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CALL FOR PAPERS

Workshop on Management of Data under Uncertainty (MoDU 2023)
To be held in conjunction with ADBIS 2023 (https://www.essi.upc.edu/dtim/ADBIS2023/)
September 4, 2023
Barcelona, Spain
https://modu2023.lis-lab.fr/

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** GENERAL INFORMATION **
In the era of big data and Machine learning, the issue of uncertainty, is still an active research topic. Uncertainty needs to be managed at various levels of data management process: data collection, data querying, machine learning and data analytics. For instance, the presence of uncertainty can be source of semantics errors during query evaluation. Moreover, traditional machine learning and deep learning models do not consider uncertainty in data and predictions while they are prone to noises. Then, quantifying uncertainty is a critical challenge for most machine learning techniques. From analytics perspective, the presence of uncertainty and imprecision can cause inaccuracies in predictions that may impact the quality of the data analytics procedures themselves.


** GOAL OF THE WORKSHOP **
The aim of the workshop is to allow academics and industrial from various areas to share their experiences on management of uncertain data. Authors are encouraged to submit their research work and case studies addressing all facets of uncertainty and showing the usefulness of their approaches in different application domains.


** LIST OF TOPICS **
We seek contributions covering all aspects of data management under uncertainty, including, but not limited to, the following topics:

Uncertainty in data collection and querying:
• Incompleteness, ambiguity, inconsistency in data
• Aleatoric and epistemic uncertainty
• Uncertainty Modeling
• Querying uncertain data
• Approximate query
• Uncertain data fusion

Uncertainty in ML and Deep learning models:
• Prediction models for uncertain data
• Uncertainty quantification in deep and machine learning
• Uncertainty in data labeling
• Reasoning under uncertainty
• Uncertain data and conformal approaches

Uncertainty in data analytics:
• Uncertainty and Imprecision in (big) data management and Analytics
• Uncertain Spatial Data Management
• Data mining on uncertain data
• Metrics for uncertainty and data quality
• Uncertainty quantification

** SUBMISSION INSTRUCTIONS **
Submissions should present original works not currently under review or published elsewhere. This workshop accepts research and industrial papers (regular: 12 pages max., and short: 6-8 pages max.) including novel approaches for management of uncertain data. All accepted papers will be published in the conference proceedings and will be submitted for inclusion. Papers should submitted in PDF format using the EasyChair online submission system (https://easychair.org/my/conference?conf=modu2023). Authors should consult Springer's authors' guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers.

** IMPORTANT DATES **
• Paper submission: April 24, 2023
• Notification of paper acceptance: May 15, 2023
• Camera-ready due: June 9, 2023
• Workshop day: September 4, 2023

** WORKSHOP ORGANIZERS **
• Richard Chbeir, University Pau & Pays Adour, Anglet, France
• Allel Hadjali, Engineer School ENSMA, Poitiers, France
• Sana Sellami, Aix Marseille University, Marseille, France

** PUBLICATION **
The workshop papers will be published by Springer in Communications in Computer and Information Science (CCIS). The authors of selected workshop papers will be invited to submit an extended version of their contributions to a special issue of a well-established and ranked international journal (tbd).

** DIVERSITY, EQUITY AND INCLUSION STATEMENT **
We kindly ask authors to adopt inclusive language in their papers and presentations. Our aim is to promote DEI in MoDU by implementing different actions such as having diverse PC members, co-chairs and session chairpersons.

** SHORT BIO OF THE WORKSHOP ORGANIZERS **
• Richard Chbeir is a professor of computer science at the University Pau and Pays de l’Adour in France, where he leads the computer science laboratory called LIUPPA. He is the director of the Semantics & Privacy In Digital Ecosystems Research group (SPiDER) and the head of the OpenCEMS industrial chair. Richard Chbeir received his Ph.D. in computer science from the Institut national des sciences appliquées de Lyon in 2001 and got his Habilitation degree in 2010 from the University of Burgundy. He is currently working on Data semantics, information and knowledge extraction. He is the co-founder of the MEDES Conference. He is involved in several conferences, most recenty: Program Chair @ WISE 2022, Program Chair of ICCCI 2022, General Chair of ICWE 2021, General co-chair of ACM SAC 2018 to mention a few.
• Allel Hadjali is Full Professor in Computer Science at the National Engineering School for Mechanics and Aerotechnics (ISAE-ENSMA), Poitiers, France. He is a member of the Data and Model Engineering research team of the Laboratory of Computer Science and Automatic Control for Systems (LIAS). His main area of research falls within Data Science field, and more specifically, the research topics related to Data Exploitation and Analysis (sensor data, semantic data, incomplete data), Knowledge Extraction and Recommendation. His current research interests include Soft Computing and Computational Intelligence in Databases (Cooperative/Intelligent Databases, Data fusion/integration, Data quality, Data Uncertainty, Data Privacy and Trust), Machine Learning-based Recommendation, Explainable Artificial Intelligence. His recent works were published in well-known journals (e.g., Applied Soft Computing, Knowledge and Information Systems, Fuzzy Sets and Systems, International Journal of Intelligent Systems, Journal of Intelligent Information Systems). He also published several papers in International Conferences (e.g., ESWC, ICTAI, WISE, Fuzz-IEEE, DEXA, FQAS, SUM, ISMIS, IPMU, CoopIS, IFSA, ACM SAC). He co-organized several special sessions, e.g., « Advances in Data Management in the Context of Incomplete Databases » in conjunction with IFSA (2015) Conference and « Uncertainty in Cloud Computing » in conjunction with DEXA (2017) Conference. He co-organized also several special issues in well-known journals, among them, « On Advances in Soft Computing Applied to Databases and Information Systems » in Fuzzy Sets and Systems Journal (2011), « Post LFA 2015 Conference » in Fuzzy Sets and Systems Journal (2017), « Uncertain Cloud » in International Journal of Approximate Reasoning (2019). The complete list of his publications is available in http://www.lias-lab.fr/members/allelhadjali.
• Sana Sellami is an associate-professor in computer science at Aix-Marseille University, and a member of LIS laboratory, within the DIAMS research team. Her main research interests are related to data management especially data integration and analytics. She was a publicity chair of ICWS 2022, a track data Science co-chair of AICCSA 2022, DEI (Diversity Equity and Inclusion) co-chair of WISE 2022.