THE DATA JOURNEY FRAMEWORK: PROPOSAL OF FORMAL REPRESENTATION OF DATA AGENTS, ASSETS, AND STATES FROM DATA GENERATION TO DATA SERVING IN A DATA-CENTRIC OPERATING ENVIRONMENT

Abstract

In the ever-expanding landscape of data-intensive operations, such as Data Analytics, Machine Learning, and Deep Learning, where massive computational resources and extensive data are essential, the need for reliable and consistent attributes for data and operating agents becomes paramount. While frameworks like Archimate® and BPMN enable functional and semantic representation of organizational architecture and processes at a higher abstraction level, the data context lacks a comprehensive framework capable of capturing its components' semantic and functional aspects, from minor to big data infrastructures. This paper proposes a novel ontological framework that addresses this gap, offering a semantic and practical representation approach for data-centric business contexts. The proposed model encompasses the entire data journey, starting from data generation, moving through various stages of maturity within the value chain, and culminating in its utilization by consumer business platforms. The framework aims to be vendor-agnostic and intelligible across diverse organizations and technological ecosystems, fostering interoperability and collaboration. By leveraging this ontological framework, organizations can enhance data operations, ensuring reliability, consistency, and compliance while facilitating effective communication and decision-making within and between entities.