-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP HICSS Minitrack: Data Science for Collaboration Datum: Mon, 4 May 2015 09:14:50 -0400 Von: Lakshmi Iyer lsiyer@uncg.edu An: aisworld@lists.aisnet.org Kopie (CC): Souren Paul spaul@nova.edu, zhoul@umbc.edu zhoul@umbc.edu
Call for papers
January 5-8, 2016 Grand Hyatt, Kauai http://www.hicss.hawaii.edu
HICSS2016 Minitrack: Data Science for Collaboration (Collaboration Systems and Technologies Track)
Data science for collaboration is the study of the generalizable extraction of knowledge from data to support human collaboration within and across groups and organizations. The new knowledge gained is expected to be actionable for achieving collaborative goals such as generating, choosing, negotiating, and executing. Data science for collaboration couples a systematic study of collection, aggregation, organization, processing, and analysis of data. In addition, it requires deep understanding of formulating problems valuable for collaboration, engineer effective solutions to the collaboration problems, and ways to effectively communicate findings across roles ranging from business managers to data analysts. There is exploding interest in organizations looking for ways to increase value from data science and using it to address business challenges. One promising way for businesses and organizations to enhance their performance or competitiveness is investigating how data science can facilitate collaboration both internally and externally. We welcome technical, empirical, and behavioral research that cover various aspects of data science for collaboration.
Topics of interest include, but not limited to:
· Challenges and opportunities of data science for collaboration · Collection, aggregation, and organization collaborative Big Data · Managing heterogeneity of collaborative big data · Visualization and presentation of collaborative big data · Data science for collaborative work (decision making, problem solving, negotiation, and creativity/innovation) · Data science for internal collaboration in groups and organizations · Data science for inter-organizational collaboration · Crowdsourcing for collaborative tasks · Security and privacy in collaborative Data Science · Data science in collaborative creation · Case studies on Data science for Collaboration: Adaptive collaboration systems that feature modeling, collaboration, and advanced analytics to detect patterns, make sense, simulate, predict, learn, take action, and improve performance with use and scale. · Application of control-theoretic models to interactions among social entities · Application of survival models to predict hazard rate of computer supported social processes · Application of N-person game theory in problems arising from unregulated use of collaboration systems · Knowledge extraction from collaborative data in social media · Social network analysis (SNA) of collaboration big data* · Data science applications in assessing risks in financial systems and interdependent critical infrastructures · Analytics for data-driven operations management · Data science application for smart cities · Analytics for healthcare delivery
IMPORTANT DATES June 15, 2015 Submission full manuscripts August 15, 2015 Acceptance Notifications September 15, 2015 Submission camera-ready paper October 1, 2015 Early Registration fee deadline
For formatting and submission instructions, see HICSS website. http://www.hicss.org/#!author-instructions/c1dsb
Minitrack Co-Chairs:
Souren Paul - Souren.paul@gmail.com, Nova Southeastern University Lakshmi Iyer - Lsiyer@uncg.edu, The University of North Carolina at Greensboro Lina Zhou - zhoul@umbc.edu, University of Maryland Baltimore County
Regards, Lakshmi ------ Lakshmi S. Iyer, Ph.D. Associate Professor and Information Systems Graduate Programs Director The University of North Carolina at Greensboro Email: Lsiyer@uncg.edu; Phone: 336/334-4984; Fax: 336/334-5580 URL: http://lsiyer.wp.uncg.edu/ Women in IT - http://wiit.uncg.edu, www.facebook.com/wemakeIT Global IT conference; AMCIS 2015; 2015 Business Analytics Congress; ICIS 2015 DAS Track #12 MS in IT Program (Online) in the U.S. (US News, 2015) _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org