Problem Description

During the last years, the Web has emerged as a vast collection of resources that provide data both in the form of (static) documents and in the form of services. The huge number of available data resources in the Web, as well as ongoing trends of Web-based data processing such as service mashups, Data-as-a-Service or Web content integration portals call for techniques to aggregate (i.e., collect, select and transform) heterogeneous data from distributed sources in a uniform way.

Brief Overview

We argue that there is still a lack of generic frameworks that support loosely coupled, distributed aggregation of heterogeneous data published in the Web. We present the WS-Aggregation framework as a generic solution to this problem. WS-Aggregation employs a set of interconnected aggregator nodes, which cooperate with each other to execute client requests. Following the SOA paradigm, WS-Aggregation decouples the aggregation platform from the target data services. The endpoint information of the system participants is stored in the VRESCo service registry and binding takes place dynamically at runtime.

The WAQL Query Language

WS-Aggregation makes use of the Web services Aggregation Query Language (WAQL), which is based on XQuery and provides a set of additional convenience features which we deem important in the context of data aggregation on the Web. The WAQL parser and preprocessor have been implemented with the aid of the parser generator JavaCC. A detailed description of the implementation can be found here.

Web User Interface

to be posted soon...

Contribute

We offer several internships where you can contribute to this project (see our Open Topics page for details). If you are interested in contributing to this project or have any question concerning the project, do not hesitate to contact us.

Source Code and Examples

You can download the code (source and binary) here:

WS-Aggregation-2011-10-15.zip (6.8MB) (migrated to Maven build)
WS-Aggregation-2010-12-01.zip (15.6MB)
WS-Aggregation-2010-06-20.zip (11.8MB)

Please read the README.txt for installation instructions.

Publications

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Staff

• Schahram Dustdar
• Waldemar Hummer
• Christian Inzinger
• Philipp Leitner
• Benjamin Satzger