Big Data and Analytics: Concepts, Methods, Techniques and Applications Minitrack

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 services to their customers and clients. It seeks papers in all technical areas of big data and analytics, including: technology and infrastructure, storage, management, usage case studies, innovative applications, innovative uses of tools to solve complex problems using big data, metrics for assessing big data value, and enabling technology. It also seeks papers and case studies in relevant organizational and management areas associated with effective big data and analytics practices, including: strategy, governance, security, human resources, work coordination, business process and business impact, among others. Relevant papers on the development of strategy for deploying big data and analytics in distributed organizations – including geographic and virtual entities, the effects of big data and analytics on organizational behavior, and the development of big data analytics are sought. Additionally, papers are sought on developing an analytic cadre, including curriculum concepts, in-house training, and skills development and measurement.

We solicit 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 business analytics; begin to identify ways to measure the organizational benefits derived from using and analyzing Big Data; present case studies of Big Data implementation and use; address the design and development of analytical frameworks that incorporate multiple analytic methods and techniques based on different architectures and technologies; and address the organizational and business aspects of big data and analytics.

Papers will be solicited in several areas, including, but not limited to the following:

  • Challenges in managing big data repositories and projects
  • 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 as applied to complex problems in different domains
  • Scalable semantic annotation and reasoning across big data stores
  • Metrics for assessing the impact of big data in business, scientific, and governmental decision-making
  • Organizational and business aspects of big data, analytics and data science
  • Crowdsourcing as a distributed, complex analytic tool

Minitrack Co-Chairs:

Stephen Kaisler (Primary Contact)
SHK & Associates

Frank Armour
American University

Alberto Espinosa
American University

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