This paper presents a novel ontology-based framework designed to enhance collaborative analytics in high-frequency data (HFD) environments. Addressing the integration challenges posed by disparate software modules, the proposed ontology streamlines collaborative efforts across diverse data and software landscapes. Key contributions include a preliminary ontology design that enables seamless integration of microservices and data sources, thereby facilitating efficient and coherent data analytics workflows. The effectiveness of this framework is demonstrated through a case study involving intraday metric analysis in high frequency trading data, highlighting improvements in efficiency, accuracy, and flexibility. This study underscores the transformative potential of integrating ontology frameworks into collaborative analytics environments, particularly in handling the complexities of high-frequency data.