AIRDeM 2025

About AIRDeM

RDM in the data intensive era has become increasingly challenging. Researchers face obstacles like manual (i.e. prone to error) and time-consuming (i.e. expensive) processes of creating metadata, removing inconsistencies in data formats, dealing with data heterogeneity and sharing for reusability. The lack of standardised and scalable tools supporting these tasks, leads to inefficient research data management.

AIRDeM explores how AI methods, particularly recent advancements in LLMs, can revolutionise RDM by enabling automation. The topics include, but not limited to:

Automated Metadata Extraction, Annotation, and Generation: Leveraging LLMs and AI-driven methods to enrich metadata, enhancing the findability and accessibility of data across research domains
FAIR Metrics Enhancement: Developing and applying metrics to measure and improve data discovery, interoperability, and overall data quality.
Enhanced Metadata Quality: Utilising existing vocabularies, and KGs to enrich metadata, improve searchability, and enable data interoperability across heterogeneous datasets.
AI-Driven Question Answering for RDM: Incorporating AI-driven data descriptions, summarizations, and question answering chatbots to support researchers in searching, navigating and utilising the research data more effectively.
AI-Driven Data Quality and Harmonization: Use of AI tools for improving the data quality, dealing with missing, inconsistent data, and handling heterogenous multimodal data.

This workshop will showcase the application of state-of-the-art AI methods, including information extraction (IE) and neuro-symbolic AI, to support and enhance FAIR RDM practices. Additionally, it will explore how RDM practices can be significantly improved through the use of KGs and linked data, which play a crucial role in enriching metadata and standardization efforts. The workshop will also delve into the integration of LLMs with KGs, focusing on their tailored applications for streamlining and facilitating RDM tasks.

Call for Participation

We invite submissions for the AIRDeM workshop at the Extended Semantic Web Conference (ESWC). Participants can contribute through the following formats:

Full Research Papers (up to 12 pages): Presenting novel scientific research addressing RDM challenges or enhancing FAIR practices.
Short Research Papers (up to 6 pages): Showcasing research results at early stages, including preliminary findings or innovative concepts.
Position Papers (up to 6 pages): Introducing positions, ideas, opinions, and discussions around specific RDM topics.
Demos (up to 3 pages): Presenting tools (software, workflows, etc.) with a practical perspective for using AI for improving RDM practices.
Posters (up to 3 pages): Highlighting novel approaches, insights, or tools through visual presentations.
Bring Your Challenge (up to 3 pages): Submit real-world RDM problems and collaborate on innovative solutions during the workshop.

This workshop offers a platform to share innovative AI-driven solutions, foster discussions, and explore collaborations to address pressing RDM challenges. We look forward to your participation!

Submit your contributions here: Submission page!

Important Dates

Submission Deadline: March 20, 2025
Notification of Acceptance: April 3, 2025
Camera-Ready Deadline: May 1, 2025
Workshop Date: June 10, 2025

Organizing Committee

Hajira Jabeen: Leads AI in RDM at the Institute for Biomedical Informatics, University of Cologne. Contact: "fname.lastname@uk-koeln.de"
Damien Graux: Principal Research Scientist, Huawei Technologies, UK, specializing in Semantic Web technologies.
Ahmad Abu Dayeh: PhD Candidate focusing on distributed machine learning, FAIR data management, and knowledge graphs.
Oya Beyan: Professor of Medical Informatics, University of Cologne, expert in FAIR data management and distributed analytics.

Location

The AIRDeM 2025 workshop will take place at the Extended Semantic Web Conference (ESWC) venue. More details will be provided closer to the event date.