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.