Implementing Semantic Web Applications: challenges and reference architecture

Speaker : Benjamin Heitmann

ABSTRACT

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.

BIO

Benjamin Heitmann joined DERI as a Ph.D. candidate/researcher in  September 2008. His primary advisor for his Ph.D. program is Dr. Conor  Hayes, and he is working as a part of the LION II cluster. Benjamin  made his M.Sc. in Computer Science at the University of Karlsruhe,  Germany, which is one of the nine German Excellence Universities. His  main research interests are: (1) next generation of personalisation  and recommendation systems, (2) architectural perspectives on the Web of Data, and (3) applying  Software Engineering to the Web of Data.