Planning and Design Soa Architecture Blueprint

Service Oriented Architecture (SOA) is a framework for integrating business processes and supporting IT infrastructure as secure, standardized components-services-that can be reused and combined to address changing business priorities. Services are the building blocks of SOA and new applications can be constructed through consuming these services and orchestrating services within a business process. In SOA, services map to the business functions that are identified during business process analysis. Upon a successful implementation of SOA, the enterprise gain benefit by reducing development time, utilizing flexible and responsive application structure, and following dynamic connectivity of application logics between business partners. This paper presents SOA reference architecture blueprint as the building blocks of SOA which is services, service components and flows that together support enterprise business processes and the business goals

ATLAS Data Challenge 1

In 2002 the ATLAS experiment started a series of Data Challenges (DC) of which the goals are the validation of the Computing Model, of the complete software suite, of the data model, and to ensure the correctness of the technical choices to be made. A major feature of the first Data Challenge (DC1) was the preparation and the deployment of the software required for the production of large event samples for the High Level Trigger (HLT) and physics communities, and the production of those samples as a world-wide distributed activity. The first phase of DC1 was run during summer 2002, and involved 39 institutes in 18 countries. More than 10 million physics events and 30 million single particle events were fully simulated. Over a period of about 40 calendar days 71000 CPU-days were used producing 30 Tbytes of data in about 35000 partitions. In the second phase the next processing step was performed with the participation of 56 institutes in 21 countries (~ 4000 processors used in parallel). The basic elements of the ATLAS Monte Carlo production system are described. We also present how the software suite was validated and the participating sites were certified. These productions were already partly performed by using different flavours of Grid middleware at ~ 20 sites.Comment: 10 pages; 3 figures; CHEP03 Conference, San Diego; Reference MOCT00

BlogForever D2.4: Weblog spider prototype and associated methodology

The purpose of this document is to present the evaluation of different solutions for capturing blogs, established methodology and to describe the developed blog spider prototype

Integrating E-Commerce and Data Mining: Architecture and Challenges

We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining. We describe an integrated architecture, based on our expe-rience at Blue Martini Software, for supporting this integration. The architecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80% of the time in knowledge discovery projects. We emphasize the need for data collection at the application server layer (not the web server) in order to support logging of data and metadata that is essential to the discovery process. We describe the data transformation bridges required from the transaction processing systems and customer event streams (e.g., clickstreams) to the data warehouse. We detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and OLAP. We con-clude with a set of challenges.Comment: KDD workshop: WebKDD 200