Hazar Harmouch

I am a member of the Intelligent Data Engineering Lab at the Informatics Institute of the University of Amsterdam, Netherlands. My research focus is on the field of data quality for and with machine learning.

Before that, I was a Postdoc at the Information Systems Group at the Hasso Plattner Institute, University of Potsdam. During my doctoral research at the same group, I worked in the field of data profiling with the aim of developing algorithms for efficiently processing and analyzing large volumes of data.

Beyond my research, I am also interested in keeping up with the latest developments in machine learning, data management, and integration. I am also constantly looking for new collaboration opportunities! Outside of work, I enjoy traveling, reading, cooking and training.

Research interests

Data quality for AI (fairness, non-discrimination, privacy)
Data profiling, integration and cleaning
Data mining and machine learning
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News

Mar 07, 2024	I will serve as a Program Committee member at BTW 2025.
Dec 14, 2023	A proposal for a special issue titled “Data quality dimensions in Data FAIRification design and processes” by me, Anna Bernasconi, Stefano Cirillo, and Alberto García Simon has been accepted by the JDIQ journal . The submission deadline will be end of November 2024. Stay tuned for the call for papers.
Dec 14, 2023	I will serve as a Program Committee member at SIGMOD 2025.
Nov 20, 2023	I am attending the The Federal Government DIGITAL SUMMIT 2023 in Jena, Germany (invite only) to contribute my expertise regarding data quality importance for AI applications.
Oct 31, 2023	I will serve as a Program Committee member of the 3rd International workshop on Databases and Machine Learning (DBML) in conjunction with ICDE 2024 in Utrecht, Netherlands.
Jul 18, 2023	On 1st of November, I will start as an assistant professor at the university of Amesterdam - INDE Lab .
Apr 06, 2023	I will serve as a Program Committee member for the database track of LWDA 2023.
Feb 09, 2023	Co-organizing QDB workshop at VLDB 2023
Nov 02, 2022	I am speaking about our KITQAR project at the first AI Quality summit-Frankfurt am Main.
Oct 31, 2022	I will serve as a Program Committee member of the DBML Workshop at ICDE 2023.
May 09, 2022	I will serve as a Demo Program Committee member at BTW 2023.
Dec 13, 2021	I will serve as a Program Committee member of the DBML Workshop at ICDE 2022
Nov 08, 2021	An article about our project "sales comparison approach"
Feb 16, 2021	I will serve as a Program Committee member at SIGMOD 2022.
Feb 12, 2021	Papers accepted at ICDE 2021
Aug 17, 2020	I defended my PhD and officially Frau Dr. Harmouch!
Jul 09, 2020	I will serve as a Demo Program Committee member at BTW 2021.
Mar 04, 2020	After four years of hard work, I handed in my PhD. thesis today I am going to stay at HPI as a Postdoc with Prof. Dr. Felix Naumann.
Aug 09, 2019	Papers accepted at CIKM 2019
Mar 16, 2018	Metanome data profiling platform wins a prize
Mar 16, 2018	Paper marked as reproducible by pVLDB Reproducibility Committee
Mar 16, 2018	Papers accepted at VLDB 2018
Nov 15, 2017	Experimental survey accepted at VLDB 2018
Jun 22, 2016	Article published in the IEEE Data Engineering Bulletin journal
Oct 01, 2015	I started my PhD. studies at HPI, Germany under the supervision of Prof. Dr. Felix Naumann.

Recent Publications

A Data Quality Glossary

Sedir Mohammed , Lou Therese Brandner , Felicia Burtscher , Sebastian Hallensleben , Hazar Harmouch, Andreas Hauschke , Jessica Heesen , Stefanie Hildebrandt , Simon David Hirsbrunner , Julia Keselj , Philipp Mahlow , Marie Massow , Felix Naumann , Frauke Rostalski , Anna Wilken , and Annika Wölke

Jan 2024

Bib PDF

@manual{mohammed_2024_10474880,
  title = {A Data Quality Glossary},
  author = {Mohammed, Sedir and Brandner, Lou Therese and Burtscher, Felicia and Hallensleben, Sebastian and Harmouch, Hazar and Hauschke, Andreas and Heesen, Jessica and Hildebrandt, Stefanie and Hirsbrunner, Simon David and Keselj, Julia and Mahlow, Philipp and Massow, Marie and Naumann, Felix and Rostalski, Frauke and Wilken, Anna and Wölke, Annika},
  month = jan,
  year = {2024},
  doi = {10.5281/zenodo.10474880},
  url = {https://doi.org/10.5281/zenodo.10474880},
}

Data Quality Assessment: Challenges and Opportunities

Sedir Mohammed , Hazar Harmouch, Felix Naumann , and Divesh Srivastava

arXiv preprint arXiv:2207.14529, Jan 2024

Abs Bib PDF

Data-oriented applications, their users, and even the law require data of high quality. Research has broken down the rather vague notion of data quality into various dimensions, such as accuracy, consistency, and reputation, to name but a few. To achieve the goal of high data quality, many tools and techniques exist to clean and otherwise improve data. Yet, systematic research on actually assessing data quality in all of its dimensions is largely absent, and with it the ability to gauge the success of any data cleaning effort. It is our vision to establish a systematic and comprehensive framework for the (numeric) assessment of data quality for a given dataset and its intended use. Such a framework must cover the various facets that influence data quality, as well as the many types of data quality dimensions. In particular, we identify five facets that serve as a foundation of data quality assessment. For each facet, we outline the challenges and opportunities that arise when trying to actually assign quality scores to data and create a data quality profile for it, along with a wide range of technologies needed for this purpose.
@article{mohammed2024data, title = {Data Quality Assessment: Challenges and Opportunities}, author = {Mohammed, Sedir and Harmouch, Hazar and Naumann, Felix and Srivastava, Divesh}, journal = {arXiv preprint arXiv:2207.14529}, year = {2024}, }