Web of Data Quality Workshop

Web of Data Quality Workshop at The Web Conference 2025



Web of Data Quality Workshop


Web of Data Quality Workshop aims to foster an in-depth discussion to address Web of Data quality issues, fostering dialogue on the establishment of standardized processes, development of accessible tools, implementation of reusable best practices and workflows working across various domains. By bringing together academia, industry professionals, and practitioners, we aim to cultivate practical strategies and tools that can strengthen data pipelines across various domains, ensuring that data quality is prioritized, reproducible, and effective in driving reliable outcomes. Contributions in this direction will affect any data-driven pipeline dealing with machine readable data.

Topics of interest

Topics of interest include but are not limited to the following ones:

  • Web of Data Quality Assessment at Both Metadata and Data Levels
  • Standardized, Reusable, and Tailored Approaches for Quality Assessment and Improvement
  • Interplay and Alignment Among Different Standards for Data Quality
  • Artificial Intelligence-Driven Approaches for Web of Data Quality Assessment and Improvement
  • Impact of Data Quality on Governance of Responsible Artificial Intelligence
  • Temporal Variability of Data Quality and Its Implications
  • Data Quality Assessment and Improvement as Part of Complex Data Management Pipelines
  • Alignment Between Intrinsic Quality Dimensions and “Fit for Use” Requirements
  • Interplay and Correlation Among Different Quality Dimensions and Influencing Factors

Submission details

NEWS!!! We are excited to announce that we have joined the fast-track program in conjunction with the main conference!

How to join the fast-track option in our workshop?

To participate, please add an Appendix to your submission, located below the References, containing the following:

  • Cut-and-pasted reviews from the main review process.

Note: As organizers, we guarantee that your reviews will not be shared with any third parties.

  • A section titled “Improvements”, where authors should briefly describe whether they were able to address any issues raised in the main reviews and how they addressed them. Note that only light revisions are expected. If the work is already in good shape, no revisions are necessary.

Important: Heavy revisions or altering review comments are not allowed.

By default, accepted papers will be published in the ACM Companion Proceedings. If you wish to opt out of having your work included in the ACM Companion Proceedings, please inform us upon acceptance, during the camera-ready submission process.

Submissions can fall in one of the following categories:

  • Full research papers (up to 8 pages, excluding references)
  • Short research papers (up to 4 pages, excluding references)

We welcome contributions presenting

  • success stories,
  • negative results,
  • reviews of the state of the art,
  • position papers critically discussing what is missing in this alliance, i.e., data quality and KGs.

Submissions must be in English, in double-column format, and must adhere to the ACM template and format (also available in Overleaf). Word users may use the Word Interim Template and the recommended setting for LaTeX is:

\documentclass[sigconf, anonymous, review]{acmart}

Papers are submitted in PDF format via EasyChair.

Papers will be review by at least 2 experts.

At least one of the authors of the accepted papers must register for the workshop to be included into the workshop proceedings. Information about registration can be found on the Web Conference 2025 official page.

Important dates

  • Paper submission deadline: 18 December, 2024 8 January, 2025
  • Notification of Acceptance: 13 January, 2025 27 January, 2025
  • Camera-ready paper due: 2 February, 2025
  • The Web Conference 2025 Workshops day: April 28th, 2025, from 1:30 PM to 5:00 PM (Sydney time)

All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.

Program details and Keynote

Start Speaker Talk title
13:30 Gianluca Demartini, University of Queensland Keynote entitled “Bias in Data Annotations”
14:15 Oshani Seneviratne Explainability-Driven Quality Assessment” for Rule-Based Systems
14:30 Shima Esfandiari Enhancing Data Quality by Identifying Influential Nodes: Integrating Complementary Features with CoCoFISo
14:40 Yuhao Gong Adaptive Confidence-aware Preference-based Reinforcement Learning with Noisy Feedback
15:00 BREAK - Take a coffee! :)  
15:30 Paolo Missier, University of Birmingham Invited lightning talk
16:00 Gabriele Tuozzo Navigating the LOD Subclouds: Assessing Linked Open Data Quality by Domain
16:15 Elyas Meguellati Are Large Language Models Good Data Preprocessors?
16:25 Kerry Taylor, Australian National University Invited lightning talk

Organizers
Maria Angela Pellegrino Anisa Rula Anelia Kurteva
University of Salerno University of Brescia University of Birmingham
Italy Italy United Kingdom

Advisory board
Heiko Paulheim Laure Berti-Équille Paul Groth
University of Mannheim French Institute of Research for Sustainable Development University of Amsterdam
Germany France The Netherlands

Program committee

  • Aidan Hogan, Universidad de Chile, Chile
  • Ernesto Jiménez-Ruiz, University of London, UK
  • Gabriele Tuozzo, University of Salerno, Italy
  • Heiko Paulheim, Universität Mannheim, Germany
  • Paul Groth, University of Amsterdam, The Netherlands