## 1 Introduction  
Sensors and their networks are becoming essential sources of information for planning, risk management and other scientific applications. They are revolutionising the way geo-referenced data is collected and analysed [1]. In this paper, the focus is on Wireless Sensor Networks (WSNs). These networks are composed of a large number of nodes, densely deployed within or very close to a phenomenon of interest [2]. They present an advantage over other sensor networks mainly because the WSN nodes are small, lightweight, and they consume less energy. They are usually self-adaptive systems and can be deployed with a spatial distribution that best fits the communication protocol requirements for gathering geo-referenced data [3]. Data collected by the nodes are typically transmitted through the wireless network to a sink node using some radio frequency technology, which supports the storage of the transmitted data and the communication with other devices and networks. The interoperability of WSNs aims at the achievement of an integrated sensing system, in which sensors act in a collaborative and autonomous approach to produce more value than individual observations [4,5]. The objective of the sensor standardisation initiatives carried out by the Institute of Electrical and Electronics Engineers (IEEE) and the Open Geospatial Consortium (OGC) is to overcome the heterogeneity of devices, communication protocols, networks, data formats and structures. However, in order to support the interoperability of WSNs over time it is necessary to deal with the dynamic changes in the network, components and functionalities [6,7]. In general, interoperability could be achieved by taking into account several levels, including technical, syntactic, semantic, pragmatic, and dynamic ones [8]. For example: (a) the technical level of interoperability aims at the interconnection of WSNs using common communication protocols, hardware and software; (b) the syntactic level supports the exchange of information among WSNs using a common data structure, language, logic, records and files; (c) the semantic level supports the exchange of information using a common vocabulary and it is related to standards and specifications that define schemas for the exchange of information and meaning. In the case of the pragmatic interoperability level, it allows the interconnected WSNs to be known to each other and can explore interface applications and/or services to invoke methods or procedures in order to manage the data they need. Finally, the dynamic interoperability level allows the monitoring of operation of other WSNs and the response to changes. Currently the OGC Sensor Web Enablement specifications (e. g. SML, SOS, SAS, SPS) provide a set of standards, interfaces and encodings to achieve interoperability of sensor and sensor systems [5]. From our understanding, it is mainly designed to handle the following interoperability levels: technical (web technologies), syntactic (encodings) and pragmatic (standardised interfaces). Moreover, some initiatives are being carried out to deal with the semantic interoperability of sensors [9,10]. However, the dynamic interoperability still remains to be addressed in order to monitor and manage the changes of the status of different WSNs over time. Some of these changes are due to internal factors, such as a battery run down or a neighbour's communication failure. Others may be produced by external factors such as node damage by weather conditions or changes of objectives, purpose, security and privacy constraints. Therefore, the main research challenge is mostly related to the heterogeneity and dynamic issues of how to maintain the interoperability of WSNs over time. When a change of a WSN's status occurs, thesystem must respond by triggering a self-adaptive process, which in turn, is interconnected with the WSN's functionalities. These functionalities are used to configure, protect, optimise and repair a network itself, without the intervention of humans.