[AISWorld] CFP HICSS Minitrack: Data Science for Collaboration

[Lakshmi Iyer]

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 at gmail.com, Nova Southeastern University
Lakshmi Iyer -  Lsiyer at uncg.edu, The University of North Carolina at
Greensboro
Lina Zhou -      zhoul at 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 at 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)