Scope and Vision:

Big Data computer and service is becoming a very hot research and application subject in academic research, industry community, and government services. Today, with the fast advance of big data science, analytics and technology, big data researchers and application professionals are able to access to diverse data mining and machine learning algorithms, open-source platforms & tools, and cloud DB technology and big data access technologies.

According to IDC’s prediction in 2013, the market for big data will reach $16.1 billion in 2014, growing 6 times faster than the overall IT market. This kind of business analysis reports brings great business opportunities and strong research interests among both academic and industry communities. Recently, a number of IEEE international conferences are organized focusing on Big Data Computing, Big Data Sciences and Analytics, and Big Data Technology and Engineering. Since emergent big data computing and services can be used in many disciplines and diverse applications, including business management, library science, energy and environment, education, biomedical, and healthcare and life science, social media and networking, smart city and travel, and transportation, etc.

Establishing and conducting successful big data projects in different domain applications require the following essential and critical entities:
-Various big data banks and resources with quality data collection, validation, evaluation and certification methods and standards
-Scalable and efficient big data computing services
-Well-defined domain-specific big data knowledge engineering and analytic intelligence
-Well-developed big data infrastructures supported with high-quality big data DB technologies and tools

Unlike the other venues, this international conference is established to address the above needs for big data computing service researchers, domain-specific researchers, government agencies, and practitioners. The major objective is to provide a big platform for them to exchange innovation ideas and research results, and share application experiences and lessons.

The three major objectives of this conference include:
-Big Data Innovation of big data computing and service models, theories, tools, solutions and technologies
-Big Data and Service Sharing in big data banks and resources, portals, platforms, and open-sources, technology and tools
-Big Data Application in real world big data application service projects for major application domains, including energy and environment, medical and healthcare, library, social media and networking, and education.

This conference will include a three-day program with a well-defined track program, plus a number of invited keynote speeches from well-known speakers from the real world, as well as a CLOUD TECH SUMMIT with big data sessions.

Conference Tracks:

This conference seeks to research papers all aspects of mobile cloud computing, engineering, and service, including but not limited to:

Research Tracks on Innovation:

(a)Big Data Computing and Service
Big data scalable computing models, theories, and algorithms
Big data service models, collection, validation, analysis, and visualization
Big data service frameworks, platforms, solutions and tools
Big data computing infrastructures, platforms, and SaaS
Big data computing service businesses, billing, protocols, APIs
Big data-as-a-service (Big DaaS)
Big data security, privacy, and services
Mobile big data computing and services
Big data add-value computing services

(b)Big Data Modeling, Sharing Technologies and Platforms
Big data modeling and banking methods in data indexing, classification, integration, merging, and migration
 Big Data DB, CLOUD DB, and NOSQL DB, and Hadoop solutions and technology
Big Data policies, processes and standards in collection, store, accesses, and sharing
Big Data validation, certification, and quality assurance
Big Data sharing and access protocols, methods, processes, and platforms and technologies

(c)Big Data Intelligence and Knowledge Engineering
Innovative, concurrent, and scalable big data intelligence analysis
Big data knowledge extraction, discovery, analysis, presentation, and visualization
Big data knowledge integration, merging, migration, and transformation
Big data based reference, ranking, decision making, and prediction
Big data knowledge indexing, classification, sharing, and assembly
Big data knowledge-based open-source development and technology
Big data based knowledge system development and tools

(d)Big Data Center and Enable Technologies:
New big data storage infrastructures, hardware technologies
Innovation big data storage and cloud management systems and solutions
Big data search, access methods and algorithms
Big data collection sensors, networks, devices, and solutions
Big data security solutions
New big networking infrastructure, systems, and protocols
Green computing for big data centers
Big data management and deployment systems and solutions

Domain Application Tracks:

-Big Data Information Banking - This track includes the papers focusing on big data information banking projects, policies, standards, business services & cost models, data sharing & exchange protocols, data classification/indexing and search solutions, and supporting infrastructures.

-Energy and Environment – This track includes the papers focusing on energy and environment big data modeling applications. The typical subjects include big data based energy and environment control, evaluation and management, monitoring & altering, protection & prediction.

-Bio-Medical and Healthcare Services – This track includes the papers focusing on bio-medical and healthcare services and applications based on big data. Typical topics include big data research and project experience in bio-medical and health care application services.

-Big Data Education and Learning – This track includes the papers focusing on big data education and learning in service systems, programs, and project experience reports in energy and environment control, evaluation and management, monitoring & altering, protection & prediction.

-Multi-media and Social Networking - This track includes the papers focusing on big data research application and service systems in multi-media and social networking.

Reviews, Survey Papers, and Application Experience Reports:
•Survey/review reports on big data computing, services, and engineering
•Industry and government experience reports on big data projects and applications

Important Dates:

Abstract submission: 11/01/2014
Paper submission: 11/15/2014
Review notification: 12/15/2015
Camera Ready and registration: 01/15/2015
Conference Date: (03/30-4/03/2015)
3/30/2015 Shared Workshop and Tutorial Day
3/31/2015-4/3/2015 Conference

Paper Submission:

Format: Please submit papers in PDF format through IEEE BigDataService 2015 web site. Manuscript should be prepared following the IEEE Computer Society Press Proceedings Author Guidelines (http://www.computer.org/portal/pages/cscps/cps/cps_forms.html).

Page Limit:

Research Paper: 10 pages (in IEEE Format)
Papers in the class will be evaluated by the relevance, significance, originality, clarity, and technical merit.

Project Experience and Case Study Report: (up to 6 pages)
Papers in this class will be evaluated by the relevance, clarity, and value to the research community

Survey/Tutorial Papers: 10 pages
Papers in this class will be evaluated by the coverage of the up-to-date literature, relevance, soundness, technical validity, insightful discussion, timeliness, well-structure and clarity.

Publication:

All accepted papers will be included in the symposium proceedings, which will be published by the IEEE Computer Society Press and included in the IEEE Digital Library. At least one author of each accepted paper must attend the symposium to present the work.

Journal Special Issue:

We plan to publish a special journal issue for the extended and revised versions of selected best papers which will be published as a special issue for the Journal of Frontier of Computer Science.