Agriculture industries and their business ecosystems experience data and information overload because of complex network or interconnected domains linked to a variety of agro-based systems. Data search becomes tedious when specific queries are made to support crucial technical and financial decisions by agroecosystem service providers. Due to accumulated volumes of heterogeneous data and information in multiple primary sources, websites and company servers, the agriculture industry needs a robust and flexible digital agroecosystem development. To address the major challenges, a Design Science Research (DSR) approach is adopted, articulating systematic data mapping workflows and integrating their data structures in different knowledge domains. Purpose of the research is aimed at designing and developing an ontology-based data warehousing framework, with comprehensive multidimensional ontologies that motivated us to present various data modelling architectures in different knowledge-based domain applications. An emphasis is given to spatial-temporal dimensions in the modelling process that affect the structuring of data relationships in large geographic regions, which are typical in the agro-business environment.
