high-power computing in research. Statistics are shown to quantify the carbon impact on such practices.
INTERNET WEBSITE:
Van Kessel, Patrick. “Methods 101: What is Machine Learning, and How Does it Work?” Youtube, uploaded by Pew Research Center, 4 June 2020, Methods 101: What is machine learning, and how does it work? - YouTube.
This source was conducted by a Senior Data Scientist at Pew Research Center. This source provides information on machine learning, a computational tool that aids the analysis of data. It displays the potential benefits and pitfalls that computational technology can create.
ACADEMIC SEARCH COMPLETE DATABASE:
Zarghani, Maryam, et al. “Iranian Researchers’ Perspective About Concept and Effect of Open Science on Research Publication.” BMC Health Serv Res, vol. 23, no. 1, 2023, pp. 437–437, https://doi.org/10.1186/s12913-023-09420-9.
This source was conducted by researchers from the Department of Medical Library and Information Sciences at Iran University of Medical Sciences. This source provides insight on the effects and implications of the digitization and spread of scientific findings.
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