Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: http://hdl.handle.net/1946/44483
This thesis examines the importance of context, limitations disclosure, integrity, and correctness in; data processing and ethical issues of misrepresenting data through visualisations, impairing the interpretation and understanding of the information being presented. The use of misleading graphical representations, such as intentionally Darkened Data, malinformation, exaggerating the size of certain data points, presenting data without a scale of reference or context, and distorting the scales on axes, affects human ability to accurately interpret the data. The key contribution of this thesis is the mapping of common methods and pitfalls on this topic. It has important implications for the presentation and interpretation of data in fields such as; journalism, politics, and business, where the use of misleading visual representations can lead to misguided decisions and misinformed public opinion. The thesis found that the use of misleading or biased visual representations impairs an audience's ability to correctly assess the data provided and while there seems to be increased public awareness about some tactics, such as distorted scales on axes, strategic use of dark data and exaggerating data point sizes continues to threaten the truth.
Keywords: Human-Centred Computing, Dark Data, Misinformation, Disinformation, Malinformation, Ethics, Visualization Literacy, Decision Making, Effects of Cognitive Bias, Media Manipulation, Visualization Design, Visualization Theory, Information Visualization, Noise Removal.