Presenting Bangladesh Education Data in Analytical and Semantic Format

In an era where data plays a pivotal role in shaping policy and driving progress, especially in education, the need for well-informed decision-making is more important than ever. Like other governments, Bangladesh regularly publishes education data as part of open data policies to promote transparency and accessibility. However, while Bangladesh’s educational data is rich in key metrics, it faces limitations such as 1) a lack of a unified analytical format and insufficient aggregation, which restricts its usability for Business Intelligence, Online Analytical Processing (OLAP), and gaining a complete view of the data to extract meaningful insights; 2) limited interoperability and accessibility. In this study, we model Bangladesh’s education data across multiple dimensions, integrating diverse sources into a multidimensional framework using Data Warehousing technology. This enables OLAP-like analysis for comprehensive insights. To improve interoperability and accessibility, the data is integrated into a Knowledge Graph called BEdKG. BEdKG is modeled with the Resource Description Framework (RDF) model and composed of 337,308 RDF triples, adheres to Findability, Accessibility, Interoperability, and Reusability (FAIR) principles, and is linked to 72 external resources. Finally, evaluations through a query interface show that BEdKG, with a size of 45.3 MB, effectively addresses the issue of insufficient aggregation by providing interactive query responses and performing operations over 99% faster than manual methods.