Toward Sustainable Data Practices: Integrating Open Data With SDG-Based Data Lake Frameworks

Abstract

Achieving sustainable development goals (SDGs) necessitates the adoption of sustainable policies, which entails a crucial task of policy formulation. Policymakers must consider multiple factors, such as the present development status, which can be assessed using diverse data points, as well as the policy’s impact and an action plan outlining its implementation [1] . These data points typically originate from various sources, primarily governmental bodies encompassing statistics, budgets, legislation, public services, and geospatial data (maps, satellite imagery), along with domain users comprising individuals, organizations, and governments [2] . The SDGs are intricately crafted, taking into account a multitude of factors and pinpointing key indicators that influence these factors. These factors typically span across diverse data points sourced from various sectors. For instance, in assessing the student dropout rate, it is imperative to consider factors such as the availability of transportation facilities, basic hygiene amenities, access to drinking water, and the effectiveness of government-organized schemes in utilization and impact. Employing an open data framework coupled with advanced artificial intelligence (AI) models has the potential to facilitate in-depth exploration and analysis, providing valuable insights into the complex interplay of these factors and contributing to a more comprehensive understanding of SDG-related challenges and opportunities.