  In Bangladesh, agriculture is a crucial driver for addressing Sustainable
Development Goal 1 (No Poverty) and 2 (Zero Hunger), playing a fundamental role
in the economy and people's livelihoods. To enhance the sustainability and
resilience of the agriculture industry through data-driven insights, the
Bangladesh Bureau of Statistics and other organizations consistently collect
and publish agricultural data on the Web. Nevertheless, the current datasets
encounter various challenges: 1) they are presented in an unsustainable,
static, read-only, and aggregated format, 2) they do not conform to the
Findability, Accessibility, Interoperability, and Reusability (FAIR)
principles, and 3) they do not facilitate interactive analysis and integration
with other data sources. In this paper, we present a thorough solution,
delineating a systematic procedure for developing BDAKG: a knowledge graph that
semantically and analytically integrates agriculture data in Bangladesh. BDAKG
incorporates multidimensional semantics, is linked with external knowledge
graphs, is compatible with OLAP, and adheres to the FAIR principles. Our
experimental evaluation centers on evaluating the integration process and
assessing the quality of the resultant knowledge graph in terms of
completeness, timeliness, FAIRness, OLAP compatibility and data-driven
analysis. Our federated data analysis recommend a strategic approach focused on
decreasing CO$_2$ emissions, fostering economic growth, and promoting
sustainable forestry.
