With the growing popularity of data-intensive services on the Intet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and de-pendencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are for-mulated by Linear-time Temporal Logic (LTL) is presented, and their satisfiability is validated by an automaton-based model checking algo-rithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on jBPM for data-aware work-flow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system man-agement in reality.