5/2014 Big Data

Published : 23.05.2013 | Categories: Call For Papers

Special issue
Since Jim Gray started his huge astronomy project at Microsoft to proclaim the age of “data science” in the late 1990s, this approach has proliferated to many other areas beyond the natural sciences. In Information Systems, the 1990s saw the analysis of historical data collected in data warehouses. Soon after, the quasi real-time analysis of high-frequency trading in finance added the data stream aspect to data mining. Search engines, web commerce, and social media have added text mining, social network analysis, and heterogeneous data analysis to the spectrum.

The buzzword „Big Data“ nowadays characterizes analytical systems with extreme data Volume, high data Variety, and rapid data generation Velocity. Even though this buzzword is surely approaching its peak in the Gartner lifecycle, there are many arguments why this trend will continue and even accelerate in the coming years. The Internet of Things accelerates data generation by integrating billions of sensors, the media spectrum is broadened by image, audio, and video, and ever faster multicore and parallel computers produce ever more complex simulation results that need to be administered and analyzed. This offers numerous chances for business, public administration, and all kinds of sciences. But intrinsically, it also increases dependency on systems and allows systems to enter more and more deeply into areas of life that until very recently were unquestionably private. Nationally and internationally, very many research endeavours have begun to explore these new chances and challenges.

The planned special issue wants to contribute to the scientific debate especially of the role of business information systems in this major societal change. We desire contributions from research and practice e.g. on the following themes:

  • Strategic role of big data for competitiveness and service quality
  • Empirical studies of the impact of big data
  • Legal and regulatory aspects of big data
  • Privacy-aware data mining
  • Big data in specific aspects of business such as finance, marketing, logistics, etc.
  • Big data in public sector services and government planning
  • Big data und Cyberphysical Systems in business
  • Data quality and Big Data
  • Role of novel big data technologies such as stream mining, main memory databases, cloud computing, etc.
  • Big data analysis of heterogeneous data sources

The emphasis of submissions should be on data-centric approaches; purely model-centric methods, even if they work with large data sets, are not in the focus of the special issue.

Submission Guidelines
Please submit papers for the sections BISE – Research Paper and BISE – State of the Art by 2013-11-1 at the latest via the journal’s online submission system (http://www.editorialmanager.com/buis/). Please observe the instructions regarding the format and size of contributions to Business & Information Systems Engineering (BISE)/WIRTSCHAFTSINFORMATIK. Papers should not exceed 50,000 characters including spaces, minus 5,000 characters per page for illustrations. Detailed authors’ guidelines can be downloaded from http://www.bise-journal.org.
All papers will be reviewed anonymously (double-blind process) by several referees with regard to relevance, originality, and research quality. In addition to the editors of the journal, including those of this special focus, distinguished national and international professionals with scientific and practical backgrounds will be involved in the review process.

Schedule

Paper submission deadline: 2013-11-1
Author notification: 2014-1-10
First revision due: 2014-2-28
Second author notification: 2014-4-18
Final revision due (one language): 2014-5-23
Final revision due (second language): 2014-6-20

Special Issue Editors
Professor Vasant Dhar Ph.D.
Stern School of Business
New York University, USA
New York, USA
vdhar@stern.nyu.edu

Professor Dr. Matthias Jarke
Information Systems
RWTH Aachen University, Germany
jarke@cs.rwth-aachen.de

Dr. Jürgen Laartz
McKinsey & Company
Juergen.laartz@mckinsey.com