The increasing dependence of businesses, organizations and institutes on internet systems has significantly increased the pressure on existing infrastructures to meet the needs of end users.
As a consequence, there is increasing demand for connected IoT or internet systems.
Traditional resource management, including information databases and analytics architectures and infrastructures, remain essential. With the growing data management demands, there are specific needs in terms of sheer capacity and capability to be able to handle diverse and complex data streams from different sources. This data needs to be processed and managed properly to maximize its value in a secure manner, while complementing it with other information sources.
Ontology's Distributed Data Exchange Framework (DDXF) defines an infrastructure framework and guidelines to support comprehensive data processing and management, while incorporating reasonable measures to achieve a layered, data-centric paradigm. As a result of extensive research on the characteristics of effective data processing and management systems, DDXF is focusing on the data interoperability, classification, format and security issues that affect various stakeholders.
It provides a series of methods and interfaces to meet the requirements of trust and data interoperability across multiple systems, which serves multiple business requirements and scenarios, especially the data exchange scenarios.