Cite

1. Al Nuaimi, E., Al Neyadi, H., Mohamed, N., Al-Jaroodi, J. (2015), “Applications of big data to smart cities”, Journal of Internet Services and Applications, Vol. 6 No. 1, pp. 25. Search in Google Scholar

2. Al-Mallah, M. H., Keteyian, S. J., Brawner, C. A., Whelton, S., Blaha, M. J. Rationale (2014), “Design of the Henry Ford ExercIse Testing Project (The FIT Project)”, Clinical Cardiology, Vol. 37 No. 8, pp. 456-461.10.1002/clc.22302 Search in Google Scholar

3. Borne, K. (2021), “Top 10 List – The V’s of Big Data. Data Science Central – a Community for big data practitioners”, available at https://www.datasciencecentral.com/profiles/blogs/top-10-list-the-v-s-of-big-data (8 March 2021) Search in Google Scholar

4. Che, D., Safran, M., Peng, Z. (2013), “From big data to big data mining: challenges, issue, and opportunities”, Database Systems for Advanced Applications, Vol. 19 No. 2, pp. 1-15.10.1007/978-3-642-40270-8_1 Search in Google Scholar

5. Chen, M., Mao, S., Liu, Y. (2014), “Big data: A survey”, Mobile Networks and Application, Vol. 19 No. 2, pp. 171-209.10.1007/s11036-013-0489-0 Search in Google Scholar

6. Cheng, Y., Song, Y. (2021) “Sports big data analysis based on cloud platform and its impact on sports economy”, Mathematical Problems in Engineering, Vol. 21 No. 2, pp. 1-12.10.1155/2021/6610000 Search in Google Scholar

7. De Mauro, A., Greco, M., Grimaldi, M. (2015), “What is big data? A consensual definition and a review of key research topics”, AIP Conference Proceedings, Vol. 1644 No. 1, pp. 97-104.10.1063/1.4907823 Search in Google Scholar

8. De Mauro, A., Greco, M., Grimaldi, M. (2016), “A formal definition of big data based on its essential features”, Library Review, Vol. 63 No. 1, pp. 122-135.10.1108/LR-06-2015-0061 Search in Google Scholar

9. Dijcks, J. (2012), “Oracle: Big data for the enterprise”, Redwood Shores, USA, pp. 1–16. Search in Google Scholar

10. Emig, T., Peltonen, J. (2020), “Human running performance from real-world big data”, Nature communications, Vol. 11 No. 1, pp. 4936-4945.10.1038/s41467-020-18737-6 Search in Google Scholar

11. Favaretto, M., De Clercq, E., Schneble, C. O., Elger, B. S., Fischer, F. (2020), “What is your definition of Big Data? Researcher’s understanding of the phenomenon of the decade”, PLoS One, Vol. 15 No. 2, pp. 1-20.10.1371/journal.pone.0228987 Search in Google Scholar

12. Goel, R., Garcia, L. M. T., Goodman, A., Johnson, R., Aldred, R., Murugesan, M., Brage, S., Bhalla, K., Srinivasan, M. (2018), “Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain”, PLoS One, Vol. 13 No. 5, pp. 1-22.10.1371/journal.pone.0196521 Search in Google Scholar

13. Hayano, J., Kisohara, M., Yoshida, Y., Sakano, H., Yuda, E. (2019), “Association of heart rate variability with regional difference in senility death ratio: ALLSTAR big data analysis”, SAGE Open Medicine, Vol. 7 No. 2, pp. 1-7.10.1177/2050312119852259 Search in Google Scholar

14. Hou, X., Jiang, J. (2017), “Analysis on the mental quality and performance of table tennis players based on the cloud computing big data”, Technical Bulletin, Vol. 55 No. 1, pp. 348-354. Search in Google Scholar

15. Kaur, G., Jagdev, G. (2020), “Analyzing and Exploring the Impact of Big Data Analytics in Sports Science”, in Indo - Taiwan 2nd International Conference on Computing, Analytics and Networks, Indo-Taiwan ICAN, pp. 218-224.10.1109/Indo-TaiwanICAN48429.2020.9181320 Search in Google Scholar

16. Khan, N., Yaqoob, I., Targio Hashem, I. A., Inayat, Z., Mahmud Ali, W. K., Alam, M., Shiraz, M., Gani, A. (2014), “Big Data: Survey, Technologies, Opportunities, and challenges”, The Scientific World Journal, Vol. 2014 No. 2, pp. 1-18.10.1155/2014/712826 Search in Google Scholar

17. Kharabian Masouleh, S., Beyer, F., Lampe, L., Loeffler, M., Luck, T., Riedel-Heller, S., Schroeter, M. L., Stumvoll, M., Villringer, A., Witte, A. V. (2018), “Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults”, Journal of Cerebral Blood Flow & Metabolism, Vol. 38 No. 2, pp. 360-372.10.1177/0271678X17729111 Search in Google Scholar

18. Khazaeli, M., El Kari, C. (2016), “The effects of technology and big data in sports industry”, in Proceedings of the 2016 Industrial and Systems Engineering Research Conference, ISERC 2016-2020, pp. 2404-2409. Search in Google Scholar

19. Kim, S. W., Lee, K., Sohn, J. S., Cha, S. W. (2020), “Product development using online customer reviews: A case study of the South Korean subcompact sport utility vehicles market”, Applied Sciences, Vol. 10 No. 19, pp. 1-12.10.3390/app10196918 Search in Google Scholar

20. Kokkotis, C., Moustakidis, S., Giakas, G., Tsaopoulos, D. (2020), “Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients”, Applied Sciences, Vol. 10 No. 19, pp. 1-23.10.3390/app10196797 Search in Google Scholar

21. Laney, D. (2012), “3D Data Management: Controlling Data Volume, Velocity and Variety”, available at http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf (15 March 2021) Search in Google Scholar

22. Li, J., Deng, K., Huanh, X., Xu, J. (2019), “Analysis and application of location-aware big complex network data”, Complexity, Vol. 2019 No. 1, pp. 1-2.10.1155/2019/3410262 Search in Google Scholar

23. Liu, G., Luo, Y., Schulte, O., Kharrat, T. (2020), “Deep soccer analytics: learning an action-value function for evaluating soccer players”, Data Mining and Knowledge Discovery, Vol. 34 No. 2, pp. 1531-1559.10.1007/s10618-020-00705-9 Search in Google Scholar

24. Liu, H. (2019), “Opportunities, challenges and Countermeasures for the development of China’s sports industry in the era of big data”, Journal of Physic: Conference Series, Vol. 1237 No. 2, pp. 1-14.10.1088/1742-6596/1237/2/022012 Search in Google Scholar

25. Marker, A. M., Steele, R. G., Noser, A. E. (2017), “Physical activity and health-related quality of life in children and adolescents: A systematic review and meta-analysis”, Health Psychology, Vol. 37 No. 1, pp. 893-903. Search in Google Scholar

26. Matheson, G. O., Klügl, M., Engebretsen, L., Bendiksen, F., Blair, S. N., Börjesson, M., Budgett, R., Derman, W., Erdener, U., Ioannidis, J. P. A., Khan, K. M., Martinez, R., van Mechelen, W., Mountjoy, M., Sallis, R. E., Schwellnus, M., Shultz, R., Soligard, T., Steffen, K., Sundberg, C. J., Weiler, R., Ljungqvist, A. (2013), “Prevention and Management of Noncommunicable Disease”, Clinical Journal of Sport Medicine, Vol. 23 No. 2, pp. 419-429.10.1097/JSM.0000000000000038 Search in Google Scholar

27. Mobertz, L. (2019), “The Four V” s of Big Data”, available at https://www.bigdataframework.org/four-vs-of-big-data/ (24 March 2021) Search in Google Scholar

28. Morgulev, E., Azar, O. H., Lidor, R. (2018), “Sports analytics and the big-data era”, International Journal of Data Science and Analitics, Vol. 5 No. 4, pp. 156-159.10.1007/s41060-017-0093-7 Search in Google Scholar

29. Nguyen Quynh C., Brunisholz, K. D., Yu, W., McCullough, M., Hanson, H., Litchman, M. L., Li, F., Wan, Y., VanDerslice, J. A., Wen, M., Smith, K. R. (2017), “Twitter-derived neighborhood characteristics associated with obesity and diabetes˝, Scientific Report, Vol. 7 No. 1, pp. 1-10. Search in Google Scholar

30. Oguntimilehin A., Ademola E. O. (2014), “A Review of Big Data Management, Benefits and Challenges”, A Review of Big Data Management, Benefits and Challenges, Vol. 5 No. 6, pp. 433-438. Search in Google Scholar

31. Owais, S. S., Hussein, N. S. (2016), “Extract Five Categories CPIVW from the 9V “s Characteristics of the Big Data”, International Journal of Advanced Computer Science and Applications, Vol. 7 No. 3, pp. 254-258. Search in Google Scholar

32. Pappalardo, L., Cintia, P., Rossi, A., Massucco, E. (2019), “A public data set of spatio-temporal match events in soccer competitions”, Scientific Data, Vol. 6 No. 1, pp. 1-15.10.1038/s41597-019-0247-7 Search in Google Scholar

33. Park, S. U., Ahn, H., Dong, K., So, W. (2020), “Big Data Analysis of Sports and Physical Activities among Korean Adolescents”, International Journal of Environmental Research and Public Health, Vol. 17 No. 15, pp. 5577-5589.10.3390/ijerph17155577 Search in Google Scholar

34. Patel, D., Shah, D., Shah, M. (2020), “The intertwine of brain and body: a quantitative analysis on how big data influences the system of sports”, Annals of Data Science, Vol. 7 No. 1, pp. 1-16.10.1007/s40745-019-00239-y Search in Google Scholar

35. Phan, L., Yu, W., Keralis, J. M., Mukhija, K., Dwivedi, P., Brunisholz, K. D., Javanmardi, M., Tasdizen, T., Nguyen, Q. C. (2020), “Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States”, International Journal of Environmental Research and Public Health, Vol. 17 No. 10, pp. 3659-3669.10.3390/ijerph17103659 Search in Google Scholar

36. Rajeshwari Sreenivasan, R. (2017), “Characteristics of Big Data – A Delphi study”, Newfoundland, Faculty of Business Administration Memorial University of Newfoundland, pp. 13-34. Search in Google Scholar

37. Raywood, E., Douglas, H., Kapoor, K., Filipow, N., Murray, N., O’Connor, R., Stott, L., Saul, G., Kuzhagaliyev, T., Davies, G., Liakhovich, O., Van Schaik, T., Furtuna, B., Booth, J., Shannon, H., Bryon, M., Main, E. (2020), “Protocol for Project Fizzyo, an analytic longitudinal observational cohort study of physiotherapy for children and young people with cystic fibrosis, with interrupted time-series design”, BMJ Open, Vol. 10 No. 10, pp. 1-10.10.1136/bmjopen-2020-039587 Search in Google Scholar

38. Saez, Y., Baldominos, A., Isasi, P. (2016), “A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition”, Sensors, Vol. 17 No. 1, pp. 66-92.10.3390/s17010066 Search in Google Scholar

39. Sagiroglu, S., Sinanc, D. (2013), “Big data: a review”, in Proceedings of the International Conference on Collaboration Technologies and Systems (CTS ‘13), San Diego, California, USA, pp. 42-47.10.1109/CTS.2013.6567202 Search in Google Scholar

40. Schroeck, M., Schockley, R., Smart, J., Morales D. R. (2012), “Analytics: the real-world use of big data: how innovative enterprises extract value from uncertain data”, executive report, IBM Institute for Business Value and Said Business School at the University of Oxford, Somers, USA. Search in Google Scholar

41. Singh, J., Singla, V. (2015), “Big Data: Tools and Technologies in Big Data”, International Journal of Computer Application, Vol. 112 No. 15, pp. 6-10. Search in Google Scholar

42. Snedden, T. R., Scerpella, J., Kliethermes, S. A., Norman, R. S., Blyholder, L., Sanfilippo, J., McGuine, T. A., Heiderscheit, B. (2019), “Sport and Physical Activity Level Impacts Health-Related Quality of Life Among Collegiate Students”, American Journal of Health Promotion, Vol. 33 No. 5, pp. 675-682.10.1177/0890117118817715 Search in Google Scholar

43. Sung-Un, P., Hyunkyun, A., Dong-Kyu, D., Wi-Young, S. (2020), “Big Data Analysis of Sports and Physical Activities among Korean Adolescents”, International Journal of Environmental Research and Public Health, Vol. 17 No. 15, pp. 5577-5588.10.3390/ijerph17155577 Search in Google Scholar

44. Suthaharan, S. (2013), “Big Data Classification: Problems and challenges in network intrusion prediction with machine learning”, ACM Sigmetrics, Vol. 41 No. 4, pp. 70-73.10.1145/2627534.2627557 Search in Google Scholar

45. Wang, S., Scheider, S., Sporrel, K., Deutekom, M., Timmer, J., Krose, B. (2021), “What are good sitiations for running? A machine learning study using mobile and geographical data”, Frontiers in Public Health, Vol. 8, pp. 1-15. Search in Google Scholar

46. Worldometer (2021), “Current world population”, available at: https://www.worldometers.info/world-population/ (6 March 2021) Search in Google Scholar

47. Wu, X. Y., Han, L. H., Zhang, J. H., Luo, S., Hu, J. W., Sun, K. (2017), “The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review”, PLoS One, Vol. 12 No. 11, pp. 1-29.10.1371/journal.pone.0187668 Search in Google Scholar

48. Zhao, D., Wei, L., Wang, Z., Du., Y. (2015), “Modeling and analysis in marine big data: advandes and challenges”, Mathematical Problems in Engineering, Vol. 15 No. 2, pp. 1-15. Search in Google Scholar

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