[AISWorld] HICSS 47 Call for Papers Mini-Track: Big Data: Challenges, Opportunities and Realities

[Alberto Espinosa]

Title: Big Data: Challenges, Opportunities and Realities

Introduction:

Big Data focuses on databases and files with volumes in the tera- (1012) 
to exabytes (1015) currently, but trending towards zettabytes (1018). Big 
data databases and files have scaled beyond the capacities and 
capabilities of commercial database management systems. Structured 
representations become a bottleneck to efficient data storage and 
retrieval. Gartner has noted four major challenges (the four Vs): 
increasing volume of data, increasing velocity (e.g., in/out and change of 
data), increasing variety of data types and structures, and increasing 
variability of data. We have suggested a fifth V: value, which is the 
contribution big data has to decision making. Add to these the increasing 
number of disciplines and problem domains where big data is having an 
impact and one sees an increase in the number of challenges and 
opportunities for big data to have a major impact on business, science, 
and government.

Big Data analysis appears to be an emerging discipline in need of 
distinguishing methodologies and tools. The challenges and opportunities 
have multiplied over the past two yeas and continue to grow. As the 
plethora of data grows, new methods for processing and understanding this 
data to provide actionable information for decision-makers are required 
that match the domain knowledge and problems of fields with specific 
missions and constraints. New metrics are required to assess its impact on 
decision-making in each domain where success is defined in mission based 
terms.

This mini track is soliciting paper submissions that: advance our 
knowledge of Big Data storage and structure; help us learn about effective 
processes and approaches to effectively manage Big Data and the associated 
analytics; and begin to identify ways to measure the organizational 
benefits derived from using and analyzing Big Data. Papers will be 
solicited in several areas, including, but not limited to the following: 

•       Innovative structures and techniques for big data representation 
(including RDF, RDFS, audio, image, video, etc.)
•       Graph analytics – both syntactic and semantic
•       Business Analytics – to include business intelligence as it uses 
big data
•       Advanced analytics, including applications of the MapReduce and 
Message-Passing Interface (MPI) paradigms for implementing analytics
•       Mechanisms for annotating big data with semantic information
•       Scalable semantic reasoning across big data stores
•       Challenges in using and analyzing big data
•       Case Studies of big data implementations
•       Innovative visualization algorithms and techniques for big data
•       Challenges in managing big data repositories and projects using 
emerging tools and accessing such repositories using new languages (such 
as Pig, Jaql, etc.)
•       Metrics for assessing the impact of big data in business, 
scientific, and governmental decision-making.

If you have any questions, please contact the primary co-chair.

HICSS-47 offers a unique, highly interactive and professionally 
challenging environment that attendees find "very helpful -- lots of 
different perspectives and ideas as a result of discussion." HICSS 
sessions are comprised primarily of refereed paper presentations; the 
conference does not host vendor presentations. HICSS is sponsored by the 
Shidler College of Business a the University of Hawai’i at Manoa and the 
IEEE Computer Society.

CoChairs: 

Stephen Kaisler, skaisler1 at comcast.net, Primary Co-chair
Frank Armour, fjarmour at gmail.com
Alberto Espinosa, alberto at american.edu
William H. Money, wmoney at gwu.edu

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