Logo PUC-Rio Logo Maxwell
ETDs @PUC-Rio
Estatística
Título: UNCOVERING FACTORS THAT INFLUENCE HOW DATA VISUALIZATIONS ARE INTERPRETED BY NON-EXPERTS
Autor: ARIANE MORAES BUENO RODRIGUES
Colaborador(es): SIMONE DINIZ JUNQUEIRA BARBOSA - Orientador
Catalogação: 23/MAI/2022 Língua(s): ENGLISH - UNITED STATES
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=59149&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=59149&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.59149
Resumo:
Data visualizations are increasingly common in traditional media and social networks. However, the visualization literacy of the population did not follow this growing popularity. It is necessary for those who create the charts to assemble a visual communication that contains the necessary information in an attractive and easy-to-understand way. By contrast, it is necessary for those who consume them to capture information represented by the charts and extract the analyses of what they see. The importance of visual literacy is the ability to read a chart, i.e., look at a chart and identify relevant information, trends, and outliers in a given scenario. In this work, we conducted four studies to explore factors related to the success of visual data analysis. We identified issues ranging from data distribution to formulating good questions to enrich exploration. The first study discovered how people try to make sense of specific data visualizations through questions they ask when they first encounter a visualization. In the second study, we explored how data distributions can affect the effectiveness and efficiency of data visualizations. In the third study, we investigated when non-experts identify that particular visualization is not adequate to answer a specific analysis question, when they make good suggestions for changes to make these visualizations adequate, and when they evaluated well the adequacy of some suggestions offered to them. In the fourth study, we created a test to assess people s understanding of the applied (answering analysis questions supported by a visualization) and conceptual (questions about function and structure) aspects of data visualization. Our results provide resources for developing of educational material and tools for recommending data visualizations to answer specific data-relation questions. An additional contribution of this work to the results of the studies was the structuring of a unified list of different visualization tasks that we found in the literature.
Descrição: Arquivo:   
COMPLETE PDF