Using architecture integration patterns to compose enterprise mashups

Abstract

Enterprise mashups deal with corporate data and various sources of information to compose new value-added applications. The architecture design of enterprise mashups encompasses integration issues-it needs to integrate heterogeneous data and/or compose new situational applications from existing infrastructure. We envisage that architecture integration patterns can be applied not only as architecture solutions to mashup development, but also to help develop practical mashup techniques. In this paper, we combine several common architecture integration patterns, namely Pipes and Filters, Data Federation, and Model-View-Control to compose enterprise mashups. A number of techniques are also developed to customize these patterns for specific mashup needs. We illustrate our approach with a property valuation service derived from a real-world setting.

Composing enterprise mashup components and services using architecture integration patterns

“…Leveraging this kind of information brings opportunities to develop new situational applications (Mohammadi et al, 2009a) to improve business productivity or repurpose existing applications with value-added features. An example scenario in this context has been presented in our previous work (Liu et al, 2009): a property valuation service (PVS) company which uses an internal service to retrieve historical data about the valuation results of individual areas. Such data informs the house price valuation process when combined with other public information such as traffic and crime statistics.…”

“…In this paper, we compose key architecture patterns developed in our previous work (Liu et al, 2009) using components and RESTful Web services in extensible design of mashups. In addition, we develop essential techniques to realize this architecture for a map with overlays, however, the approach is generic to other types of mashup presentation such as markers and annotation on a map.…”

“…One study (Clarkin and Holmes, in press) categorizes them based on their role in the lifecycle of a mashup. In our previous paper (Liu et al, 2009), we broadly categorize them into two groups, the mashup builders and the mashup enablers.…”