Implementing Semantic Web applications: reference architecture and challenges

To date, Semantic Web research has tended to focus on data modelling challenges, at the expense of software architecture and engineering issues. Our empirical analysis shows that implementing Semantic Web technologies creates challenges which can affect the whole application. Standard solutions and best practices for Semantic Web technologies are just emerging. The lack of these has been an obstacle for implementing and deploying applications which exploit Semantic Web technologies for real world use cases. In this paper we conduct an empirical survey of Semantic Web applications. We use this empirical data to propose a reference architecture for Semantic Web applications, and to identify the four main challenges for implementing the most common functionality related to Semantic Web technologies from a software engineering perspective: (i) the issues involved in integrating noisy and heterogeneous data, (ii) the mismatch of data models and APIs between components, (iii) immature and belated best practices and standards, and (iv) the distribution of application logic across components. We describe two orthogonal approaches for mitigating these challenges: (a) simplifying the application architecture by delegating generic functionality to external service providers, and (b) assembling and customising of components provided by software frameworks for rapid development of complete applications.