Wizualizacja danych, informacji i wiedzy

ISBN: 978-83-7972-683-7    ISBN (online): 978-83-7972-673-8    ISSN: 0860-2751    OAI    DOI: 10.18276/978-83-7972-673-8
CC BY-SA   Open Access 

Issue archive / T. (MCCCLXXI) 1297

Year of publication:2023
Dziedzina:Dziedzina nauk społecznych
Dyscyplina:nauki o zarządzaniu i jakości
Keywords: data visualization information visualization distortions in charts good practices for creating visualizations
Authors: Ewa Krok ORCID
Uniwersytet Szczeciński

Information

Electronic version of the publication available under CC BY-SA 4.0 license after 12 months from the date of release: December 2023

Abstract

The monograph was devoted to the issues of visualization. The concepts were systematized, important elements were analyzed, the knowledge of which affects the quality of the created visualizations and thus affects the effectiveness of content transfer, which from a business point of view often determines the accuracy of the actions taken. The book contains many valuable tips on the principles of developing visualizations, coming from world-class specialists. Aspects that affect the readability and unambiguity of the message, as well as its accessibility, were discussed. A review of websites devoted to visualizations, chart selectors and IT tools supporting the creation of graphics was made. It also presents the possibilities of distortion of facts and manipulation in the transfer of information, which are sometimes used by chart designers in order to induce a specific way of thinking about the presented situation in the recipient. Distortions resulting from the conscious use of the functionality of computer graphics programs to create charts, as well as distortions resulting from the deliberate selection of such and not other data for visualization, were analyzed. The last chapter of the monograph contains an analysis of the results of the study of students’ skills in creating charts based on a verbal description, which allowed the identification of the most common mistakes that limit the readability of visualization and affect its quality.

Bibliography

1.Bauer M., Johnson-Laird P. (1993). How diagrams can improve reasoning. Psychological Science 4(6), 372–378. DOI: 10.1111/j.1467-9280.1993.tb00584.x.
2.Bertschi S., Bresciani S., Crawford T., Goebel R., Kienreich W., Lindner M., Sabol V., Moere A. (2011). What is knowledge visualization? Perspectives on an emerging discipline, w: Proceedings of the International Conference on Information Visualisation, 329–336. DOI: 10.1109/IV.2011.58.
3.Biecek P. (2014). Odkrywać! Ujawniać! Objaśniać! Zbiór esejów o sztuce pokazywania danych. Warszawa: Fundacja Naukowa SmarterPoland.pl. http://www.biecek.pl/Eseje/.
4.Bresciani S., Eppler M.J. (2015). The Pitfalls of Visual Representations. SAGE Open 5(4). DOI: 10.1177/2158244015611451.
5.Burkhard R.A. (2004). Learning from architects: the difference between knowledge visualization and information visualization, w: Proceedings of Eighth International Conference on Information Visualization (04.2004), 519–524. IEEE, London
6.Burkhard R.A. (2005). Towards a Framework and a Model for Knowledge Visualization: Synergies Between Information and Knowledge Visualization. Conference Knowledge and Information Visualization Searching for Synergies. DOI: 10.1007/11510154_13.
7.Cairo A. (2012). The Functional Art: An introduction to information graphics and visualization. Berkeley: New Riders.
8.Cairo A. (2016). The Truthful Art: Data, Charts, and Maps for Communication. Berkeley: New Riders.
9.Cairo A. (2018). In visualization, white space is your friend. https://questionsindataviz.com/2018/01/06/is-white-space-always-your-friend/.
10.Cairo A. (2020). How Charts Lie: Getting Smarter about Visual Information. New York: W.W. Norton & Company.
11.Camões J. (2016). Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel. Berkeley: New Riders.
12.Card S.K., Mackinlay J.D., Shneiderman B. (1999). Readings in Information Visualization; Using Vision to think. Los Altos, CA: Morgan Kaufmann.
13.Chan V. (2017) Getting it right: why infographics are not the same as data visualizations. https://blog.prototypr.io/getting-it-right-why-infographics-are-not-the-same-as-data-visualizations-a23da7de745e.
14.Chen M., Ebert D., Hagen H., Laramee R.S., Van Liere R., Ma K.-L., Ribarsky W., Scheuermann, G., Silver D. (2009). Data, Information, and Knowledge in Visualization. Computer Graphics and Applications, IEEE. 29(1), 12–19. DOI: 10.1109/MCG.2009.6.
15.Cicharski B. (2021). Kłamstwo ma krótką oś Y, czyli jak wykreślić nieprawdę. Finanse i Controlling 73.
16.Czapiewski B. (2010). Projektowanie wykresu krok po kroku. https://skuteczneraporty.pl/blog/projektowanie-wykresy-krok-po-kroku/.
17.Dylak S. (2012). Alfabetyzacja wizualna jako kompetencja współczesnego człowieka, w: W. Skrzydlewski, S. Dylak (red.), Media – Edukacja – Kultura. Poznań–Rzeszów: Polskie Towarzystwo Technologii i Mediów Edukacyjnych, 119–132.
18.Ellis W.D. (1938). A Source Book of Gestalt Psychology. New York: Harcourt, Brace & World. DOI: 10.1037/11496-000.
19.Emery A.A. (2021). Designing accessible data visualizations. 10 Quick Wins. https://depictdatastudio.gumroad.com/l/accessibility, https://gumroad.com/l/NILdp.
20.Eppler M.J. (2011). What is an effective knowledge visualization? Insights from a review of seminal concepts, w: Proceedings of the International Conference on information Visualisation, 3–12. DOI: 10.1109/IV.2011.13.
21.Falkowitz R. (2019). Information Visualization or Data Visualization? Concentric Circle Consulting. https://www.3cs.ch/information-visualization-data-visualization/.
22.Few S. (2009). Now You See It: Simple Visualization Techniques for Quantitative Analysis. Oakland: Analytics Press.
23.Few S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Oakland: Analytics Press.
24.Few S. (2013). Information Dashboard Design: Displaying Data for At-a-glance Monitoring. Oakland: Analytics Press.
25.Franconeri S. (2019). Multiple views on how to choose a visualization. https://medium.com/multiple-views-visualization-research-explained/multiple-views-on-how-to-choose-a-visualization-b3ffc99fcddc.
26.Gatto M.A.C. (2015). Making Research Useful: Current Challenges and Good Practices in Data Visualization. Oxford: Reuters Institute for the Study of Journalism, University of Oxford.
27.Glenberg A., Langston M. (1992). Comprehension of illustrated text: pictures help to build mental models. Journal of Memory and Language 31(2), 129–151. DOI: 10.1016/0749-596X(92)90008-L.
28.Kahneman D. (2012). Pułapki myślenia. O myśleniu szybkim i wolnym. Poznań: Media Rodzina.
29.Kelleher C., Wagener T. (2011). Ten guidelines for effective data visualization in scientific publications. Environmental Modelling and Software 26(6), 822–827. DOI: 10.1016/j.envsoft.2010.12.006.
30.Kirk A. (2019). Data Visualisation: A Handbook for Data Driven Design. Thousand Oaks: SAGE Publications Ltd.
31.Koffka K. (1935). The Principles of Gestalt Psychology. New York: Harcourt, Brace & World.
32.Kosslyn S.M. (1980). Images and Mind. Cambridge: Harvard University Press.
33.Krok E. (2013). Determinanty skłonności pracowników do dzielenia się wiedzą – koncepcja diagnozy dla potrzeb zarządzania. Szczecin: Volumina.
34.Krok E. (2021) Visualization on charts – manipulations and distortions. Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES2021. Procedia Computer Science 192, 3932–3944. DOI: 10.1016/j.procs.2021.09.168.
35.Krok E. (2022). Assessment of students’ skills in visual communication of information. Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES2022. Procedia Computer Science 207, 2891–2900. DOI: 10.1016/j.procs.2022.09.347.
36.Król K. (2019). Map charts: visualisation of statistical data on a background map – case study. Geomatics, Landmanagement and Landscape (GLL) 4, 171–181. DOI: 10.15576/GLL/2019.4.171.
37.Larkin J., Simon H. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science 11, 65–99. DOI: 10.1111/j.1551-6708.1987.tb00863.x.
38.Leo S. (2019). Mistakes, we’ve drawn a few. Learning from our errors in data visualisation. The Economist. https://medium.economist.com/mistakes-weve-drawn-a-few-8cdd8a42d368.
39.Manovich L. (2010). What is visualization? The Journal of the Initiative for Digital Humanities, Media, and Culture 2(1), 1–32.
40.Marchese F.T., Banissi E. (2013). Knowledge Visualization Currents: From Text to Art to Culture. London: Springer-Verlag. DOI: 10.1007/978-1-4471-4303-1.
41.Medyńska-Gulij B. (2011). Kartografia i geowizualizacja. Warszawa: Wydawnictwo Naukowe PWN.
42.Meirelles I. (2013). Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations. Beverly: Rockport Publishers.
43.Meyer R. (2010). Knowledge Visualization. Trends in Information Visualization 32, 63–84.
44.Midway S.R. (2020). Principles of Effective Data Visualization. Paterns Perspective 1(9). DOI: 10.1016/j.patter.2020.100141.
45.Miller G.A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review 63, 81–97. DOI: 10.1037/h0043158.
46.Mills J.H., Thurlow A., Mills A.J. (2010). Making sense of sensemaking: the critical sensemaking approach. Qualitative Research in Organizations and Management: An International Journal 5(2), 182–195. DOI: 10.1108/17465641011068857.
47.Motylińska P. (2014). Wybrane zagadnienia wizualizacji w nauce o informacji, w: A. Korycińska-Huras, M. Janiak (red.), Komunikacja naukowa w środowisku cyfrowym: badania, zasoby, użytkownicy. Warszawa: Wydawnictwo SBP, 406–427.
48.Munzner T. (2009). Visualization. w: P. Shirley, S. Marschner (red.), Fundamentals of Computer Graphics. Natick: AK Peters, 675–707. DOI: 10.1201/9781315372198-26.
49.Nielsen C.B. (2016). Visualization: A Mind-Machine Interface for Discovery. Trends in Genetics 32(2), 73–75. DOI: 10.1016/j.tig.2015.12.002.
50.Nonaka I. (1991). The Knowledge-Creating Company. Harvard Business Review 69(6), 96–104.
51.Novick L.R. (2001). Spatial diagrams: Key instruments in the toolbox for thought. The psychology of learning and motivation 40, 279–325. DOI: 10.1016/S0079-7421(00)80023-7.
52.Nussbaumer Knaflic C. (2015). Storytelling with Data: A Data Visualization Guide for Business Professionals. Hoboken: Wiley.
53.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(1), 22. DOI: 10.1186/s40537-015-0031-2.
54.Pugsley S. (2022). Telling a Great Data Story: A Visualization Decision Tree. https://www.kdnuggets.com/2021/02/telling-great-data-story-visualization-decision-tree.html.
55.Renaud K., van Biljon, J. (2017). Charting the Path towards Effective Knowledge Visualisations, w: Proceedings of the Southern African Institute of Computer Scientists and Information Technologists, South Africa, (SAICSIT’17). Association for Computing Machinery. DOI: 10.1145/3129416.3129421.
56.Riche N.H., Hurter Ch., Diakopoulos N., Carpendale S. (2018). Data-Driven Storytelling. Boca Raton: A K Peters/CRC Press.
57.Robbins N.B. (2013). Creating More Effective Graphs. Katy: Chart House.
58.Roberts J.C., Ritsos P.D., Badam S.K., Brodbeck D., Kennedy J., Elmqvist N. (2014). Visualization beyond the desktop-the next big thing. IEEE Computer Graphics and Applications 34(6), 26–34. DOI: 10.1109/MCG.2014.82.
59.Schwabish J.A. (2016). Better Presentations: A Guide for Scholars, Researchers, and Wonks. New York: Columbia University Press. DOI: 10.7312/schw17520.
60.Schwabish J.A. (2020). Elevate the Debate: A Multilayered Approach to Communicating Your Research. Hoboken: Wiley.
61.Shepard R.N., Cooper L.A. (1982). Mental Images and Their Transformations. Cambridge: MIT Press.
62.Shirley P., Marschner S. (red.) (2009). Fundamentals of Computer Graphics. Natick: AK Peters.
63.Stanimir A. (2012). Różne techniki prezentacji powiązań kategorii zmiennych niemetrycznych. Ekonometria 3(37), 9–25.
64.Steczkowski J., Zeliaś A. (1981). Statystyczne metody analizy cech jakościowych. Warszawa: PWE.
65.Stevens S.S. (1959). Measurement, psychophysics and utility, w: C.W. Churchman, P. Ratoosh (red.), Measurement: Definitions and Theories. New York: Wiley.
66.Szews P. (2017). Wizualizacja przekazu w dziennikarstwie. Infografika i data journalism w wybranych mediach. Praca doktorska, Uniwersytet Łódzki.
67.Taei P. (2018). What is an infographic? And how is it different from a data visualization? https://towardsdatascience.com/what-is-an-infographic-and-how-is-it-different-from-a-data-visualization-a92c23b35197.
68.Tal A., Wansink B. (2016). Blinded with science: Trivial graphs and formulas increase ad persuasiveness and belief in product efficacy. Public Understanding of Science 25(1), 117–125. DOI: 10.1177/0963662514549688.
69.Tufte E.R. (2007). The Visual Display of Quantitative Information. Cheshire: Graphics Press.
70.Valkanova N., Jorda S., Vande Moere A. (2015). Public visualization displays of citizen data: Design, impact and implications. International Journal of Human Computer Studies 81, 4–16. DOI: 10.1016/j.ijhcs.2015.02.005.
71.Van Biljon J., Renaud K. (2015). Do Visualizations Ease Dissertation Assessment?, w: Proceedings of the 44th Annual Southern African Computer Lecturers Association, 177–185.
72.Van Stralen D. (2015). Ambiguity. Journal of Contingencies and Crisis Management 23(2), 47–53. DOI: 10.1111/1468-5973.12082.
73.Ware C. (2013). Information Visualization. Perception for Design. Burlington: Morgan Kaufmann.
74.Wexler S., Shaffer J., Cotgreave A. (2017). The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios. Hoboken: Wiley. DOI: 10.1002/9781119283089.
75.Wilke C.O. (2020). Podstawy wizualizacji danych. Zasady tworzenia atrakcyjnych wykresów. Gliwice: Helion.
76.Wong Dona M. (2013). The Wall Street Journal Guide to Information Graphics: The Dos and Don’ts of Presenting Data, Facts, and Figures. New York: W.W. Norton & Company.
77.Yaacob S., Liang H., Mohamad N. (2017). Towards a characterization of complex visualizations. Open International Journal of Informatics (OIJI) 5, 19–29.
78.Yau N. (2011). Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics. Hoboken: Wiley.
79.Yusoff Z., Katmon S.A., Ahmad M.N., Miswan S.H.M. (2013). Visual representation: Enhancing students’s learning engagement through knowledge visualization, w: International Conference on Informatics and Creative Multimedia, 242–247. DOI: 10.1109/ICICM.2013.48.
80.Zhang Y., He X., Xie J., Wang Z. (2008). Study on the knowledge visualization and creation supported Kmap platform, w: 1st International Workshop on Knowledge Discovery and Data Mining, WKDD, 154–159.
81.Portale i strony internetowe, do których odwołania pojawiają się w tekście
82.http://chartchoosercards.com/
83.http://chartmaker.visualisingdata.com/
84.http://visualizationuniverse.com/
85.https://adioma.com/
86.https://coolinfographics.com/
87.https://datavizcatalogue.com/
88.https://datavizproject.com/
89.https://depictdatastudio.com/
90.https://experception.net/
91.https://extremepresentation.com/
92.https://flowingdata.com/
93.https://gravyanecdote.com
94.https://infonewt.com/
95.https://insights.datylon.com/stories
96.https://kulturawrazliwa.pl/wiedza/jak-stworzyc-tekst-alternatywny-krotki-poradnik/
97.https://policyviz.com/
98.https://readable.com/
99.https://stephanieevergreen.com/
100.https://support.microsoft.com/pl-pl/office/dost%C4%99pne-typy-wykres%C3%B3w-w-pakiecie-office-a6187218-807e-4103-9e0a-27cdb19afb90
101.https://thenounproject.com/
102.https://www.data-to-viz.com/
103.https://www.datawrapper.de/
104.https://www.datylon.com/
105.https://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=00002o
106.https://www.esri.pl/arcgis/
107.https://www.ferdio.com/
108.https://www.geckoboard.com/
109.https://www.iconfinder.com/
110.https://www.juiceanalytics.com/chartchooser/
111.https://www.kdnuggets.com/wp-content/uploads/pugsley-visualization-decision-tree-kd-v12.jpg
112.https://www.qlik.com/blog/patrik-lundblad/
113.https://www.statsoft.pl/textbook/
114.https://www.visualisingdata.com/
115.https://www.visual-literacy.org/