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BDQM 2016 : The 1st International Workshop on Big Data Quality Management

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Link: http://theory.utdallas.edu/DASFAA2016/BDQM-CFP.docx
 
When Apr 16, 2016 - Apr 19, 2016
Where Dallas, TX
Submission Deadline Dec 1, 2015
Notification Due Jan 15, 2016
Final Version Due Jan 31, 2016
Categories    data management   databases   data mining   computer science
 

Call For Papers

Call for Papers
1st Workshop on Big Data Quality Management @ DASFAA 2016
16-19 April 2016, Dallas, TX, USA

With the development of information technology, big data arise in various applications and areas. On one hand, big data bring new value. On the other hand, new challenges are brought. One of the challenges is the data quality problem.

The features of big data bring more serious data quality problems. Due to volume, the harvest, storage, transmission and computation will cause more errors. Current data get outdated for velocity. The variety leads to more inconsistency and conflicts. Data quality problem will do harm to the applications of big data, even result in disaster.

As a result, big data quality management is in demand to decrease the harm of data quality problems and computes high-quality problem from big data. Big data management has become one of the hottest issues not only in database community but also in artificial intelligence, data mining and other related area.

The goal of the Workshop on Big Data Quality Management is to raise the awareness of quality issues in Big data and promote approaches to evaluate and improve big data quality.

The workshop topics include, but are not limited to:
Data Quality Models and Theory
Data Quality Measures and Evaluations
Data Cleaning Algorithms
Record Linkage and Entity Resolution
Privacy Preservation and Security Issues in the Process of Data Cleaning
Data Quality Policies and Standards
Data Provenance and Annotation
Data Quality in Information Retrieval and Extraction
Probabilistic, Fuzzy, and Uncertain Data Management
Data Quality in Sensor Networks and CPS
Data Quality in Information Integration
Crowdsourcing for Data Quality
Master Data Management
Applications for Data Quality Management
Error-Tolerate Computation

Submission guidelines

We seek novel technical research papers in the context of Data Quality Management with a length of up to 8 pages (long) and 4 pages (short) papers. Papers should be submitted in PDF format. Paper submissions should be formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). Please submit your paper via cmt at https://cmt3.research.microsoft.com/BDQM2016. Submissions will be peer reviewed by three independent reviewers.

Accepted papers have to be presented at the workshop to be published in the proceedings. Proceedings will be published in the Springer LNCS series.

Important Dates

All deadlines are, unless otherwise stated, at 23:59 Hawaii time.

Submission of research papers: DEC 1, 2015.
Notification of paper acceptance: Jan 15, 2016
Submission of camera-ready papers: Jan 31, 2016

Honorable Chair
Jianzhong Li, Harbin Institute of Technology

Chair
Hongzhi Wang, Harbin Institute of Technology
Jing Gao, University at Buffalo, the State University of New York

Program Committees (Tentative)
Xiaochun Yang, Northeast University
Yueguo Chen, Renmin University
Nan Tang, QCIR
Jiannan Wang, Simon Fraser University
Xianmin Liu, Harbin Institute of Technology
Zhijing Qin, Pinterest
Guoliang Li, Tsinghua University
Cheqing Jin, East China Normal University
Wenjie Zhang, University of New South Wales
Shuai Ma, Beihang University
Zhaonian Zou, Harbin Institute of Technology

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