The advance in quality of public education is a challenge to public managers in contemporary society. In this sense, many studies point to the strong influence of socioeconomical factors in school performance but it is a challenge to select proper data to perform analyses on this matter. In tandem, it has happening a growth in provision of big quantities of educational indicators data, but in isolate cases, and by different agencies of Brazilian government. For this work, we use both education and economic indicators for analysis. The following socioeconomical indicators were selected: municipal human development index (MHDI), social vulnerability index (SVI), Gini coefficient and variables extracted from DBpedia, as part of the connection of this data to the Web of data: GDP per capita and municipal population. These data were used as independent variables to look into their correlations with Brazilian Basic Education Development Index (IDEB) performances at municipal level, supported by the application of linked open data principles. OpenRefine was used to extract the data from different sources, convert to RDF triples and then the mapping of the variables to existing ontologies and vocabularies in this domain, aiming at the reuse of existing semantics. The correlational analysis of the variables showed coherence with the literature about the theme, with significative magnitude between IDEB performances and the indicators related to income and parent education (SVI and HDI), besides moderate relations with the other varibles, except for the municipal population. Finally, the consolidated dataset, enriched by information extracted DBpedia was made available by a SPARQL endpoint for queries of humans and software agents, allowing other applications and researchers to explore the data from other platforms.

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Open data has been published by governments worldwide in the last years. The educational domains in often one of the prioritary ones, presenting multiple perspectives represented by these datasets, which also brings great complexity for its integration and reuse. In this work, we present a domain ontology that enables to describe education data in a macro-level, derived from open government data. As result, it is possible to cover a big part of the datasets officially available and that can be reused in data integration among different information systems. This work contributes with a domain ontology for education open government data and a method to derive this ontology from data.Resumo. Dados abertos têm sido publicados por governos do mundo todo nos últimos anos. O domínio educacional é um dos prioritários, contendo diversas perspectivas representadas por esses dados, o que traz também grande complexidade para sua integração e seu reuso. Neste trabalho apresentamos uma ontologia de domínio que possibilita descrever dados educacionais em nível macro, a partir dos dados abertos governamentais. Como resultado, é possível obter uma cobertura de quase todos os conjuntos de dados disponíveis oficialmente e que pode ser usado na integração de dados entre diferentes sistemas de informação. Este artigo propõe como contribuição uma ontologia de domínio para dados abertos governamentais educacionais e um método de derivar tal ontologia a partir de dados já existentes.

Open government data has been published in the last few years, aiming for its economic exploitation and social control. However, given the administrative autonomy of public bodies, the data show discrepancies of formats, identifiers and descriptions, even for same entities. Linked open data seek to fill this gap by creating links for different contexts. This paper proposes a metaprocess for publishing linked data as well as a framework to assist the choices of appropriate tools for this task. The proposal is evaluated with two examples from the literature, with relevant contexts for the educational domain.Resumo. Dados abertos governamentais têm sido publicados nos últimos anos, buscando sua exploração econômica e de controle social. No entanto, com a autonomia de cada órgão produtor de dados, ocorre a discrepância entre formatos, identificadores e descrições, mesmo que para as mesmas entidades. Os dados abertos conectados buscam explorar essa lacuna, ao criar conexões entre diferentes contextos. Este artigo traz uma proposta de metaprocesso para a publicação de dados conectados bem como um framework para a escolha de ferramental apropriado para a tarefa. A proposta é avaliada com dois exemplos da literatura em cenários relevantes para o domínio educacional.

Purpose This article introduces concepts and a general taxonomy used by the educational data mining (EDM) community, as well as examples of their applications, with the aims of providing audiology educators with a referential basis for developing this area. Method A narrative review was carried out to present an overview of EDM and its main methods. Some of these methods were exemplified with analysis of real data from an Internet-based specialization course on pediatric auditory rehabilitation. Results The review introduced EDM main concepts and applications and described methods from its area. Real data examples illustrated EDM use to predict interpersonal help-seeking, model interpersonal interaction, analyze students' trajectories within a course's module, and understand how students approached group assignments. Some of the insights provided by EDM to support teaching and learning processes were also described. Conclusions EDM methods offer new tools to discover knowledge from digital traces (i.e., logs) and support key stakeholders (students, instructors, or course administrators) to raise awareness about course dynamics. This approach has the potential to foster a better understanding and management of educational processes in audiology distance education.

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Resumo. Os dados abertos educacionais trazem informações importantes IntroduçãoNa última década, diversos países pelo mundo têm apresentado iniciativas de abertura de seus dados governamentais, no chamado movimento de governo aberto, com objetivo de fornecer espaço para a abertura, transparência e diálogo contínuo entre o governo e seus cidadãos (Parycek e Sachs, 2015), viabilizado por meio dos dados abertos. Ao liberar os dados em formatos não proprietários e sem licenças restritivas, o governo permite que diferentes setores da sociedade se apropriem das informações e gerem análises, produtos e serviços que retornariam na forma de benefícios para a