[AISWorld] Call For Papers: HICSS-Mini-track on Data Science and Analytics for Collaboration

[Souren Paul]

Mini-track on Data Science and Analytics forCollaborationCollaboration Systemsand Technologies Track HawaiiInternational Conference on System Sciences
HICSS-50: January 4-7, 2017 | Hilton Waikoloa Village

Deadline for submissions: June 15, 2016
Website: www.hicss.hawaii.eduWithexplosive growth in unstructured and structured data, organizations are lookingfor ways to innovate through the use of data science and analytics. Datascience and analytics for collaboration is the study of generalizableextraction of knowledge from data to support human collaboration within andacross groups and organizations. The new knowledge gained is expected to beactionable for achieving collaborative goals such as generating, choosing,negotiating, and executing. Data science and analytics for collaborationcouples a systematic study of collection, aggregation, organization,processing, and analysis of data. In addition, it requires deep understandingof formulating problems valuable for collaboration, engineer effectivesolutions to the collaboration problems, and ways to effectively communicatefindings across roles ranging from business managers to data analysts. There isexploding interest in organizations looking for ways to increase value fromdata science and using it to address business challenges. One promising way forbusinesses and organizations to enhance their performance or competitiveness isinvestigating how data science and analytics can facilitate collaboration bothinternally and externally.  For example, businesses are not just lookingat how data science and analytics can help acquire, grow and retain customersbut also at how it can use social media to support business operations and howit can leverage the power of online word-of-mouth to promote customers’engagement with brands.  One example is collaborative generation andcreation of ideas and solutions through crowdsourcing and online communities.Emerging heterogeneous, voluminous, and unverified data present bothopportunities and new challenges for addressing collaboration problems. Anotherexample is the collection of data by public around the world which is then usedby scientists working on Genographic data by National Geographic.  Topics ofinterest include, but not limited to:·        Challenges and opportunities of datascience for collaboration·        Analysis of big data forcollaboration ·        Collection, aggregation, andorganization of collaborative big data·        Managing heterogeneous big data fromcollaborative sources·        Visualization and presentation ofcollaborative big data·        Data science for collaborative work(decision making, problem solving, negotiation, and creativity/innovation)·        Data science and analytics forinternal collaboration in groups and organizations·        Data science and analytics forinter-organizational collaboration·        Crowdsourcing for collaborativetasks·        Security and privacy issues incollaborative data science·        Data science in collaborativecreation or innovation·        Case studies on data science forcollaboration: 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-theoreticmodels to interactions among social entities·        Application of survival models topredict hazard rate of computer supported social processes·        Application of N-person game theoryin problems arising from unregulated use of collaboration systems·        Knowledge discovery fromcollaborative data in social media·        Analysis of collaborative socialnetworks  Mini-trackCo-ChairsLakshmi S.Iyer
Information Systems and Supply Chain Management (ISSCM) Department
The University of North Carolina Greensboro
Lsiyer at uncg.edu  SourenPaul
College of Engineering and Computing
Nova Southeastern University
Fort Lauderdale, Florida
Souren.paul at gmail.com Lina Zhou
Information Systems Department
University of Maryland Baltimore County
zhoul at umbc.edu   SubmissionProcess:Full paper submissions must be made electronicallythrough the HICSS on-line submission system at https://precisionconference.com/~hicssby June 15, 2016.  Papers should notexceed ten pages and the initial submission will not have author names. Pleasecheck the above web site or contact the mini-track co-chairs for moreinformation. KeyDates:June 15, 2016 (11:59pm Hawaii Time): Full papersuploaded to the appropriate minitrack.August 16, 2016: Notification of accepted papersmailed to authors.September 15, 2016: Final Paper Due.  At least one author of each papershould register by this date.  This isthe Early Registration fee deadline.