## 1 Introduction  
Wireless Sensor Networks (WSNs) offer the potential to give timely information in unattended environments. Dynamic visualisation of WSN data is needed to allow users to discover spatio-temporal patterns and intrinsic trends in such data. Information discovery in the ever-increasing collection of sensor data is an important problem in several scientific domains. Developing a service that facilitates the extraction and representation of sense data presents many challenges. With sensors reporting readings at a very high frequency, resulting in large volumes of data, there is a need for a network service to efficiently extract and visualise sense data. Although considerable developments have been made towards low-cost extraction and visualisation of sensory data, these solutions remain inadequate. Most of the solutions available in literature address a specific data extraction or visualisation problem but ignore others (see Section 2.2). None of these solutions is able to simultaneously ensure low energy and memory consumption, while providing dynamic and real-time data extraction and visualisations. Thus, there is a need for a data extraction and visualisation framework that can balance the conflicting requirements of simplicity, expressiveness, timeliness, and accuracy with efficient resource utilisation. This paper presents an information extraction and visualisation service, called the mapping service, which solves global network data extraction and visualisation problems through localised and distributed computation. Map as a Service (MaaS) offers great functionality such as the ability to analyse and geocode sensor data within spatial context. A service-oriented approach has special properties. It is made up of components and interconnections that stress interoperability and transparency. Services and service-oriented approaches address designing and building systems using heterogeneous network software components. This allows the development of the mapping service that works with any existing network components, e.g., routing protocols, and resources without adding extra overhead on the network. Our investigation into the development of an efficient mapping service starts by describing a centralised implementation. The merits and shortcomings of the centralised mapping services are discussed. Then, challenges that need to be met before a distributed service is feasible are identified. The distributed mapping service views the network as an entity rather than a collection of separated nodesand uses only the existing data and network capabilities of a classical WSN. Such service is suitable for informing other network services as well as the delivery of field information visualisation. The final mapping framework extends the capabilities of the distributed mapping service to accommodate the particular characteristics of the application domain to improve the mapping performance. This is done by using inductive and deductive methods as well as the universal physical principles to map sense data. The mapping framework is suitable for mapping an arbitrary number of sensed modalities and is capable of mapping one sensed modality from related multiple types of sensed data to overcome the limitations of generating a map from a single type of sense modality. This paper proceeds as follows. In Section \(2\), several mapping specific applications in the literature are outlined and a number of map generation techniques for WSNs are reviewed. Section \(3\) describes the mapping service for data extraction and visualisation in WSNs. A centralised implementation of this service is presented and its merits and shortcomings are discussed. Section \(4\) is the main exposition of the distributed map generation algorithm. It explains how to exploit other network services to provide more efficient, yet, less expensive mapping solutions. Section \(5\) presents the integrated inductive-detective framework for sensor data mapping. Section \(6\), presents the experimental evaluation of the proposed mapping service.