Data Quality Issues in Big Data and Machine Learning Applications: Going Beyond Data Cleaning and Transformations

A Workshop Held in Conjunction with the 2017 IEEE International Conference on Big Data

Boston, MA

11 - 14 December 2017

Data Quality Issues in Big Data and Machine Learning Applications: Going Beyond Data Cleaning and Transformations workshop will be held in conjunction with the 2017 IEEE International Conference on Big Data, Boston, Massachusetts, 11 - 14 December 2017.

Workshop Theme

Minor data errors can cause major damage in Big Data applications. Damages manifest in various forms including loss of revenue, operational inefficiency, and regulatory compliance failure. Moreover, these errors cascade through downstream applications and exacerbate damages. The goal of this workshop is to bring together data quality researchers and industry practitioners to share their ideas and best practices, identify and define important problems to further the field.

Scope of Research Topics for the Workshop

Paper Submission

Please submit a full-length paper (up to 10 pages IEEE 2-column format) through the online submission system.

Paper Formatting Instructions/Templates

Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. Use the templates shown below.

Important Dates

Workshop Chairs

For workshop related questions, please contact any of the following organizers:

Program Committee