As data continues to be produced in massive amounts, with increasing volume, velocity and variety, Big Data projects are growing in frequency and importance. However, the growth in the use of Big Data has outstripped the knowledge of how to support teams that need to do big data projects.
Following our workshops at the previous 4 IEEE Big Data conferences, this workshop will explore methodologies, tools and frameworks that have been or need to be developed to help support big data projects and help frame what a manager should think about when leading a big data science effort.
The workshop will provide a venue to explore new ideas in both possible methodologies and tools, as well case studies that describe examples of what has, or has not, worked within different Big Data teams. Significant work-in-progress papers are also encouraged.
To enable a cross pollination of ideas, the workshop welcomes both academic researchers and industry experts. We invite research results and position statements on topics including, but not limited to:
Paper submissions should be in English and not exceed 10 pages (5 pages for a work-in-progress paper).
Note that papers that are submitted by the early deadline will have the ability to get feedback and/or acceptance prior to the final submission deadline.
Accepted papers will be published as part of the IEEE Big Data conference proceedings.
Paper Submission
Please use this submission link
Important Dates
1 Sep 2019 - Workshop Early Submission Date
12 Oct 2019 - Final Workshop Submission Deadline
1 Nov 2019 - Notifications of Acceptance
15 Nov 2019 - Camera-ready of accepted papers due
9 Dec 2019 - IEEE Big Data Starts
Program Committee (to be refined)
Contact / Questions
Please email any questions to Jeffrey Saltz (jsaltz[at]syr.edu)
Please join our group
Following our workshops at the previous 4 IEEE Big Data conferences, this workshop will explore methodologies, tools and frameworks that have been or need to be developed to help support big data projects and help frame what a manager should think about when leading a big data science effort.
The workshop will provide a venue to explore new ideas in both possible methodologies and tools, as well case studies that describe examples of what has, or has not, worked within different Big Data teams. Significant work-in-progress papers are also encouraged.
To enable a cross pollination of ideas, the workshop welcomes both academic researchers and industry experts. We invite research results and position statements on topics including, but not limited to:
- Team Process Methodologies (ex. Agile) – how should teams collaborate & communicate
- Fairness in Machine Learning - how to ensure fairness, how to know if the analysis is fair
- Ethics – what are possible model or data concerns (including Model Bias and Transparency)
- Quality – how to ensure data quality, how to try ensure the results are accurate
- Team Roles – what is needed within a big data team
- Analytics Workflow Tools – how to help improve project modularity
- CMM (Capability Maturity Model) – is it useful for evaluating Big Data efforts?
- Software Engineering Project Management – challenges specific to Big Data projects
- Analytics/Model Management – is an audit trail important
- Production Robustness – ops migration & monitoring
- Evaluation - how to know the effectiveness of a Big Data team
- Frameworks - to describe Big Data projects and Big Data project process maturity
- Case studies on related topics of interest to this workshop
Paper submissions should be in English and not exceed 10 pages (5 pages for a work-in-progress paper).
Note that papers that are submitted by the early deadline will have the ability to get feedback and/or acceptance prior to the final submission deadline.
Accepted papers will be published as part of the IEEE Big Data conference proceedings.
Paper Submission
Please use this submission link
Important Dates
1 Sep 2019 - Workshop Early Submission Date
12 Oct 2019 - Final Workshop Submission Deadline
1 Nov 2019 - Notifications of Acceptance
15 Nov 2019 - Camera-ready of accepted papers due
9 Dec 2019 - IEEE Big Data Starts
Program Committee (to be refined)
- Jeffrey Saltz, Syracuse University (Chair)
- Junhua Ding, University of North Texas
- Kerk Kee, Texas Tech University
- Daniel Asamoah, Wright State University
- Patrick Mikalef, Norwegian University of Science and Technology
- Frank Armour, American University
- Bintong Chen, University of Delaware
- Ivan Shamshurin, Syracuse University
Contact / Questions
Please email any questions to Jeffrey Saltz (jsaltz[at]syr.edu)
Please join our group