[AISWorld] [CfP] 12th International Workshop on Quality in Databases (QDB'23) in conjunction with VLDB 2023

[Lisa Ehrlinger]

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CALL FOR PAPERS

12th International Workshop on Quality in Databases (QDB'23) in conjunction with VLDB 2023 August 28 (Monday), 2023, Vancouver, Canada Submissions due: May 31, 2023
https://hpi.de/naumann/s/qdb2023.html
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** Aims of the Workshop **
Data quality has been a major concern of organizations for decades. The recent advances in artificial intelligence (AI) have brought data quality (DQ) back into the spotlight: while many recent data quality and cleaning solutions are powered by ML, DQ is a core requirement to ensure reliable AI-based systems. DQ is tackled from different perspectives by different research communities, including database, machine learning (ML), and information systems. We believe it is important to bring together these communities to foster a vital discussion about the future of DQ assessment and improvement.

QDB'23 revives the successful QDB workshop series to cover the needs of the AI era, addressing both industry and academia (cf. data-centric AI). The workshop aims to (1) revive vital discussions about data quality, and (2) specifically exchange novel ideas and best practices about data quality assessment and improvement in the context of AI-based systems.

** Topics of Interest **
The focus is on new and practical methods for (semi-)automated (ML-based) data quality assessment and improvement. The topics of interest include, but are not limited to:
- Data quality assessment for AI-based systems
- Data quality improvement / data cleaning for AI-based systems
- Data preprocessing and data preparation
- Benchmark data sets to evaluate DQ assurance methods
- Automation of DQ assessment and improvement methods
- ML-powered methods for improving data quality
- Data profiling for data quality measurement
- Data quality in graph-structured or time-series data
- Metadata management
- Human-in-the-loop approaches for DQ
- Post-training quality / fact checking
- Explainable data cleaning
- Methods to scale data quality assessment and cleansing
- FAIRness in data quality

** Workshop Chairs **
- Lisa Ehrlinger, Software Competence Center Hagenberg GmbH, Austria
- Hazar Harmouch, Hasso Plattner Institute, University of Potsdam, Germany
- Ihab Ilyas, Apple, University of Waterloo, USA
- Felix Naumann, Hasso Plattner Institute, University of Potsdam, Germany

** Program Committee **
Ziawasch Abedjan (Leibniz Universität Hannover, Germany)
Felix Bießmann (Berlin University of Applied Sciences and Technology, Germany)
Ismael Caballero (University of Castilla La Mancha, Spain)
Cinzia Capiello (Politecnico di Milano, Italy)
Chang Ge (U Minnesota, USA)
Rihan Hai (TU Delft, Netherlands)
Christine Legner (University of Lausanne, Switzerland)
Sebastian Link (University of Auckland, New Zealand)
Paolo Papotti (EURECOM, France)
Elizabeth Pierce (University of Little Rock, USA)
Erhard Rahm (Uni Leipzig, Germany)
Kai-Uwe Sattler (TU Ilmenau, Germany)
Sebastian Schelter (University of Amsterdam, Netherlands)
Panos Vassiliadis (New York University, USA)
Wolfram Wöß (Johannes Kepler University Linz, Austria)
TBD

** Important Dates **
Submission: May 31, 2023
Notification: July 25, 2023
CRC: August 10, 2023
QDB workshop: August 28, 2023

** Submission **
Authors are invited to submit original, unpublished full research papers and demo descriptions that are not being considered for publication in any other forum. Please submit your paper as a PDF using Microsoft's QDB CMT site: https://cmt3.research.microsoft.com/QDB2023 You need to append the category tag as a suffix to the title of the paper such as “Data Management in the Year 3000 [Regular]”; “Spatial Database System [Demo]”. This must be done both in the paper file and in the CMT submission title. The suffix will not be part of the camera-ready copy if the paper is accepted.

Manuscripts should be formatted and submitted as a PDF according to the VLDB format. The template can be found at https://vldb.org/pvldb/volumes/16/formatting.
In particular, it is not allowed to modify the format with the objective of squeezing in more material. Submissions that do not comply with the formatting detailed here will be rejected without review. Note that the limit of up to 6 pages (including all figures, tables, and references) must be followed for both full papers and demos.

Dr. Lisa Ehrlinger
Senior Researcher Data Science
Phone/Mobile: +43 50 343 836
E-Mail: Lisa.Ehrlinger at scch.at
scch { }
Integrated Software and AI Systems (INTEGRATE)
Software Competence Center Hagenberg GmbH
A-4232 Hagenberg, Softwarepark 32a
www.scch.at
UID: ATU 48056909 | FN: 184145b, Landesgericht Linz
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