-------- Forwarded Message --------
Second Call for Papers
Hawaii International Conference on System Sciences
HICSS-52: January 8-11, 2019 | Grand Wailea, Maui
Deadline for submissions: June 15, 2018
Minitrack:
BIG DATA, DATA SCIENCE AND ANALYTICS MANAGEMENT, GOVERNANCE AND
COMPLIANCE
Track:
Organizational Systems and Technology
Big Data, data science and analytics have become increasingly
important strategic assets because they can help organizations
make better decisions, discover new insights, competitively
differentiate, and they enable the embedding of intelligence into
automated processes so organizations can efficiently respond at
the speed of business. They can also provide inter-organizational
partnerships with sharable, actionable insights leading to
significant innovation. Organizations need new theories,
frameworks and methodologies that can help them:
* Realize strategies and principles for managing Big Data
* Streamline processes to develop and deploy analytical models and
machine learning algorithms
* Design new KPIs and deploy actionable dashboards
* Manage and staff data science teams
* Structure and coordinate analytics functions/capabilities within
organizations
* Design, staff and provide direction to data and analytics
governance committees
* Manage project and deployment risk, and
* Advance analytics capability maturity
What is new? Organizational roles like Chief Data Officer and
Chief Analytics Officer are emerging. Funding models for
prioritizing analytics opportunities are more frequently being
discussed. Centers of Excellence and shared services entities are
being created to handle and manage an increasing data science
workload. New agile methodologies are emerging, and building an
organization-wide culture of evidence-based management is becoming
a competitive necessity. Big Data resource investment decisions
are becoming more complex with the emergence of the Internet of
Things.
Effective organizational management and governance of data
analytic practices are necessary in order to mitigate risks
associated with analytics deployment. Organizations need to
capture and manage critical meta-information detailing modeling
and environmental assumptions underlying analytics solutions, and
they need to establish policies and a culture designed to ensure
adherence to the highest ethical standards of data management and
predictive model deployment. In addition, organizations need new
legal analytics tool familiarity and to understand the role of
legal analytics in compliance. Unleashing machine learning
algorithms that may take on a life of their own may require
safeguards and risk mitigation monitoring.
This minitrack welcomes submissions of original work addressing
challenges, theoretical lenses, frameworks, development ideals,
evaluation methodologies, strategies and impact studies assessing
the implications of Big Data, data science and analytics
management, governance, and compliance. We also encourage
submissions of research-in-progress as well as those that are
practically oriented yet have the potential to make significant
contributions to the research community.
Relevant topics for the minitrack include, but are not limited to,
the following:
* Innovative Big Data, data science and analytics governance
approaches
* Chief Data Officer and Chief Analytics Officer roles and
responsibilities
* Data, analytical model and algorithm asset management
* Analytics workflow management
* Analytic model life-cycle management
* Model management platform design
* Model compliance management
* Model documentation
* Ethics of data analytics
* Analytics regulatory risks and risk mitigation
* Data and model transparency
* Business value of analytics governance
* Platform economics and strategy
* Coordinate IT, analytic and client teams
* Analytics documentation and metadata design
* Legal implications of analytics governance policies
* Organizational implications of advances in the field of legal
analytics
* Managing and deploying champion and challenger models
* Campaign documentation and model reuse
* Data and model ownership and contracts
Minitrack Co-Chairs:
Michael Goul (Primary Contact)
Arizona State University
Michael.Goul@asu.edu<mailto:Michael.Goul@asu.edu>
Zhongju Zhang
Arizona State University
Zhongju.Zhang@asu.edu<mailto:Zhongju.Zhang@asu.edu>
Jeffrey Saltz
Syracuse University
jsaltz@syr.edu<mailto:jsaltz@syr.edu>
Michael Goul
Associate Dean for Faculty & Research
W. P. Carey School of Business
Arizona State University
Michael.Goul@asu.edu<mailto:Michael.Goul@asu.edu>
p.480.727-6031 BAC 600
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