Editorial for IEEE access special section on theoretical foundations for big data applications : challenges and opportunities Yu, Shui, Wang, Chonggang, Liu, Ke and Zomaya, Albert Y 2016, Editorial for IEEE access special section on theoretical foundations for big data applications : challenges and opportunities, IEEE access, vol. 4, pp. 5730-5732, doi: 10.1109/ACCESS.2016.2605338. Attached Files Name Description MIMEType Size Downloads shui-editorialforieee-2016.pdf Published version application/pdf 1.82MB 156 Title Editorial for IEEE access special section on theoretical foundations for big data applications : challenges and opportunities Author(s) Yu, Shui orcid.org/0000-0003-4485-6743 Wang, Chonggang Liu, Ke Zomaya, Albert Y Journal name IEEE access Volume number 4 Start page 5730 End page 5732 Total pages 3 Publisher Institute of Electrical and Electronics Engineers Place of publication Piscataway, N.J. Publication date 2016 ISSN 2169-3536 Keyword(s) Science & Technology Technology Computer Science, Information Systems Engineering, Electrical & Electronic Telecommunications Computer Science Engineering Summary Big data is one of the hottest research topics in science and technology communities, and it possesses a great application potential in every sector for our society, such as climate, economy, health, social science, and so on. Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, and manage. We can conclude that big data is still in its infancy stage, and we will face many unprecedented problems and challenges along the way of this unfolding chapter of human history. Notes Included in Special Section in IEEE Access: Theoretical Foundations for Big Data Applications: Challenges and Opportunities Language eng DOI 10.1109/ACCESS.2016.2605338 Field of Research 080109 Pattern Recognition and Data Mining Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category C4 Letter or note ERA Research output type C Journal article Copyright notice ©2016, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30089900 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Thu, 01 Dec 2016, 17:41:34 EST Fri, 02 Dec 2016, 04:02:00 EST Fri, 02 Dec 2016, 05:06:54 EST Wed, 07 Dec 2016, 13:21:04 EST Wed, 07 Dec 2016, 13:23:45 EST Wed, 07 Dec 2016, 13:25:42 EST Mon, 03 Apr 2017, 11:56:53 EST Fri, 16 Jun 2017, 11:15:53 EST Fri, 07 Sep 2018, 12:36:59 EST Filtered Full Citation counts:   Cited 1 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 141 Abstract Views, 158 File Downloads  -  Detailed Statistics Created: Thu, 01 Dec 2016, 17:41:34 EST

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