Osservare tanti dati. Il ruolo della visualizzazione dei Big Data nella ricerca valutativa

Titolo Rivista RIV Rassegna Italiana di Valutazione
Autori/Curatori Davide Bennato
Anno di pubblicazione 2018 Fascicolo 2017/68
Lingua Italiano Numero pagine 21 P. 63-83 Dimensione file 698 KB
DOI 10.3280/RIV2017-068005
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The use of the Big Data in social sciences has raised a number of very delicate questions both in terms of access and in the management strategies of these sources of information. In particular, Big Data has posed a challenge mainly to data analysis from a research, decision and evaluation perspective. The aim of the paper is to illustrate the role of data visualization in assisting the process of data analysis and communication. After a brief introduction to the reasons behind the growing interest in this area and the importance of seeking new forms of data representation, attention will focus on two of the key components: the analytical component, oriented in the analysis of the data, and the communicative component, focuses on the forms of dissemination of the information. Analyzing and communicating data are the elements of the understanding process on which data visualization can make an important contribution.

Parole chiave:Big Data; Data Visualization; Visual Analytics; Data Storytelling; Assessment.

  1. Agodi M. C. (2010). L’estrazione di dati dalla Rete: una nota introduttiva. Quaderni di sociologia, 54(3): 11-21.
  2. Azzam T., Evergreen S., Germuth A. A., Kistler S. J. (2013). Data visualization and evaluation. In Azzam T. and Evergreen S., editors, Data visualization, part 1. New Directions for Evaluation, 139, 7-32.
  3. Balduzzi G. (2017). Altro che euro: secondo un grafico (satirico) la crisi economica è colpa di Facebook. Termometro Politico, 9 febbraio. -- testo disponibile al sito: http://www.termometropolitico.it/1244467_altro-euro-la-crisi-economica-cominciaarriva-facebook-grafico-satirico-gira-sui-social.html (05/08/2017).
  4. Bennato D. (2015). Il computer come macroscopio. Big data e approccio computazionale per comprendere i cambiamenti sociali e culturali, Milano: Franco Angeli.
  5. Bezzi C. (2001). Il disegno della ricerca valutativa. Milano: Franco Angeli.
  6. Cairo A. (2013). The Functional Art: An introduction to information graphics and visualization. Berkeley: New Riders (trad. it.: L’arte funzionale. Infografica e visualizzazione delle informazioni. Torino: Pearson, 2013).
  7. Chen H., Chiang R. H., Storey V. C. (2012). Business intelligence and analytics: From big data to big impact, MIS quarterly, 36(4):1165-1188.
  8. Duncan C. A., Eppstein D., Goodrich M. T., Kobourov S. G., Nöllenburg M. (2012). Lombardi Drawings of Graphs. Journal of Graph Algorithms and Application, 16(1):37-83.
  9. Feinberg J. (2010). Wordle. In: Steele J. and Iliinsky N., editors, Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media.
  10. Fisher D. (2010) Animation for Visualization: Opportunities and Drawbacks. In: Steele J. and Iliinsky N., editors, Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media.
  11. Gelman A., Kastellec J. P., Ghitza Y. (2009). Beautiful Political Data. In: Segaran T., Hammerbacher
  12. J., editors, Beautiful data: the stories behind elegant data solutions. Sebastopol: O’Reilly Media. Goldstone P. (2015). Interlock: Art, Conspiracy, and the Shadow Worlds of Mark Lombardi, Berkeley: Counterpoint.
  13. Knaflic C. N. (2015). Storytelling with data: A data visualization guide for business professionals. Hoboken: John Wiley & Sons.
  14. Kosara R., Mackinlay J. (2013). Storytelling: The next step for visualization. Computer, 46(5): 44-50.
  15. Lih A. (2009). The Wikipedia revolution, New York: Hyperion Books. (trad. it.: La rivoluzione di Wikipedia. Torino: Codice Edizioni, 2010).
  16. McFarland D. A., Lewis K., Goldberg A. (2015). Sociology in the era of big data: the ascent of forensic social science. The American Sociologist, 47(1): 12-35.
  17. Obermaier F., Obermayer B., Wormer V., Jaschensky W. (2016). About the Panama Papers, Sueddeutsche Zeitung, -- testo disponibile al sito (05/08/2017): http://panamapapers.sueddeutsche.de/articles/56febff0a1bb8d3c3495adf4/.
  18. Obermayer B., Obermaier F. (2016) Panama Papers. Die Geschichte Einer Weltweiten Enthüllung. Köln: Verlag Kiepenheuer & Witsch GmbH. & Co. (trad. it.: Panama Papers. Gli affari segreti del potere. Milano: Rizzoli, 2016).
  19. Olshannikova E., Ometov A., Koucheryavy Y., Olsson T. (2015). Visualizing Big Data with augmented and virtual reality: challenges and research agenda. Journal of Big Data, 2:22.
  20. Perer A. (2010). Finding Beautiful Insights in the Chaos of Social Network Visualizations. In Steele J. and Iliinsky N., editors, Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media.
  21. Rosling H., Rosling O., Rosling A. R. (2018). Factfulness. London: Sceptre Hodder & Stoughton (trad. it.: Factfulness. Milano: Rizzoli, 2018).
  22. Schutt, R., O’Neil C. (2013). Doing data science: Straight talk from the frontline. Sebastopol: O’Reilly Media.
  23. Shapiro M. (2010). Once upon a stacked time series. The importance of storytelling in information visualization. In: Steele J. and Iliinsky N., editors, Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media.
  24. Silver N. (2012). The signal and the noise: the art and science of prediction. London: Penguin. (trad. it.: Il segnale e il rumore. Arte e scienza della previsione. Roma: Fandango, 2013).
  25. Simon P. (2014). The Visual Organization: Data visualization, Big Data, and the Quest for Better Decisions, Hoboken: John Wiley & Sons.
  26. Steele J. and Iliinsky N., editors (2010). Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media.
  27. Thomas J. J., Cook K. A. (2006). A visual analytics agenda. IEEE computer graphics and applications, 26(1): 10-13.
  28. Tufte E. R. (2001). The visual display of quantitative information 2nd edition. Cheshire: Graphic Press.
  29. Van Ham F. (2013). Six Years of Many Eyes: A Personal Retrospective. IBM Analytics Zone, 28 February, -- testo disponibile al sito: https://www.ibm.com/blogs/analytics-zone/six-years-ofmany-eyes-a-personal-retrospective/ (05/08/2017).
  30. Vigen, T. (2015). Spurious correlations. New York: Hachette Books.
  31. Wang L., Wang G., Alexander C. A. (2015). Big data and visualization: methods, challenges and technology progress. Digital Technologies, 1(1): 33-38.
  32. Wattenberg M., Viegas F. (2010). Beautiful History: Visualizing Wikipedia. In: Steele J. and Iliinsky N., editors, Beautiful visualization: looking at data through the eyes of experts. Sebastopol: O’Reilly Media. Yau N. (2013). Data points: Visualization that means something. Indianapolis: John Wiley & Sons.
  33. Zhang L., Stoffel A., Behrisch M., Mittelstadt S., Schreck T., Pompl R., Stefan W., Holger L., Keim, D. (2012). Visual analytics for the big data era – A comparative review of state-of-the-art commercial systems. In: Santucci G., Ward M., editors, IEEE Conference on Visual Analytics Science & Technology Proceedings.

Davide Bennato, Osservare tanti dati. Il ruolo della visualizzazione dei Big Data nella ricerca valutativa in "RIV Rassegna Italiana di Valutazione" 68/2017, pp 63-83, DOI: 10.3280/RIV2017-068005