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Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.
Huang, Xiuzhen; Jennings, Steven F; Bruce, Barry; Buchan, Alison; Cai, Liming; Chen, Pengyin; Cramer, Carole L; Guan, Weihua; Hilgert, Uwe Kk; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Donald F; Nanduri, Bindu; Perkins, Andy; Rekepalli, Bhanu; Salem, Saeed; Specker, Jennifer; Walker, Karl; Wunsch, Donald; Xiong, Donghai; Zhang, Shuzhong; Zhang, Yu; Zhao, Zhongming; Moore, Jason H.
Afiliação
  • Huang X; Department of Computer Science, Arkansas State University, Jonesboro, AR 72467 USA.
  • Jennings SF; Sector3 Informatics, Marana, AZ 85658 USA.
  • Bruce B; Sustainable Energy & Education Research Center, University of Tennessee at Knoxville, Knoxville, TN 37996 USA.
  • Buchan A; Department of Microbiology, University of Tennessee, Knoxville, TN 37996 USA.
  • Cai L; Department of Computer Science, University of Georgia, Athens, GA 30602 USA.
  • Chen P; Crop, Soil, and Environmental Sciences, University of Arkansas at Fayetteville, Fayetteville, AR 72701 USA.
  • Cramer CL; Arkansas Biosciences Institute, Department of Biological Sciences, Arkansas State University, Jonesboro, AR 72467 USA.
  • Guan W; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455 USA.
  • Hilgert UK; BIO5 Institute & iPlant Collaborative, The University of Arizona, PO Box 210240, Tucson, AZ 85721 USA.
  • Jiang H; Department of Statistics, Northwestern University, Evanston, IL 60208 USA.
  • Li Z; Center for Applied Genetic Technologies, The University of Georgia, Athens, GA 30602 USA.
  • McClure G; Arkansas Science & Technology Authority, Arkansas NSF EPSCoR, Little Rock, AR 72201 USA.
  • McMullen DF; Arkansas High Performance Computing Center, University of Arkansas at Fayetteville, Fayetteville, AR 72701 USA.
  • Nanduri B; Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Jackson, MS 39762 USA.
  • Perkins A; Department of Computer Science and Engineering, Mississippi State University, Jackson, MS 39762 USA.
  • Rekepalli B; National Institute for Computational Sciences, Department of Electrical Engineering and Computer Science, UTK and ORNL, Oak Ridge, TN 37832 USA.
  • Salem S; Department of Computer Science, North Dakota State University, Fargo, ND 58102 USA.
  • Specker J; Graduate School of Oceanography, University of Rhode Island, Narragansett, RI 02882 USA.
  • Walker K; Department of Computer Science, University of Arkansas at Pine Bluff, Arkansas, 71601 USA.
  • Wunsch D; Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO 65409 USA.
  • Xiong D; Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee, WI 53223 USA.
  • Zhang S; Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, MN 55455 USA.
  • Zhang Y; Department of Computer Science, Trinity University, San Antonio, TX 78212 USA.
  • Zhao Z; Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37203 USA.
  • Moore JH; Department of Genetics, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756 USA.
BioData Min ; 8: 7, 2015.
Article em En | MEDLINE | ID: mdl-25670967
ABSTRACT
Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article