Development of E-Comic Based on Local Wisdom to Improve Scientific Literacy

This research is the development of local wisdom-based e-comics to increase scientific literacy. Learning media can help achieve learning objectives. This study aims to develop e-comic learning media based on local wisdom to improve scientific literacy in grade IV elementary school. The type of research used is Research and Development with the ADDIE development model namely Analyze, Design, Development, Implementation, and Evaluation. This study used test subjects by carrying out validity tests on media experts, material experts, learning experts and the responses of ten fourth grade elementary school students. Data collection using a questionnaire instrument. Research data were analyzed by means of descriptive quantitative and descriptive qualitative. The results of the media expert validator are categorized as very valid. The results of the material expert validator are categorized as very valid. The results of the learning expert validator are categorized as very valid. As well as the results of the responses of ten fourth grade elementary school students categorized as very valid. The overall results of the validator test are categorized as very valid so that e-comic media based on local wisdom can be used with learning alternative energy sources in grade IV Elementary School Science lessons

PROV-Health: método para gerenciamento de dados de proveniência em sistemas de informação em saúde

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências da Educação, Programa de Pós-Graduação em Ciência da Informação, Florianópolis, 2023.A Ciência da Informação e a Ciência da Computação, compactuam aspectos interdisciplinares no que diz respeito à Proveniência de Dados entre diferentes Sistemas de Informação em Saúde (SIS). Os SIS armazenam grandes volumes de dados em seus repositórios descentralizados, tornando um desafio o gerenciamento e a interoperabilidade desses dados. Assim, a Proveniência de Dados associada a tecnologias computacionais contribui para a rastreabilidade dos dados de origem nos SIS, a fim de identificar erros e transformações nos dados e atribuí-los às fontes, sendo útil para tomadas de decisões nos mais variados cenários de saúde. Nesta tese apresenta-se um método para gerenciamento de dados de proveniência em SIS com base no instanciamento do modelo da World Wide Web Consortium Provenance (W3C PROV) em conformidade com os aspectos de interoperabilidade entre diferentes bases de dados de saúde descentralizadas. Para alcançar os objetivos definidos para esta tese, assume-se uma metodologia de pesquisa aplicada em um estudo de caso, caracterizada como experimental e exploratória, com abordagem quantitativa e qualitativa. Quanto aos procedimentos técnicos no desenvolvimento e validação do método, foram realizados experimentos em um cenário de saúde real com dados reais, os quais possibilitaram identificar além de benefícios, desafios e ameaças durante sua experimentação. O método foi avaliado via formulário eletrônico enviado a especialistas da área, os quais destacaram pontos importantes para reflexão na estrutura do método. Conclui-se que ao final dos experimentos e das etapas de análises dos resultados, o método proposto mostrou-se significativo no que se refere ao gerenciamento de dados de proveniência em diferentes SIS, sendo possível adaptá-lo a qualquer cenário de saúde.Abstract: Information Science and Computer Science share interdisciplinary aspects when it comes to Data Provenance between different Health Information Systems (HIS). HIS store large volumes of data in their decentralized repositories, making the management and interoperability of this data a challenge. Thus, Data Provenance associated with computer technologies contributes to the traceability of source data in HIS, in order to identify errors and transformations in the data and attribute them to the sources, being useful for decision-making in the most varied health scenarios. This thesis presents a method for managing provenance data in HIS based on instancing the World Wide Web Consortium Provenance (W3C PROV) model in accordance with interoperability aspects between different decentralized health databases. In order to achieve the objectives defined for this thesis, an applied research methodology was used in a case study, characterized as experimental and exploratory, with a quantitative and qualitative approach. As for the technical procedures for developing and validating the method, experiments were carried out in a real health scenario with real data, which made it possible to identify not only benefits, but also challenges and threats during experimentation. The method was evaluated via an electronic form sent to experts in the field, who highlighted important points for reflection on the structure of the method. The conclusion is that at the end of the experiments and the stages of analysis of the results, the proposed method proved to be significant in terms of managing provenance data in different HIS and can be adapted to any healthcare scenario

Visualizing the Provenance of Personal Data using Comics

Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comics strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations

Visualizing the Provenance of Personal Data Using Comics

Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comic strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations