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master's thesis
Izbor alata i dobre prakse kod izrade vizualizacija podataka
Split: University of Split, Faculty of Science, 2024. urn:nbn:hr:166:082073
Gabelić, Ira
University of Split
Faculty of Science

Institutional repository: Repository of Faculty of Science

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Gabelić, I. (2024). Izbor alata i dobre prakse kod izrade vizualizacija podataka (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:082073

Gabelić, Ira. "Izbor alata i dobre prakse kod izrade vizualizacija podataka." Master's thesis, University of Split, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:166:082073

Gabelić, Ira. "Izbor alata i dobre prakse kod izrade vizualizacija podataka." Master's thesis, University of Split, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:166:082073

Gabelić, I. (2024). 'Izbor alata i dobre prakse kod izrade vizualizacija podataka', Master's thesis, University of Split, Faculty of Science, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:166:082073

Gabelić I. Izbor alata i dobre prakse kod izrade vizualizacija podataka [Master's thesis]. Split: University of Split, Faculty of Science; 2024 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:166:082073

I. Gabelić, "Izbor alata i dobre prakse kod izrade vizualizacija podataka", Master's thesis, University of Split, Faculty of Science, Split, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:166:082073

Metadata
TitleIzbor alata i dobre prakse kod izrade vizualizacija podataka
Title (english)Selecting tools and good practices for data visualizations
AuthorIra Gabelić
MentorGoran Zaharija (mentor)
Committee memberGoran Zaharija (predsjednik povjerenstva)
Committee memberDivna Krpan (član povjerenstva)
Committee memberMonika Mladenović (član povjerenstva)
GranterUniversity of Split
Faculty of Science
Split
Defense date and country2024-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zbog velikog broja podataka koji se generiraju suočeni smo s potrebom za većim brojem vizualizacija koja često rezultira s lošim vizualizacijama. Područje je specifično po tome što se s vizualizacijama susreću svi, a ne samo stručne osobe koje mogu primijetiti da ona ne odgovara podacima ili da je zbunjujuća pa je stoga važno precizno prikazati podatke. U radu je napravljeno istraživanje kojim su testirane prakse koje su u znanstvenim člancima opisane kao dobre, a rezultati ankete će ih potvrditi ili demantirati.
Abstract (english)
With the increasing amount of data generated daily, the need for effective visualization has become necessary. However, this often leads to poor or misleading visualizations, which is a significant concern as data visualization is not confined to scientific fields—it's something everyone encounters, often unknowingly. This paper explores the principles deemed effective in scientific literature, testing their validity through empirical research. The results of this survey aim to either support or challenge these established best practices.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:082073
Study programmeTitle: Data Science and Engineering
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra podatkovne znanosti i inženjerstva (sveučilišni/a magistar/magistra podatkovne znanosti i inženjerstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-10-28 11:50:17