Rethinking big data: A review on the data quality and usage issues

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 115, Issue , 2016, Pages 134-142

  Liu, Jianzheng ^a   Li, Jie ^a   Li, Weifeng ^a   Wu, Jiansheng ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b PEKING UNIVERSITY   (China)

Author keywords

Big data; Data ethnics; Data quality and error; Spatial information sciences

Indexed keywords

DATA ACQUISITION; DATA HANDLING; ERRORS; INFORMATION SCIENCE; RELIABILITY ANALYSIS;

DATA AVAILABILITY; DATA ETHNICS; DATA QUALITY; EMPIRICAL STUDIES; GOOD SCIENTIFIC PRACTICES; INFORMATION INCOMPLETENESS; RESEARCH DESIGNS; SPATIAL INFORMATION SCIENCE;

BIG DATA;

DATA PROCESSING; DATA QUALITY; EMPIRICAL ANALYSIS; ERROR ANALYSIS; ETHNICITY; INFORMATION MANAGEMENT; NOISE; RESEARCH METHOD;

EID: 84951971627     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2015.11.006     Document Type: Short Survey

References (56)

1. Acquisti A., Gross R. Predicting social security numbers from public data. Proc. Natl. Acad. Sci. 2009, 106:10975-10980.
2. Anderson C. The end of theory: the data deluge makes the scientific method obsolete. Wired Mag. 2008.
3. Bacon-Shone, J., 2014. Human Research Ethics in HKU. <> (accessed 16.12.15). http://www.intraweb.hku.hk/local/rss/RCR/human-research-ethics-hku.pdf.
4. Batty M. Smart cities, big data. Environ. Plan. B - Plan. Des. 2012, 39:191-193. 10.1068/b3902ed.
5. Boyd D., Crawford K. Critical questions for big data provocations for a cultural, technological, and scholarly phenomenon. Inf. Commun. Soc. 2012, 15:662-679. 10.1080/1369118x.2012.678878.
6. Boyd, D., Marwick, A.E., 2011. Social privacy in networked publics: Teens' attitudes, practices, and strategies. In: Proceedings of the a Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. Oxford Internet Institute, pp. 1-29.
7. Cheshire J., Batty M. Visualisation tools for understanding big data. Environ. Plan. B - Plan. Des. 2012, 39:413-415. 10.1068/b3903ed.
8. China Internet Network Information Center, 2014a. Research Report on Social Media User Behaviors 2014. <> (accessed 16.12.15). https://www.cnnic.cn/hlwfzyj/hlwxzbg/sqbg/201408/P020150401351309648557.pdf.
9. China Internet Network Information Center, 2014b. Statistical Report on Internet Development in China. <> (accessed 16.12.15). http://www.cnnic.cn/hlwfzyj/hlwxzbg/hlwtjbg/201403/P020140305346585959798.pdf.
10. Crampton J.W., Graham M., Poorthuis A., Shelton T., Stephens M., Wilson M.W., Zook M. Beyond the geotag: situating 'big data' and leveraging the potential of the geoweb. Cartogr. Geogr. Inf. Sci. 2013, 40:130-139. 10.1080/15230406.2013.777137.
11. de Montjoye Y.-A., Hidalgo C.A., Verleysen M., Blondel V.D. Unique in the crowd: the privacy bounds of human mobility. Sci. Rep. 2013, 3. 10.1038/srep01376.
12. de Montjoye Y.-A., Quoidbach J., Robic F., Pentland A. Predicting personality using novel mobile phone-based metrics. Social Computing, Behavioral-Cultural Modeling and Prediction 2013, 48-55. Springer Berlin Heidelberg. A. Greenberg, W. Kennedy, N. Bos (Eds.).
13. Duggan, M., Brenner, J., 2013. The Demographics of Social Media Users - 2012. <> (accessed 16.12.15). http://www.pewinternet.org/2013/02/14/the-demographics-of-social-media-users-2012/.
14. Einav L., Levin J. Economics in the age of big data. Science 2014, 346:1243089. 10.1126/science.1243089.
15. Fu K.-W., Chau M. Reality check for the Chinese microblog space: a random sampling approach. PLoS ONE 2013, 8:e58356.
16. Gao S., Li L., Li W., Janowicz K., Zhang Y. Constructing gazetteers from volunteered big geo-data based on Hadoop. Comput. Environ. Urban Syst. 2014, 10.1016/j.compenvurbsys.2014.02.004.
17. Gao S., Liu Y., Wang Y., Ma X. Discovering spatial interaction communities from mobile phone data. Trans. GIS 2013, 17:463-481.
18. Gonzalez M.C., Hidalgo C.A., Barabasi A.-L. Understanding individual human mobility patterns. Nature 2008, 453:779-782. 10.1038/nature06958.
19. Graham M., Hale S.A., Gaffney D. Where in the world are you? Geolocation and language identification in Twitter. Prof. Geogr. 2014, 66:568-578.
20. Haklay M. How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environ. Plan. B - Plan. Des. 2010, 37:682-703.
21. Huang W., Li S., Liu X., Ban Y. Predicting human mobility with activity changes. Int. J. Geogr. Inf. Sci. 2015, 29:1-19.
22. IBM, 2013. The Four V's of Big Data. <> (accessed 16.12.15). http://www.ibmbigdatahub.com/infographic/four-vs-big-data.
23. Khoury M.J., Ioannidis J.P.A. Big data meets public health. Science 2014, 346:1054-1055. 10.1126/science.aaa2709.
24. Kohavi R., Longbotham R., Sommerfield D., Henne R.M. Controlled experiments on the web: survey and practical guide. Data Min. Knowl. Disc. 2009, 18:140-181.
25. Krings G., Calabrese F., Ratti C., Blondel V.D. Urban gravity: a model for inter-city telecommunication flows. J. Stat. Mech: Theory Exp. 2009, 2009:L07003.
26. Laney, D., 2001. 3-D Data Management: Controlling Data Volume, Velocity and Variety. <> (accessed 16.12.15). http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf.
27. Lazer D., Pentland A.S., Adamic L., Aral S., Barabasi A.L., Brewer D., Christakis N., Contractor N., Fowler J., Gutmann M. Life in the network: the coming age of computational social science. Science 2009, 323:721.
28. Lazer D.M., Kennedy R., King G., Vespignani A. The parable of Google Flu: traps in big data analysis. Science 2014, 343:1203-1205.
29. Lee R., Wakamiya S., Sumiya K. Urban area characterization based on crowd behavioral lifelogs over Twitter. Pers. Ubiquit. Comput. 2013, 17:605-620. 10.0007/s00779-012-0510-9.
30. Liu X., Long Y. Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest. Environ. Plan. B - Plan. Des. 2015, 1-20. 10.1177/0265813515604767.
31. Liu Y., Kang C., Gao S., Xiao Y., Tian Y. Understanding intra-urban trip patterns from taxi trajectory data. J. Geogr. Syst. 2012, 14:463-483.
32. Long, Y., Liu, X., Zhou, J., Chai, Y., 2015. Early Birds, Night Owls, and Tireless/Recurring Itinerants: An Exploratory Analysis of Extreme Transit Behaviors in Beijing, China. [physics.soc-ph]. arxiv:1502.02056.
33. Long Y., Thill J. Combining smart card data, household travel survey and land use pattern for identifying housing-jobs relationships in Beijing. Comput. Environ. Urban Syst. 2015, 53:19-35. 10.1016/j.compenvurbsys.2015.02.005.
34. Loshin, D., 2012. Data Governance and Quality: Data Reuse vs. Data Repurposing. <> (accessed 06.05.15). http://dataqualitybook.com/?p=349.
35. Mao M., Long Y. Ji yu wei bo shu ju de gui hua quan shi bie chu tan [an exploration into the personal connection of urban planning practitioners using Sina Weibo data]. Annual National Planning Conference 2013 2013, Urban Planning Society of China, Qingdao, China.
36. Mayer-Schönberger, V., Cukier, K., 2013. Big Data: A Revolution that Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.
37. McNulty, E., 2014. Understanding Big Data: The Seven V's <> (accessed 15.12.15). http://dataconomy.com/seven-vs-big-data/.
38. Niu, X., Ding, L., Song, X., 2015. Understanding urban spatial structure of shanghai central city based on mobile phone data. China City Planning Review 3, 004.
39. O'Leary D.E. Artificial intelligence and big data. IEEE Intell. Syst. 2013, 28:96-99.
40. Pei T., Sobolevsky S., Ratti C., Amini A., Zhou C. Uncovering the directional heterogeneity of an aggregated mobile phone network. Trans. GIS 2014, 18:126-142.
41. Pigliucci M. The end of theory in science?. EMBO Rep. 2009, 10. 534-534.
42. Pijanowski B.C., Tayyebi A., Doucette J., Pekin B.K., Braun D., Plourde J. A big data urban growth simulation at a national scale: configuring the GIS and neural network based land transformation model to run in a high performance computing (HPC) environment. Environ. Modell. Softw. 2014, 51:250-268. 10.1016/j.envsoft.2013.09.015.
43. Reades J., Calabrese F., Ratti C. Eigenplaces: analysing cities using the space-time structure of the mobile phone network. Environ. Plan. B - Plan. Des. 2009, 36:824-836.
44. Richardson D.B., Volkow N.D., Kwan M.-P., Kaplan R.M., Goodchild M.F., Croyle R.T. Spatial turn in health research. Science 2013, 339:1390.
45. Robinson W.S. Ecological correlations and the behavior of individuals. Int. J. Epidemiol. 2009, 38:337-341.
46. Roth C., Kang S.M., Batty M., Barthélemy M. Structure of urban movements: polycentric activity and entangled hierarchical flows. PLoS ONE 2011, 6:e15923.
47. Ruths D., Pfeffer J. Social media for large studies of behavior. Science 2014, 346:1063-1064. 10.1126/science.346.6213.1063.
48. Song C., Qu Z., Blumm N., Barabási A.-L. Limits of predictability in human mobility. Science 2010, 327:1018-1021.
49. Soto V., Frías-Martínez E. Automated land use identification using cell-phone records. Proceedings of the 3rd ACM International Workshop on MobiArch 2011, 17-22. ACM.
50. Toole J.L., Ulm M., González M.C., Bauer D. Inferring land use from mobile phone activity. Proceedings of the ACM SIGKDD International Workshop on Urban Computing 2012, 1-8. ACM.
51. Webster, C., 2014. Dean's Roundup (Friday, 31 October, 2014). <> (accessed 06.05.15). http://fac.arch.hku.hk/wp-content/uploads/2014/10/DeansRoundup-20141031.pdf.
52. Wu H.Y., Zhang T., Gong J.Y. Geocomputation for geospatial big data. Trans. GIS 2014, 18:1-2. 10.1111/tgis.12131.
53. Yuan J., Zheng Y., Xie X. Discovering regions of different functions in a city using human mobility and POIs. Proceedings of the ACM KDD 2012, 186-194. ACM.
54. Zhen F., Wang B., Chen Y. China's city network characteristics based on social network space: an empirical analysis of sina micro-blog. Acta Geogr. Sin. 2012, 67:1031-1043.
55. Zheng Y., Liu F., Hsieh H.-P. U-Air: when urban air quality inference meets big data. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2013, 1436-1444. ACM.
56. Zuo X., Zhang Y. Detection and analysis of urban area hotspots based on cell phone traffic. J. Comput. 2012, 7:1753-1760.