Abstract

Data integration is often one of the most challenging and time-consuming tasks, particularly within large and complex datasets. BPS-Statistics Indonesia gathers a wide range of data from the field to produce official statistics, which are then published through a data service portal. The main difficulty in this process is data integration, as users spend considerable time gathering and preprocessing the necessary datasets due to the portal's diverse data sources. To address this issue, we propose using a Virtual Knowledge Graph (VKG) approach for integrating official statistics which creates a unified view by linking and relating data from various databases, APIs, and other sources without requiring data conversion to a single format. The VKG relies on three key components: data sources, ontology to characterize data’s meaning, and mappings that specify relationships between ontology and data sources. We use statistical indicators to demonstrate the effectiveness of this approach and its ability to optimize data workflows and boost data analysis efficiency. By reducing the time and effort needed for data preprocessing, this approach frees data users to focus more on analysis and decision-making.