Workshop on Data Intensive Services based Application (DISA)
Service-oriented architecture (SOA) is a widely accepted and engaged paradigm for the realization of business processes that incorporate several distributed, loosely coupled partners. Today, Web services and the Business Process Execution Language for Web Services (BPEL4WS, BPEL for short) are the established technologies to implement such a service-oriented architecture. The functionality provided by business applications is enclosed within Web service software components. Those Web services can be invoked by application programs or by other Web services via Internet without explicitly binding them. On top of that, BPEL has been established as the de-facto standard for implementing business processes based on Web services.
Aside from business processes, the service-oriented approach using Web services and BPEL is also of great interest for the implementation of data-intensive processes such as, for example, those found in the area of data analytics. Over the recent years, data generated by humanities, scientific activities, as well as commercial applications from a diverse range of fields have been increasing exponentially. Data volumes of applications in the fields of sciences and engineering, finance, media, online information resources, etc. are expected to double every two years over the next decade and further. There is no doubt in the industry and research community that the importance of data intensive computing has been raising and will continue to be the foremost fields of research. As a result, the data intensive services based applications have become the most kind of application in SOA. Also, it has become a hot issue in the academia and industry. Potentially, this could have a significant impact on the on-going researches for services and data intensive computing.
Generally, we define the notion of a data-intensive services based application as a collection of related structured activities or tasks (services) that produce a specific result; huge data sets have to be exchanged between several loosely coupled services in such a data-intensive application. In this case, many new challenges are proposed, for example, the exchange of massive data. Although the preferred XML-based SOAP protocol can meet the communication between Web services, it is not efficient enough in those scenario settings. DISA focuses on the challenges imposed by data-intensive services based applications, and on the different state-of-the-art solutions proposed to overcome these challenges. The aim of DISA is to encourage academic researchers and industry practitioners to present and discuss all methods and technologies related to research and experiences in a broad spectrum of data-intensive services based applications.
The topics of the workshop include but not limited to:
(1) Data intensive services representation
- Modeling of data intensive services
- Reference models for data intensive services
- Semantic models for data intensive services
- Logistics Ontology for data intensive services
- Integrating data intensive services models with Web service models
- Repositories and dictionaries for data intensive services
- data intensive service data integration
(2) Data intensive services based application building, management and coordination
- data intensive service design and engineering
- data intensive service composition, orchestration and choreography
- data intensive service runtime management and monitoring
- Services for managing decentralized data intensive services
- data intensive service quality aspects and their management
- Negotiation protocols for data intensive services
- Market-based coordination of data intensive services, i.e., auctions, exchanges
- Modeling, simulation and optimization of data intensive services
- Verification of data intensive services
- Transactional safeguarding of data intensive services
- Service-oriented architectures for the setup and enactment of data intensive services
- Mashups and data intensive services
- Agents for the lifecycle management of data intensive services
- Performance aspects of data intensive application
(3) SLA Management
- Languages for describing SLAs for data intensive services along and across value chains
- Semantic annotation of SLA for data intensive services
- SLA negotiation for data intensive services
- SLA monitoring for data intensive services
- Integrating data intensive services into SLA management infrastructures
4) Case studies and demos
- Industry-specific case studies on service-oriented computing
- Innovative research prototypes and demonstrators
- Empirical research on service-oriented computing
Workshop Chairs
Prof. Ying Li, Professor, Zhejiang University, China
Prof. Honghao Gao, Shanghai University, China