Internet of Things (IoT) is an emerging paradigm that involves both industry and academic communities. In term of smart cities, IoT plays an essential role in the technological development applied to society to improve life quality. In several application fields such as environmental monitoring, using the concept of the sensors network to produce data is also considered as the Internet of Things platform for data producing. In the race of designing IoT as a part of the Future Internet architecture, Information and Communication Technology (ICT) industry and academic communities have realized the crucial problem in IoT is the interoperability of the information and sersvices [1]. In order to enable the interoperability among systems and data services in sensors networks, in this paper we propose an IoT data analytic framework that deals with the heterogeneous sensors data sources and play as a data management tool in the context of environmental monitoring. This proposed framework also helps reuse data, share knowledge and provide environmental rules among the data services with Semantic Web technologies across IoT platforms. We describe a semantic data model, rules, and a reasoning platform taking SPARQL queries as rules to enable high-level data abstraction and knowledge extraction. Our approach is realized by Semantic Web technologies as the core with reusable components for supporting different types of services through Web of Things.