-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] ISF Special Issue on Big Data and Analytics - Submission Deadline Extended to Oct 15, 2015 Datum: Wed, 30 Sep 2015 18:04:03 -0400 Von: Deokar, Amit deokar.amit@gmail.com An: aisworld@lists.aisnet.org

Information Systems Frontiers (ISF) Journal Call For Papers: A Special Issue on “Big Data and Analytics for a Better World”

*** NEW : Submission Deadline Extended to Oct 15th, 2015. ***

Background: The recent explosion of big data has radically changed the way managers can measure and gain insights about their businesses (McAfee and Brynjolfsson 2012). Application analytics and big data approaches enable measurement and creation of knowledge that helps organizations make effective decisions and gain high performance in various business functions. The adoption of a data driven culture and the use of big data approaches for decision-making has the potential to lead organizations towards sustainable competitive advantage and productivity gains (Watson 2014).

As organizations in various sectors re-formulate IT strategies and investments for the evolving market, it is imperative to understand how big data can be used effectively for decision-making purposes. Companies are actively seeking for mechanisms to outrun their competitors through analytics driven innovation. For example, companies are strategizing to increase their customer base by developing a better and deeper understanding of customer needs through big data analytics.

Scientific community has a strong focus on understanding the paradigm shifts resulting from increased use of big data from multiple sources for decision-making. The management, processing and use of these large data sets present new challenges for organizations and society. Consequently, big data has become fertile grounds for further development of new areas that will lead to improved functioning of various components of society. Beyond organizational impact, analytics is starting to play a critical role in non-profits, non-government and government entities to address several social and global challenges. As a result, there is considerable interest worldwide in examining how big data and related new computing paradigms can improve or alter processes and core functionalities while improving outcomes and key performance indicators.

This special issue of Information Systems Frontiers on ‘Big Data and Analytics for a better world’ seeks theory building, design science, behavioral research and emerging applications in innovative areas of big data use, analytics, and decision support. Topics of interest include, but not limited to:

- Energy analytics – sustainability, smart grid, etc. - Health care analytics – personalized medicine, population health management, smart HIT systems, fraud prevention, etc. - Analytics for improved disease management, diagnostics, endemics, and rural health - Analytics in developing and underdeveloped nations, smart resource sharing and allocation - Analytics for climate and weather, environment and pollution management - Analytics for open government and data portals - Big data approaches applied to improve cognitive performance and reduce the dark side of technology, (e.g. information overload, techno stress, technology addiction, etc.). - Application of analytics for global development - Security and privacy in the social media and big data context; - Case studies utilizing disparate and big data emphasizing on high global and societal impact or problems of high value; - Application of social network analysis (SNA) on big data in collaborative systems, - Transportation and traffic safety

A major focus of the issue will be on novel and high impact problems having a positive impact on global and societal issues. However, the special issue will also solicit original research on topics related to innovative design and development of analytics models as applied to solve such problems using approaches including but not limited to:

- Analytics for Decision Support: visual analytics; data warehousing; OLAP and executive support; big data and large-scale data storage; in-memory analytics;. - Analytics for smarter Knowledge management: smart expert systems applications using data from disparate sources and methodologies such text mining, data mining, rule-based systems, semantic web technologies to address specific decision support needs; mobile technologies. - Predictive Analytics and descriptive analytics applied to large scale datasets. - Document-driven Analytics: knowledge coding, analysis, search and retrieval for decision support for a variety of devices (e.g., tablets, smartphones). - Analytics using social media, identifying socio-technical gaps, benefits and challenges for collaboration in Big Data; novel storage and management approaches for big data; - Decision Outcomes and Performance Evaluation: effects of using decision technologies, designing for improved decision performance; metrics for data warehousing, BI, and analytics.

Projected Time Line: Deadline for original submissions: Oct 15, 2015 Final notifications to authors: July 15, 2016

References McAfee, Andrew and Erik Brynjolfsson. (2012) "Big Data: The Management Revolution". Harvard Business Review, October. Watson, Hugh J. (2014) "Tutorial: Big Data Analytics: Concepts, Technologies, and Applications," Communications of the Association for Information Systems: Vol. 34, Article 65.

Special Issue Guest Editors: Lakshmi Iyer, University of North Carolina Greensboro (UNCG), lsiyer@uncg.edu Ashish Gupta, University of Tennessee Chattanooga, gupta@utc.edu Amit Deokar, Penn State University Erie, avd108@psu.edu Ramesh Sharda, Oklahoma State University, ramesh.sharda@okstate.edu Dave Schrader, Teradata University Network, drdaveschrader@gmail.com _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org