AIMS AND SCOPE
Several trends happening in recent years have significant impact on service oriented computing. Production and processing of large volumes of data (big data) are now a norm in most industries. In order to create value from this data, analytics systems and services turned from a nice to have feature to a necessity. Typically, such analytics services are designed in various forms of rich blending of automated services with humans, including expert work as well as an integration with social systems. Finally, cloud became the major model from the technology point of view (delivery, deployment, implementation) as well as from the business point of view. More recently cyberphysical systems emerge with humans in the loop that are composed of physical entities such as mechanisms controlled or monitored by computer-based algorithms. Big data analytics is important for orchestrating the physical entities along a mission. Humans in cyberphysical systems are supported by big-data analytics in their decision making about mission modifications.
Given this context, we use the term intelligent service clouds as a broad category of (1) cloud deployed, defined, operated or enabled services or ecosystems which may (2) leverage the power of automated and human-centric services, (3) in order to enable creation of insights or value, (4) potentially operating with big data. Here intelligent may refer to many possible capabilities – e.g., the ability to generate insights; or the ability to enable new types or styles of collaborations within or between enterprises; or the ability of services to adapt to changing environments, etc. These trends brought together present new opportunities and challenges for service oriented systems, add new dimensions to services technology, enable new service models when delivering value, call for re-imagining service approaches to integration, composition, data integration and linkage, infrastructure for support massive and scalable data processing as a service.
The workshop on “Intelligent Service Clouds” follows the increasing interest in big data, cloud, analytics services and rich combinations with human driven services. The goal of the workshop is to provide a platform for exploring this exciting landscape and new challenges in the context of intelligent service clouds. It aims at bringing together researchers from various communities interested in the challenges. We will solicit contributions that study fundamental as well as practical aspects. At the fundamental, solution side we will seek approaches that study adequate service models addressing above characteristics, mechanism for specification, discovery, composition, delivery and scaling of intelligent cloud services, data, computational, security and privacy aspects of analytics services, and cloud environments for analytics services, and address specific technical intelligent service-oriented cloud solutions, e.g., analytics; mining, visualization; self-management; security; trust mechanisms; collaboration mechanisms. At the practical, problem side we are interested in case studies in which intelligent service-oriented cloud computing technologies are applied in socio-technical systems/processes like smart logistics, smart manufacturing, healthcare, commerce, public administration, etc.
Expected papers deal with methods, models, techniques, case studies and practical experiences related to intelligent service clouds. Topics of interest to the workshop include, but are not limited to:
- At the solution side approaches that address specific technical intelligent service-oriented cloud solutions for socio-technical systems e.g.
- analytics: mining, visualization;
- privacy and security / trust, privacy and security management in cross-organizational interactions;
- trust mechanisms;
- collaboration mechanisms;
- data model to support Cloud analytics;
- cloud analytics architecture;
- quality of analytics services;
- cloud service composition;
- mixed private/public cloud environments for analytics services;
- system reliability;
- migration to cloud;
- analysis of cloud workloads;
- API challenges
- service models of Cloud analytics
- At the problem side: case studies in which intelligent service-oriented cloud computing technologies are applied
- socio-technical systems/processes like smart logistics, smart manufacturing, or
- analysis of social media data
- analysis of social relationships among participants in business processes and its implications for businesses
- analytics service in emerging domains
- Models, methods, formalisms, and languages that focus on control and coordination of
- cloud services involving cross-enterprise collaboration among business services,
- socially-enhanced services and human-provided services in different domains
- integration of human and automated services
- Ecosystems for service-oriented cloud computing, their secure, dependable and sustainable engineering, maintenance and dissolution.
- Big data in service clouds with data mining for knowledge extraction and information logistics with dynamic mashups.
- Techniques for aligning service clouds operational level to business strategy and high-level goals of an enterprise.
- Extending SOA-formalisms, encapsulations, and constructs to facilitate the definition, dispatch, and orchestration of human cloud services
- IT, middleware, systems, tools, and framework that support smart service clouds
- Human centric approaches to operations and optimization of smart service clouds, such as gamification, collaboration, and crowd-sourcing methods and techniques and their applications
The workshop solicits original research and practice papers on the above topics. Submitted papers will be evaluated according to their rigor, significance, originality, technical quality, and exposition. All papers will be reviewed by at least three members of the program committee.
Full papers are not to exceed 12 LNCS pages including all references and figures. Short papers, up to 6 LNCS pages, can present new ideas and preliminary results. All papers must be prepared in the Springer LNCS format and be submitted electronically in PDF.
Paper submission: July 24, 2016
Acceptance notification: August 14, 2016
Camera ready: August 30, 2016
Workshop: October 10, 2016
Submit using https://easychair.org/conferences/?conf=isc16
PAPER REVIEW AND SELECTION PROCESS
All submissions are reviewed on the basis of relevance, originality, significance, soundness, clarity and quality. Each paper submission is reviewed by three distinct members of the workshop program committee.
We plan to work with ICSOC workshop chairs on preparing the accepted publications for the workshop post-proceedings.
We intend to include the accepted workshop publications in the Springer post proceedings.
PROGRAM COMMITTEE ( preliminary )
- Alexander Wöhrer, Vienna Science and Technology Fund, Austria
- George Feuerlicht, Prague University of Economics
- Claus Pahl, Dublin City University
- Smita Ghaisas, Tata Research Design and Development Center
- Akhil Kumar, Penn State University
- Yuqing Tang, Carnegie Mellon University
- Antonio Brogi, University of Pisa
- Shiping Chen, Networking Technologies Laboratory, CSIRO Australia
- Adrian Mos, Xerox Research, France
- Stefan Schulte, Vienna University of Technology, Austria
- Cesare Pautasso, University of Lugano, Switzerland
To be announced
Dirk Draheim, Large-Scale Systems Group, Tallinn University of Technology, Estonia
Roman Vaculin, IBM T.J. Watson Research, USA
Alexander Norta, Large-Scale Systems Group, Tallinn University of Technology, Estonia
Please contact us at ISC2016workshop AT gmail.com