We invite original research submissions focusing on novelty, best practice and use case orientation. Submissions are required to demonstrate both scientific-technical depth and practical applicability, encompassing methods along the full pipeline of data science and AI systems – from data acquisition and data management, through data analysis using machine learning and artificial intelligence (AI), to visualization, data product design, and the management of societal effects.

Topics of Interest
Topics include but are not limited to, the following key focus areas for 2025:

• Large Language and Foundation Models
  Transformer Architectures, Multimodal Models (Text, Image, Video), Pre-trained Models, Generative AI, Natural Language Processing (NLP), Question Answering, Retrieval-Augmented Generation (RAG), Model Fine-tuning, Zero-shot Learning, Conversational AI, DataData-Driven AI, Model Interpretability, and Trustworthy AI

• Human-AI Interaction
  Human-in-the-loop, Human-AI Teaming, Personalization and Contextualization, Explainable AI, Adversarial Attacks & Robustness, Data Privacy and Security, Data and Information Quality, Data Governance, Adaptive User Interfaces, Proactive AI Systems, and AI-Assisted Decision Making

• AI and Data Analytics for Science
  Scientific Machine Learning, Data Exploration, Data Modeling and Visualization, Data Mining, Feature Selection, Pattern Recognition, Evolutionary Computing and Optimization, Fuzzy Computing, Digital Twins, Automated Hypothesis Generation, Predictive Analytics, Interdisciplinary Data Integration, Data Warehousing, Data Structures and Data Management, Information Retrieval, Information Integration, Big Data Applications, and Data Quality for Trusted AI

• AI and Society
  Ethics, Fairness, Accountability and Transparency, AI Regulation, AI Certification, Cybersecurity in Relation to Data Science, Data-driven Value Creation, Business

Intelligence, Service Design and Operations, Smart Services, and Domain Specific Applications for Societal Challenges (e.g., Climate Change, Aging Population, Urban Planning and Smart Cities, Food Security and Agriculture, etc.)

Data Science is a dynamic field. Therefore, we also welcome submissions that do not fit into any of the key focus areas.

Submission Guidelines

• Full Paper: max. 8 pages incl. references, IEEE 8.5” x 11” two-column format. Present high-quality research contributions, including experiments, analysis, or system papers, as well as descriptions of application results.
• Short Paper: max. 4 pages incl. references, IEEE 8.5” x 11” two-column format. Present late-breaking results, work in progress, follow-up extensions, application case studies, or evaluations of existing methods.

All submissions must be original works that have not been published previously in any conference proceedings, magazine, journal, or edited book. Concurrent submissions are strictly forbidden. SDS 2025 maintains the confidentiality of submitted material. Upon acceptance, the titles, authorship, and abstracts of accepted papers will be released.

Review Process

• Double-Blind Review: Each submission will undergo a thorough review by the international Scientific Program Committee, with multiple experts evaluating the papers based on established scholarly criteria. To ensure impartiality, authors must anonymize their submissions appropriately. Submissions that fail to meet this requirement will be desk rejected.
• Rebuttal: Authors will have the chance to provide a response to the reviews during an author-reviewer discussion period.
• Decision by an Expert Panel: The international board of Program Co-Chairs will take the final decisions based on the reviews and the authors’ responses during the rebuttal. Excellent content and presentation are mandatory for acceptance (acceptance rate 2024: 35%).
• Commitment to Present: Submission of a paper implies the commitment of at least one author to register and present the paper at the conference (in English, as poster or talk).

Publication
Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements

Policy on AI for Writing Assistance
The use of AI assistants (e.g., ChatGPT, Copilot) in research, coding, or writing of the paper should be disclosed if it extended beyond pure language editing, brief input assistance, literature searches, or generating routine, low-novelty text.