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Journal of Big Data (Springer) 2015 : Special Issue on Service Provisioning in the Big Data Era

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Link: http://cs.adelaide.edu.au/~qsheng/bigservice-cfp.pdf
 
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Submission Deadline May 31, 2015
 

Call For Papers

As an overwhelming amount of data is generated at a faster rate every day from all sources, and applications such as cloud services, Web of Things (WoT), social network services and intelligent terminals, it has become more urgent than ever to design, deploy and provision services more wisely so that the provisioned services could support effective acquisition, storage, transformation, management and utilization of such data. Manipulating and getting the most out of the Big Data can bring unprecedented value and new opportunities that are critical to business success. Services should be ideally provisioned in a way that speeds up data processing, scales up with data volume, and improves the adaptability and extensibility over data diversity and uncertainties, and finally turns low-level data into actionable knowledge towards better understanding and manipulation of the Big Data. Big Data requires services across various domains, heterogeneous networks and cyber-physical worlds to be aggregated, interoperated, and linked together into a massive and complicated collaborative service ecosystem which could in turn handles the challenging issues of Big Data.


TOPICS OF INTEREST

This special issue aims at presenting the latest developments, trends, and research solutions of service
provisioning in the Big Data era. Topics of interests include, but are not limited to:
- Efficient models and solutions for querying and processing Big Data
- Service modeling, delivery, deployment and evolution for Big Data
- Analytic services for Big Data
- Big Data as a Service
- Business analytics & Big Data practice
- Privacy Preserving Big Data analytics and services
- Linked data and linked services
- Knowledge discovery over massive datasets
- Social sensing and social network services
- Reasoning over uncertain data and unreliable services
- Mashup services and data integration
- Crowdsourcing services
- Web of Things services
- Service ranking and recommendation for Big Data
- Credibility of data provisioning services

Articles will benefit from the advantages of open access publication, including:
- Rapid publication: Online submission, electronic peer review and production make the process of
publishing your article simple and efficient.
- High visibility and international readership in your field: Open access publication ensures high visibility
and maximum exposure for your work - anyone with online access can read your article
- No space constraints: Unlimited space for figures, extensive data and video footage.
- Authors retain copyright, licensing the article under a Creative Commons license: Articles can be freely
redistributed and reused as long as the article is correctly attributed.


SUBMISSIONS

Before submitting your manuscript, please ensure you have carefully read the Instructions for Authors for Journal
of Big Data (http://www.journalofbigdata.com/authors/instructions). The complete manuscript should be
submitted through the Journal of Big Data submission system (http://www.journalofbigdata.com/manuscript). To
ensure that you submit to the correct special issue, please select the appropriate section in the drop-down menu
upon submission. In your cover letter, please also clearly mention the title of the SI. All submissions will undergo
rigorous peer review and accepted articles will be published within the journal as a collection.
Important Dates
- Paper submission deadline: 31/05/2015
- 1st round review due: 15/08/2015
- 1st revision due: 30/09/2015
- 2nd round review due: 15/11/2015
- 2nd revision due: 15/12/2015
- Final due: 31/12/2015


Guest editors

Michael Sheng, The University of Adelaide, Australia, michael.sheng@adelaide.edu.au
Xiaofei Xu, Harbin Institute of Technology, China, xiaofei@hit.edu.cn
Xianzhi Wang, The University of Adelaide, Australia, xianzhi.wang@adelaide.edu.au
Athanasios V. Vasilakos, National Technical University of Athens, Greece, vasilako@ath.forthnet.gr

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