Modeling the Dashboard Provenance

Organizations of all kinds, whether public or private, profit-driven or non-profit, and across various industries and sectors, rely on dashboards for effective data visualization. However, the reliability and efficacy of these dashboards rely on the quality of the visual and data they present. Studies show that less than a quarter of dashboards provide information about their sources, which is just one of the expected metadata when provenance is seriously considered. Provenance is a record that describes people, organizations, entities, and activities that had a role in the production, influence, or delivery of a piece of data or an object. This paper aims to provide a provenance representation model, that entitles standardization, modeling, generation, capture, and visualization, specifically designed for dashboards and its visual and data components. The proposed model will offer a comprehensive set of essential provenance metadata that enables users to evaluate the quality, consistency, and reliability of the information presented on dashboards. This will allow a clear and precise understanding of the context in which a specific dashboard was developed, ultimately leading to better decision-making.Comment: 8 pages, 4 figures, one table, to be published in VIS 2023 (Vis + Prov) x Domai

Contributions of remote collaborative sketching to the design of infovis in public health

This paper presents contributions from using remote collaborative sketching to infovis for public health. The results come from an interdisciplinary study that involved designers, health researchers, public managers and computer scientists in the production of sketches generating alternatives for creating valuable graphics and dashboards. One of the creative stages was the remote collaborative workshops in which design alternatives were proposed based on sketches. The sketches were developed with the support of videoconferencing meetings, virtual boards, and graphic tablets. From this practice, we were able to include as contributions to the creative process in infovis: remote collaboration expansion; agile and iterative cycles improvement; interface design preview; data modeling supporting; addressing graphic literacy issues; creative process documentation; participant experience improvement; and additional information incorporation

O uso de mapas auto-organizáveis como ferramenta de análise exploratória em testes cognitivos destinados a medir o desempenho escolar

Apesar da melhora nos índices de escolarização apontada por indicadores internacionais tais como o PISA 2012/2015 - Programme for International Student Assessment, a qualidade da educação no Brasil continua muito ruim, necessitando de melhorias em praticamente todos os aspectos avaliados pela Organisation for Economic Co-operation and Development - OECD, que organiza o PISA, tais como o desempenho na leitura e no ensino da matemática. Este estudo tem como objetivo contribuir com técnicas que possam aperfeiçoar a análise dos dados educacionais e propõe o uso de mapas auto-organizáveis (SOM) como ferramenta para a análise exploratória de dados no apoio a descobertas e diagnósticos relativos a performance escolar, focando na análise de testes voltados para medir o desenvolvimento das habilidades cognitivas em estudantes. Espera-se que essas técnicas de analise possam auxiliar os pesquisadores da área educacional na elaboração de melhores diagnósticos relativos ao desenvolvimento cognitivo dos estudantes e auxiliar no processo de validação e normalização dos testes cognitivos, provendo, desta forma, técnicas para visualização dos dados, identificação de padrões, identificação de outliers, detecção de agrupamentos e busca por informações ocultas nos dados.Despite the improvement in schooling rates pointed by international indicators such as PISA 2012/2015 - Program for International Student Assessment, the education quality in Brazil continues to be very poor, necessitating improvements in practically all aspects assessed by the OECD, which organizes PISA, such as performance in reading and mathematics. This study aims to contribute with techniques that can improve the analysis of educational data and proposes the use of self-organizing maps (SOM) as a tool for exploratory data analysis to support discoveries and diagnoses related to school performance, focusing on the analysis of tests developed to measure the development of cognitive abilities in students. It is hoped that these techniques of analysis can help educational researchers in the preparation of better diagnoses related to student’s cognitive development and to assist in the validation process and normalization of the cognitive tests, thus providing techniques for data visualization, patterns and outliers detection, cluster analysis and searching at hidden information in the data.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio