## 7 Conclusions  
In order to handle changes in WSN status and to support dynamic interoperability, the relationships between local and global interoperability models must be addressed. Towards this challenge we have introduced the notion of contexts as an explicit representation of WSNs' status inferred from metadata elements. Moreover, a context model is proposed to represent the WSNs' status based on four types of contexts: sensing, node, network and organisational. The focus in this approach has been on the capturing and reasoning over different contexts, using two types of reasoning rules: contextualising rules and bridge rules. However, in this paper we have focused on the development of contextualising rules as a mechanism to infer different WSN contexts from WSN status using metadata elements. As a proof of concept we have demonstrated examples of contextualising rules based on the localised reasoning in the node and organisational contexts, as well as on the shifting reasoning in which the contexts depend on the metadata value.  
We have shown the important role of metadata elements to contextualise the dynamic interoperability of WSNs. The metadata act as parameters in order to interpret what is happening inside the box (i.e. the context). Depending on their value and the level of approximation, the interpretation of contexts could be different. Some people may argue that metadata are low level information about WSNs, but managing them in a properly form (contextualising rules), they allow the inference of high level of knowledge about the possible WSN contexts in which the sensing is carried out. The use of spatial metadata, such as location, coverage area or security area, adds the spatial dimension into the reasoning process allowing the inference of spatially related contexts.  
Furthermore from sensing data collection view point, sensor networks are sensing a massive amount of data and with their interoperability the amount of data increase even more. Currently, all these data is provided in isolation without context [5]. Thus, contextualising the interoperability will allow a more intelligent recovery of sensing data and resources based not only in queries of where (geographic coordinates), when (date and time), how (sensor specification) or what (phenomena type), but also related with more rich contextual knowledge such us: all the nodes that are sensing in a high security areas or all the nodes that are sensing near the sea; the nodes that are sensing in the same context but not necessary in the same geographic context, the context in which two nodes had been interacted, all the nodes that are allowed to interoperate and are attached to public transport. The context-based information retrieval could be pointed out as an important issue of Sensor Web.  
This paper describes our first step towards the maintenance of WSN interoperability. In order to contextualise the WSN interoperability a further analysis on the relationships among contexts is needed in order to develop the representation and bridge rules of the global model (dynamic interoperability). Therefore, our next research will be to implement the bridge rules as part of a decision-making process that can allow the reasoning among different contexts and between contexts and the dynamic interoperability, which in turn will allow us to decide what should be done to maintain the dynamic interoperability in despite of the changes of WSN status. We are planning to explore more in detail the localised, push and pop and shifting reasoning tasks and their relation with the bridge rules. Finally, we will implement a concrete case of study for the evaluation of our context model as an approach to address the dynamic interoperability of WSNs.