The 1st Workshop on Bridging AI and Data-centric SystemS (BADASS) workshop aims to address these critical and timely challenges by bringing together scientists, engineers, cognitive scientists, practitioners, data enthusiasts, and students in an interdisciplinary forum where they can share experiences and ideas, discuss the results of their research on models, methodologies and algorithms, and forge new collaborations that will lead to the development of new applications and tools to transform information extracted from data into actionable intelligence.

Today's society is data-driven: decisions are increasingly based on insights from data analysis. This societal transformation places the database community in the center of technology disruptions. Artificial Intelligence (AI) methods are now well-established and are well accepted by the data management and analytics (DMA) community to address some of its challenges.

For example, and without being exhaustive, one may cite personalization or recommendation of queries in databases, the management of time series big data streams, the recommendation of dashboards in business intelligence, the indexing of large amounts of data possibly in distributed systems based on ML-based optimization methods, the guided exploration of novel data or the explanation of the provenance of data in queries.

However, data are increasingly complex and data-centric systems often now only partially rely on the traditional relational model. For example, one may consider multivariate temporal relationships between observations as time series, possibly with no synchronicity between observations. Others may view more general relations as graphs, such as in social networks, that carry multi-modal information such as text, sound, videos and user-related information with different links between them.

On the other hand, a noticeable change in AI is the advent of Large Language Models (LLM). LLM can be seen as a paradigm shift in the way data are collected, queried, analyzed and knowledge is gained etc. and this is impacting data-centric systems. Objectives may span several complementary research directions, for example: (i) making sure that these LLM systems remains transparent and that their decisions are explainable and fair and, (ii) that these systems benefit from the accumulated experience of the data management community to produce meaningful insights for the user or to answer with correct data, hence removing the well-known risk for hallucination.

BADASS will be held in conjunction with ADBIS 2024 conference in Bayonne, France. It is planned to be an in person workshop with virtual elements (if possible a direct stream of presentations will be organized).

BADASS invites submissions of original research, practical experiences, evaluation results, or novel approaches and applications related to artificial intelligence and data management.

The scope of the workshop includes, but is not limited to the following topics.

• Exploratory data analysis
• Data storytelling, data narration
• Data visualization
• Explainability of data, algorithms, processes, causality, counterfactual reasoning
• Accounting for data uncertainty and imprecision in data analytics
• Integration of querying functionalities with ML
• Improvement of DB platforms with ML
• User models / preferences for data analytics
• Novel AI methods for data governance
• Large Language Models for data analytics
• End-to-end development of the data-to-insights pipeline
• Innovative and timely use cases showcasing any contribution to AI for data analytics (e.g., healthcare, precision agriculture, environment, social good, climate science, etc.)

Submissions should present original results and substantial new work not currently under review or published elsewhere. BADASS will follow a single-blind review process to evaluate submissions on the basis of originality, relevance, quality, and technical contribution. The following submissions are accepted:

• Regular papers (up to 10 pages)
• Position and vision papers (up to 5 pages)
• Technical summaries of previous research relevant to the workshop (up to 5 pages). Papers of this kind outline work of the authors that has already been published in other venues, and highlight the relevant future directions.

Submissions should have their type mentioned as a title footnote (i.e., technical, summary or position paper). References and figures are included in the page count. Any submitted paper violating the length, file type, or formatting requirements will be desk rejected. We kindly ask authors to adopt inclusive language in their papers and presentations (https://dbdni.github.io/pages/inclusivewriting.html and https://dbdni.github.io/pages/inclusivetalks.html), and all participants to adopt a proper code on conduct (https://dbdni.github.io/pages/codeofconduct.html)

Papers must be submitted via the ADBIS's workshop track of EasyChair. Only electronic submissions in PDF format will be considered. A paper submitted to BADASS cannot be under review for any other conference or journal during the entire time it is considered for BADASS. All accepted papers will appear in the conference proceedings.

All accepted papers are expected to be presented at the workshop, and at least one author is required to register.