[AISWorld] 2nd CFP: HICSS 51 (2018)-Mini-track on Data Science and Digital Collaborations

Lakshmi Iyer lsiyer at uncg.edu
Sun Apr 2 20:37:19 EDT 2017


Call For Papers: HICSS 51 (2018)-Mini-track on *Data Science and Digital
Collaborations*

For *Collaboration Systems and Technologies Track*

*Hawaii International Conference on System Sciences*

HICSS-51: January 3-6, 2018 | Hilton Waikoloa Village, Big Island, Hawaii

*Call for Papers*
Data science and analytics for collaboration is the study of generalizable
extraction of knowledge from structured and/or unstructured data to support
human collaboration within and across groups and organizations. The new
actionable knowledge gained is expected to support achieving collaborative
goals such as innovation, idea generation, decision making, negotiation,
and execution. Data science and analytics 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, engineering effective
solutions to the collaboration problems, and ways to effectively
communicate findings across roles ranging from business managers to data
analysts. There is an explosive 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 by investigating how data science
and analytics can facilitate collaboration both internally and externally.
For example, businesses are trying to understand how data science and
analytics can help engage customers and improve operation efficiency and
how it can use social media to support corporate knowledge management.
Another example is collaborative generation and creation of ideas and
solutions through crowdsourcing and online communities (such as
dominodatalab.com). Access to heterogeneous, voluminous, and unverified
data presents both new opportunities and challenges for addressing
collaboration problems. Yet another example is the collection of data by
the public around the world which is then used by scientists working on
Genographic data by National Geographics.

Topics of interest include, but are not limited to:

·         Challenges and opportunities of data science for collaboration

·         Analysis of big data for collaboration

·         Collaboration across organizations for social impact through
analytics

·         Collection, aggregation, and organization of collaborative big
data

·         Managing heterogeneous big data from collaborative sources

·         Visualization of collaborative big data

·         Data science for collaborative work (decision making, problem
solving, negotiation, and creativity/innovation)

·         Data science and analytics for inter-organizational collaboration

·         Crowdsourcing analytics for collaborative tasks

·         Security and privacy issues in collaborative data science

·         Data science in collaborative creation or innovation

·         Human factors in applying data science for collaboration

·         Team building in data science for collaboration

·         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.

·         Knowledge discovery from collaborative data in social media

·         Analysis of collaborative social networks

** IMPORTANT DATES:**

Paper Submission Deadline:              June 15, 2017, 11:59 p.m. HST

Notice of Acceptance/Rejection:        August 17, 2017

Final Manuscripts for Publication Due: September 22, 2017

Deadline for at least one author to register: October 1, 2017



*Submission:* See details on HICSS website: http://hicss.hawaii.edu/
tracks-and-minitracks/authors/



*Mini-track Co-Chairs*

Lakshmi S. Iyer

Information Systems and Supply Chain Management (ISSCM) Department

The University of North Carolina Greensboro

Lsiyer at uncg.edu



Souren Paul

College of Engineering and Computing

Nova Southeastern University

Souren.paul at gmail.com





Lina Zhou

Information Systems Department

University of Maryland Baltimore County
zhoul at umbc.edu

--
Lakshmi S. Iyer, Ph.D.
Director of Information Systems and Supply Chain Management Graduate
Programs
The University of North Carolina at Greensboro
Email: Lsiyer at uncg.edu; Phone: 336/334-4984 <(336)%20334-4984>; Fax:
336/334-5580 <(336)%20334-5580>
URL: http://lsiyer.wp.uncg.edu/
*Women in IT - http://wiit.uncg.edu <http://wiit.uncg.edu/>*, www.
facebook.com/wemakeIT <http://www.facebook.com/wemakeit>
http://greensboro-nc.aauw.net/techevents/



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