Every day, quintillions of bytes of data are created in different domains, including Internet, healthcare, retail and so on. The term “big data” is used to describe such data, which has three major characteristics: large volume, high speed of data flow and heterogeneous data types. Studies have shown that leveraging knowledge from big data via analytics will generate tremendous value and business impact. For example, the increasing interest of turning massive volumes of social media data into meaningful insights attracts significant attention to this field. Indeed, the use of big data has already become a key basis of competition for enterprises.

With the needs of analytics growing at ever increasing speeds, it becomes clear that traditional data processing techniques are in no way able to meet the demands. The use of big data has raised tremendous challenges on analysis techniques, e.g., data integration and linkage, data storage, pattern mining, IT infrastructure to support massive and scalable data processing, and visualization of the analysis results. Therefore, Cloud Computing becomes a perfect candidate for delivering big data analytics. However, the emerging Cloud Computing technology adds another interesting dimension in this complex area since Cloud technology enables a new service model when delivering analytics to end users.

The proposed full-day workshop on “Analytics Services on the Cloud” follows the increasing interests in big data and analytics services and aims at bringing together researchers from various communities who are interested in the challenges. We will solicit contributions that study practical as well as fundamental aspects of cloud-based analytics services including adequate service models that address characteristics and challenges of analytics services with big data, mechanism for specification, discovery, composition, delivery and scaling of analytics services, data, computational, security and privacy aspects of analytics services, and cloud environments for analytics services.

Topics of Interest

Expected papers deal with methods, models, techniques, case studies and practical experiences related to the analytics services on the Cloud. Topics of interest to the workshop include, but are not limited to:

Benchmarking
Scalability
Service model of Cloud analytics
Data model to support Cloud analytics
Cloud analytics architecture
Quality of analytics services
Analytics service composition
Privacy and security
Mixed private/public cloud environments for analytics services
Storage and access methods
Parallel analytics
Visualization
System reliability
Migration to cloud
Analysis of cloud workloads
Analysis of social media data
Analytics service in emerging domains


Best Paper Award

Among all the submissions, one outstanding paper will be selected for the best paper award. The award is sponsored by IBM Research and will be announced at the workshop award ceremony.

Submission Guidelines

All papers should be submitted electronically in PDF to the submission system EasyChair. All submissions must be prepared in the Springer LNCS format and should not exceed 12 pages including all references and figures. Each paper submission is reviewed by three distinct members of the workshop program committee on the basis of relevance, originality, significance, soundness, clarity and quality. The accepted workshop papers will be published in Springer LNCS as post conference proceedings.