Workshops
The purpose of workshops is to provide a more interactive and focused platform for presenting and discussing new and emerging ideas. The format of paper presentations may include oral presentations, poster presentations, keynote lectures and panels. Depending on the number of presentations, workshops can be scheduled for 1 day or 2 days. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, EI and Web of Science / Conference Proceedings Citation Index.
WORKSHOPS LIST
SKEAI 2025, Workshop on Semantic Knowledge-based Explainability of Artificial Intelligence
Chair(s): Adeel Ahmad
BI-DEMT 2025, Workshop on Data Engineering Models and Techniques for Business Intelligence and Enterprise Applications
Chair(s): Orlando Belo, Bruno Oliveira and Óscar Oliveira
Workshop on
Semantic Knowledge-based Explainability of Artificial Intelligence -
SKEAI
2025
Paper Submission:
January 30, 2025 (expired)
Authors Notification:
February 13, 2025 (expired)
Camera Ready and Registration:
February 21, 2025
Scope
The workshop aims to bring together researchers, practitioners, and domain experts to exchange knowledge, address challenges, and outline future directions for developing explainable, interpretable, and transparent AI systems. It focuses on advancing Explainable Artificial Intelligence (XAI) by incorporating knowledge and semantics as core components. Contributions will address “demystifying the black-box” nature of AI and tailoring explanations to diverse user expertise levels, supporting equitable and fair decision-making for long-term sustainability. The workshop seeks to overcome the challenges of embedding semantic abstractions into intelligent information systems. These efforts are intended to foster trust, improve debugging, and encourage the adoption of AI in critical domains such as healthcare, finance, policy-making, and education.
Workshop on
Data Engineering Models and Techniques for Business Intelligence and Enterprise Applications -
BI-DEMT
2025
Paper Submission:
January 30, 2025 (expired)
Authors Notification:
February 13, 2025 (expired)
Camera Ready and Registration:
February 21, 2025
Scope
In today's digital era, organizations face high-volume, complex data from diverse sources. This rapid growth demands advanced data engineering solutions for seamless ingestion, integration, and transformation into actionable insights. Traditional approaches often struggle with dynamic business needs, real-time decisions, and scalability.
Artificial Intelligence (AI) is revolutionizing data engineering, reshaping data pipelines and architectures. Through machine learning, generative AI, and automation, AI tackles challenges like data quality, anomaly detection, and metadata management, while accelerating processes and enabling new paradigms like stream analytics and knowledge discovery.
This workshop explores AI-driven innovations in data engineering for enterprise systems and business intelligence. Focus areas include AI-enhanced pipelines, real-time processing, and adaptive architectures, bridging theoretical advances and practical applications for enterprise-scale decision-making.