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Journal articles on the topic 'Emerging Data'

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Published: 10 December 2022
Last updated: 28 January 2023

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1

Spath, Jeff. "Emerging Frontiers: Big Data!" Journal of Petroleum Technology 66, no. 01 (January 1, 2014): 14–16. http://dx.doi.org/10.2118/0114-0014-jpt.

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2

Chung-Sheng Li and Y. Ofek. "Emerging Data Communication Standards." IEEE Communications Magazine 34, no. 8 (August 1996): 36. http://dx.doi.org/10.1109/mcom.1996.533917.

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3

Forster, Kenneth, and Michael Masson. "Introduction: Emerging data analysis." Journal of Memory and Language 59, no. 4 (November 2008): 387–88. http://dx.doi.org/10.1016/j.jml.2008.08.005.

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4

Galpin, Ixent. "Data science: an emerging discipline." CITAS 2, no. 1 (July 1, 2016): 39–46. http://dx.doi.org/10.15332/24224529.5178.

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The role of data scientist has been described as the “sexiest job of the 21st Century”. While possibly there is a degree of hype associated with such a claim, there are factors at play such as the unprecedented growth in the amount of data being generated. This paper characterises the already established disciplines which underpin data science, viz., data engineering, statistics, and data mining. Following a characterisation of the previous fields, data science is found to be most closely related to data mining. However, in contrast to data mining, data science promises to operate over datasets that exhibit significant challenges in terms of the four Vs: Volume, Variety, Velocity and Veracity. This paper notes that the current emphasis, both in industry and academia, is on the first three Vs, which pose mainly scientific or technological challenges, rather than Veracity, which is a truly scientific (and arguably a more complex) challenge. Data Science can be seen to have a more ambitious objective than what traditionally data mining has: as a science, data science aims to lead to the creation of new theories and knowledge. This paper notes that, ironically, the veracity dimension, which is arguably the closest one relating to this objective, is being neglected. Despite the current media frenzy about data science, the paper concludes that more time is needed to see whether it will emerge as discipline in its own right.
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5

Nandhini, P. "Emerging Technologies in Big Data." International Journal for Research in Applied Science and Engineering Technology 6, no. 6 (June 30, 2018): 2114–31. http://dx.doi.org/10.22214/ijraset.2018.6313.

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6

Raloff, J., and J. Silberner. "Chernobyl: Emerging Data on Accident." Science News 129, no. 19 (May 10, 1986): 292. http://dx.doi.org/10.2307/3970668.

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7

Vakali, A., B. Catania, and A. Maddalena. "XML data stores: emerging practices." IEEE Internet Computing 9, no. 2 (March 2005): 62–69. http://dx.doi.org/10.1109/mic.2005.48.

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8

TUCKER, MIRIAM E. "Emerging Data Support Switching Biologics." Skin & Allergy News 43, no. 2 (February 2012): 1–9. http://dx.doi.org/10.1016/s0037-6337(12)70034-7.

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9

Clifton, Chris, and Bhavani Thuraisingham. "Emerging standards for data mining." Computer Standards & Interfaces 23, no. 3 (July 2001): 187–93. http://dx.doi.org/10.1016/s0920-5489(01)00072-1.

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10

Kundu, Shakti, and M. L. "Emerging Role of Data Scientist in Big Data." International Journal of Computer Applications 123, no. 3 (August 18, 2015): 15–18. http://dx.doi.org/10.5120/ijca2015905258.

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11

Hendler, Jim. "Broad Data: Exploring the Emerging Web of Data." Big Data 1, no. 1 (March 2013): 18–20. http://dx.doi.org/10.1089/big.2013.1506.

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12

Pink, Sarah, Minna Ruckenstein, Robert Willim, and Melisa Duque. "Broken data: Conceptualising data in an emerging world." Big Data & Society 5, no. 1 (January 2018): 205395171775322. http://dx.doi.org/10.1177/2053951717753228.

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In this article, we introduce and demonstrate the concept-metaphor of broken data. In doing so, we advance critical discussions of digital data by accounting for how data might be in processes of decay, making, repair, re-making and growth, which are inextricable from the ongoing forms of creativity that stem from everyday contingencies and improvisatory human activity. We build and demonstrate our argument through three examples drawn from mundane everyday activity: the incompleteness, inaccuracy and dispersed nature of personal self-tracking data; the data cleaning and repair processes of Big Data analysis and how data can turn into noise and vice versa when they are transduced into sound within practices of music production and sound art. This, we argue is a necessary step for considering the meaning and implications of data as it is increasingly mobilised in ways that impact society and our everyday worlds.
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13

Oh, Tae-Jin, and Anthony. "New and Fast Emerging Advance Structure of Text Mining from Unstructured Data." Bonfring International Journal of Industrial Engineering and Management Science 7, no. 2 (May 30, 2017): 13–16. http://dx.doi.org/10.9756/bijiems.8325.

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14

Amankwah-Amoah, Joseph. "Emerging economies, emerging challenges: Mobilising and capturing value from big data." Technological Forecasting and Social Change 110 (September 2016): 167–74. http://dx.doi.org/10.1016/j.techfore.2015.10.022.

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15

Bach, Benjamin, Nathalie Henry Riche, Sheelagh Carpendale, and Hanspeter Pfister. "The Emerging Genre of Data Comics." IEEE Computer Graphics and Applications 37, no. 3 (May 2017): 6–13. http://dx.doi.org/10.1109/mcg.2017.33.

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16

Watson, Jane, and Ben Kelly. "Emerging Concepts in Chance and Data." Australasian Journal of Early Childhood 27, no. 4 (December 2002): 24–28. http://dx.doi.org/10.1177/183693910202700406.

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Interviews with seven six-year-old children shed light on the emerging ideas related to four themes within the chance and data part of the mathematics curriculum: appreciation of uncertainty and variation, observing and creating representations, appreciating the need to count and conserve quantity, and using data for interpreting and predicting.
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17

Ozdal, Muhammet Mustafa. "Emerging Accelerator Platforms for Data Centers." IEEE Design & Test 35, no. 1 (February 2018): 47–54. http://dx.doi.org/10.1109/mdat.2017.2779742.

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18

Tanzi, Maria G. "Emerging safety data for rheumatic drugs." Pharmacy Today 18, no. 4 (April 2012): 41–44. http://dx.doi.org/10.1016/s1042-0991(15)31882-x.

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19

BRUNK, DOUG. "Emerging Data Link Psoriasis to Comorbidities." Skin & Allergy News 39, no. 9 (September 2008): 8. http://dx.doi.org/10.1016/s0037-6337(08)70646-6.

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20

BRUNK, DOUG. "Emerging Data Link Psoriasis to Comorbidities." Family Practice News 38, no. 17 (September 2008): 27. http://dx.doi.org/10.1016/s0300-7073(08)71101-0.

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21

Han, Jiawei, Russ B. Altman, Vipin Kumar, Heikki Mannila, and Daryl Pregibon. "Emerging scientific applications in data mining." Communications of the ACM 45, no. 8 (August 2002): 54–58. http://dx.doi.org/10.1145/545151.545179.

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22

Bizer, C. "The Emerging Web of Linked Data." IEEE Intelligent Systems 24, no. 5 (September 2009): 87–92. http://dx.doi.org/10.1109/mis.2009.102.

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23

O'Leary, Daniel E. "Big Data and Privacy: Emerging Issues." IEEE Intelligent Systems 30, no. 6 (November 2015): 92–96. http://dx.doi.org/10.1109/mis.2015.110.

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24

Wright, Suzanne M., Carolien Dikkers, and Louis J. Aronne. "Rimonabant: New data and emerging experience." Current Atherosclerosis Reports 10, no. 1 (January 2008): 71–78. http://dx.doi.org/10.1007/s11883-008-0011-5.

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25

Palmer, Carole L., Cheryl A. Thompson, Carol Tenopir, Suzie Allard, Matthew S. Mayernik, and James Jim Kreft. "Responding to emerging data workforce demand: Harnessing data center expertise." Proceedings of the American Society for Information Science and Technology 51, no. 1 (2014): 1–3. http://dx.doi.org/10.1002/meet.2014.14505101026.

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26

Hostiuc, Sorin. "Management of Medical Data in Emerging Threats." Studia Universitatis Babeş-Bolyai Bioethica 66, Special Issue (September 9, 2021): 92. http://dx.doi.org/10.24193/subbbioethica.2021.spiss.57.

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"Emerging viral or bacterial threats pose significant medical and ethical issues, caused not only by the management of the disease, but also by the uncontrolled dissemination of information, both true and fake. Even the most correct and impartially presented piece of information can be understood by the patients or by the public at large in ways that are opposite to those intended by the communicators. This, associated with the increased prevalence of fake news, may cause havoc and decrease the efficacy of the needed preventive measures that have to be taken to tackle the actual medical problem. Within the context of the coronavirus outbreak, this has been coined as “infodemic”, increasing the difficulty of finding an optimal solution to the actual problem. Medical data about an emerging medical threat is disseminated through mass – and social media, especially by public authorities and physicians. The latter have specific duties, appertaining to their professional codes of morals, toward minimizing the harms generated by diseases, both at a personal and at a populational level. In infodemics, the management of the information they present to the public is extremely important, as each wording can be improperly interpreted and cause opposite effects. In this paper, we will discuss whether and which healthcare professionals should be involved in disseminating information about emerging healthcare threats, and which moral duties should prevail in these instances. "
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27

Singh, Nitin. "Emerging Trends in Technologies for Big Data." International Technology Management Review 5, no. 4 (2015): 202. http://dx.doi.org/10.2991/itmr.2015.5.4.4.

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28

Gul, Sumeer, Shohar Bano, and Taseen Shah. "Exploring data mining: facets and emerging trends." Digital Library Perspectives 37, no. 4 (October 20, 2021): 429–48. http://dx.doi.org/10.1108/dlp-08-2020-0078.

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Purpose Data mining along with its varied technologies like numerical mining, textual mining, multimedia mining, web mining, sentiment analysis and big data mining proves itself as an emerging field and manifests itself in the form of different techniques such as information mining; big data mining; big data mining and Internet of Things (IoT); and educational data mining. This paper aims to discuss how these technologies and techniques are used to derive information and, eventually, knowledge from data. Design/methodology/approach An extensive review of literature on data mining and its allied techniques was carried to ascertain the emerging procedures and techniques in the domain of data mining. Clarivate Analytic’s Web of Science and Sciverse Scopus were explored to discover the extent of literature published on Data Mining and its varied facets. Literature was searched against various keywords such as data mining; information mining; big data; big data and IoT; and educational data mining. Further, the works citing the literature on data mining were also explored to visualize a broad gamut of emerging techniques about this growing field. Findings The study validates that knowledge discovery in databases has rendered data mining as an emerging field; the data present in these databases paves the way for data mining techniques and analytics. This paper provides a unique view about the usage of data, and logical patterns derived from it, how new procedures, algorithms and mining techniques are being continuously upgraded for their multipurpose use for the betterment of human life and experiences. Practical implications The paper highlights different aspects of data mining, its different technological approaches, and how these emerging data technologies are used to derive logical insights from data and make data more meaningful. Originality/value The paper tries to highlight the current trends and facets of data mining.
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29

Muheidat, Fadi, Dhaval Patel, Spandana Tammisetty, Lo’ai A. Tawalbeh, and Mais Tawalbeh. "Emerging Concepts Using Blockchain and Big Data." Procedia Computer Science 198 (2022): 15–22. http://dx.doi.org/10.1016/j.procs.2021.12.206.

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30

Lin, Yi-Tang. "Data and Databases: Emerging Objects of Research." East Asian Science, Technology and Society: An International Journal 15, no. 3 (July 3, 2021): 395–401. http://dx.doi.org/10.1080/18752160.2021.1969626.

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31

Hawi, Nazir. "Learning Programming: A Model Emerging from Data." International Journal of Computer Applications 100, no. 4 (August 20, 2014): 24–34. http://dx.doi.org/10.5120/17514-8070.

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32

Man, Ka, and Kevin Lee. "Emerging Approaches and Advances in Big Data." Symmetry 11, no. 2 (February 13, 2019): 213. http://dx.doi.org/10.3390/sym11020213.

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33

Mahlstein, Irina, Gabriele Hegerl, and Susan Solomon. "Emerging local warming signals in observational data." Geophysical Research Letters 39, no. 21 (November 2012): n/a. http://dx.doi.org/10.1029/2012gl053952.

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34

Sivera, Piera. "EMERGING DATA FOR CANCER ASSOCIATED THROMBOSIS TREATMENT." Hematology, Transfusion and Cell Therapy 44 (October 2022): S6. http://dx.doi.org/10.1016/j.htct.2022.09.1194.

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35

Quach, Tu-Thach, Sapan Agarwal, Conrad D. James, Matthew J. Marinella, and James B. Aimone. "Sparse Data Acquisition on Emerging Memory Architectures." IEEE Access 7 (2019): 1685–93. http://dx.doi.org/10.1109/access.2018.2886931.

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36

Kant, K., and L. Ong. "Signaling in emerging telecommunications and data networks." Proceedings of the IEEE 85, no. 10 (1997): 1612–21. http://dx.doi.org/10.1109/5.640769.

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37

Knowles, Bran. "Emerging Trust Implications of Data-Rich Systems." IEEE Pervasive Computing 15, no. 4 (October 2016): 76–84. http://dx.doi.org/10.1109/mprv.2016.68.

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38

COHEN, LEE. "Emerging Data on Prenatal Exposure to SSRIs." Internal Medicine News 40, no. 2 (January 2007): 18. http://dx.doi.org/10.1016/s1097-8690(07)70023-9.

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39

Schneider, Paula J., and Campbell Gibson. "Emerging data needs for the 21st century." Government Publications Review 18, no. 3 (May 1991): 275–84. http://dx.doi.org/10.1016/0277-9390(91)90006-j.

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40

MCNAMARA, DAMIAN. "Bipolar Depression Data Emerging From STEP-BD." Clinical Psychiatry News 34, no. 5 (May 2006): 28. http://dx.doi.org/10.1016/s0270-6644(06)71419-9.

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41

Vanecek, G., N. Mihai, N. Vidovic, and D. Vrsalovic. "Enabling hybrid services in emerging data networks." IEEE Communications Magazine 37, no. 7 (July 1999): 102–9. http://dx.doi.org/10.1109/35.774888.

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42

Prakash, Deepika, and Daya Gupta. "Data warehouse requirements engineering: an emerging discipline." International Journal of Business Information Systems 23, no. 2 (2016): 194. http://dx.doi.org/10.1504/ijbis.2016.078906.

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43

Gupta, Daya, and Deepika Prakash. "Data warehouse requirements engineering: an emerging discipline." International Journal of Business Information Systems 23, no. 2 (2016): 194. http://dx.doi.org/10.1504/ijbis.2016.10000219.

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44

Findlay, Kyle. "Six steps to leveraging emerging data source." Research World 2018, no. 70 (May 2018): 48–51. http://dx.doi.org/10.1002/rwm3.20671.

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45

Gilmore-Bykovskyi, Andrea, and Basil Eldadah. "LUCIDITY IN DEMENTIA: EMERGING CONCEPTS AND DATA." Innovation in Aging 6, Supplement_1 (November 1, 2022): 88. http://dx.doi.org/10.1093/geroni/igac059.350.

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Abstract Episodes of lucidity among people with advanced Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD), reportedly evidenced by an unexpected return of meaningful communication or connection, are an area of growing interest. Event transient recovery of abilities in the setting of advanced AD/ADRD are potentially significant for caregivers and the person living with dementia; as well as for shaping our understanding of AD/ADRD more broadly. Despite the potential significance of these events, existing evidence is largely comprised of anecdotal reports and retrospective/case reports. Recently, the National Institute on Aging funded six studies to advance empiric studies on episodes of lucidity in advanced AD/ADRD. This symposium will provide an update on progress and findings across these funded studies. The first presentation focuses on acceptability and feasibility of a prospective observation study focused on characterizing potential observable indicators of episodes of lucidity in individuals with advanced AD/ADRD near end of life encompassing audiovisual observation, informant field interviews and case reviews. The second presentation will provide an overview of a 3-phase mixed methods study focused on development of preliminary types of lucid episodes. Collectively, presentations demonstrate a variety of approaches to investigating episodes of lucidity and shed light on emergent methods for operationalizing these events. Implications of various conceptualizations for EL and conceptual decisions across studies will be reviewed.
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46

Hamilton, Ian, Charlie Lloyd, Mark Monaghan, and Kirsteen Paton. "The emerging cannabis treatment population." Drugs and Alcohol Today 14, no. 3 (August 26, 2014): 150–53. http://dx.doi.org/10.1108/dat-01-2014-0005.

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Purpose – The purpose of this paper is to examine recent trends in presentation to treatment where cannabis is identified as the primary drug. Design/methodology/approach – Data is drawn from the recently published Public Health England report and supplemented with Home Office and European data. Findings – The data shows a marked increase in presentations for cannabis treatment over recent years. The authors offer some potential explanations for this trend. Research limitations/implications – The authors need to improve our understanding of the type of cannabis that is available and how specifically it is used. In parallel there is a pressing need for an evaluation of evidence in relation to treatment for problematic cannabis users. Originality/value – This paper highlights this recent trend in treatment presentations, offers some potential explanations and makes associated recommendations.
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47

Chahal, Mandeep S., and Jun Wang. "Jump Diffusion Processes and Emerging Bond and Stock Markets: An Investigation Using Daily Data." Multinational Finance Journal 1, no. 3 (September 1, 1997): 169–97. http://dx.doi.org/10.17578/1-3-1.

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48

Maffei, Stefano, Francesco Leoni, and Beatrice Villari. "Data-driven anticipatory governance. Emerging scenarios in data for policy practices." Policy Design and Practice 3, no. 2 (April 2, 2020): 123–34. http://dx.doi.org/10.1080/25741292.2020.1763896.

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49

D'yakovich, Marina. "EMERGING ADULTHOOD: REPRODUCTIVE HEALTH ANDREPRODUCTIVEATTITUDES." Bulletin of the Angarsk State Technical University 1, no. 15 (January 12, 2022): 186–90. http://dx.doi.org/10.36629/2686-777x-2021-1-15-186-190.

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The objective assessments of the reproductive health of students of both sexes, enrolled in the bachelor's training program, belonging to the group «emerging adulthood», obtained from the results of medical examinations, are considered. The data on reproductive behavior and reproductive attitudes of students, obtained in the course of a pilot sociological study, are analyzed. A comparison is made with the available literature data, and further in-depth studies are substantiated
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50

Mei Li, Paul YANNE, and Yang Zhang. "Uncertain Essential Emerging Patterns for Classifying Uncertain Data." Journal of Convergence Information Technology 8, no. 3 (February 15, 2013): 773–82. http://dx.doi.org/10.4156/jcit.vol8.issue3.91.

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