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Title: Big Data Analytics: Concepts, Methods, Techniques and Applications
Co-Chairs: Stephen H. Kaisler; Frank Armour; J. Alberto Espinosa
HICSS is turning 50!!
Big Data Analytics: Concepts, Methods, Techniques, and Applications
This minitrack focuses on the use of big data and analytics to enable
businesses and organizations to optimize their operational practices,
improve their decision-making, and better understand and provide more
effective services to their customers and clients. We seek papers in all
areas of big data and analytics, including storage, management, usage case
studies, innovative applications, and enabling technology. Relevant
papers on the development of strategy for deploying big data and analytics
in distributed organizations, the effects of big data and analytics on
organizational behavior, and the development of big data analytics are
sought. Papers are sought on developing an analytic cadre, including
curriculum concepts, in-house training, and skills development and
measurement.
In our book titled: ?Obtaining Value from Big Data for Service Delivery?
we presented knowledge framework to serve as a basis for grounding Big
Data and Business Analytics curricula. The framework is composed of key
knowledge layers, including: basic foundations (e.g., mathematics,
statistics, software programming, big data architectures); analytics/big
data (e.g., descriptive, predictive, prescriptive and visual analytics);
functional domain of analysis (e.g., marketing, healthcare, accounting
forensics, etc.); and managerial, strategic and organizational aspects
(e.g., data governance, security, privacy, human resource management, the
business value of big data and analytics investments, etc.). In order to
advance knowledge in big data and analytics, we must develop active
research agendas in all five layers. We seek research papers on any of
these five layers and also those that address the structure and evaluation
of curriculum design, implementation and evaluation for big data and
analytics.
Papers are solicited in several areas, including, but not limited to the
following:
- Challenges in managing big data repositories and projects, including
data governance
- Graph analytics ? both syntactic and semantic ? that play a big role in
the exploitation of social media data
- Advanced analytics, ? emphasizing visual analytics and non-numeric
analysis models and their implementation
- Scalable semantic annotation and reasoning across big data stores
- Metrics for assessing the impact of big data in business, scientific,
and governmental decision-making.
- Advances in analytics in specific functional domains
- Managerial, strategic and organizational aspects of big data and
analytics.
Papers presenting case studies, infrastructure and technology advances,
theoretical perspectives at the petascale and beyond, and emerging
concepts are also sought.
More information about HICSS-50 may be found at http://www.hicss.org/.
If you wish to discuss a paper concept before submitting a paper, please
contact Steve Kaisler or Frank Armour. We will be happy to discuss your
paper concept with you.
Kindly,
Minitrack Co-Chairs
Stephen H. Kaisler, D.Sc. (Skaisler1@comcast.net)
SHK & Associates
Frank Armour, Ph.D. (farmour@american.edu)
J. Alberto Espinosa, Ph.D. (alberto@american.edu)
Kogod School of Business
American University
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