CAiSE 2025 in Vienna: deadlines are near!

[Lukyanenko, Roman (ufc4tu)]

Dear Colleagues,

This is a reminder that if you are planning to submit a paper to CAiSE 2025 in Vienna, the premier conference on advanced information systems engineering, the deadlines are approaching:

Event
Date
Abstract Submission
November 22, November 29, 2024 (mandatory)
Paper Submission
December 01 December 06, 2024
Notification of Acceptance
February 28, 2025
Camera-ready Papers
April 14, 2025
Author Registration Deadline
April 14, 2025

[cid:image002.png at 01DB3FF0.807E3FA0]Engineering real-world information systems requires a coherent design encompassing human, organizational, economic, societal, and technological aspects. Information systems are applied in diverse contexts such as business process management, geographical information systems, and digital twins. The discipline continually evolves with trends in data science, machine learning, process mining, blockchain, mobile computing, sustainability, new regulations, cyber warfare, and military conflicts, all influencing its development. Each application context and emerging trend can lead to specializations within information systems engineering, necessitating various research traditions and needs. While beneficial, these specializations risk creating silos. Thus, the CAiSE conference, the premier event for this discipline, aims to prevent such fragmentation.

Topics of Contribution
The topics of contribution include but are not limited to:
Novel Approaches to IS Engineering

  *   Artificial Intelligence including generative AI and Machine Learning
  *   Robotic Process Automation (RPA)
  *   Big Data, Data Science and Analytics
  *   Blockchain applications in IS
  *   Simulation and Digital Twins
  *   IS for collaboration and social computing
  *   Virtual Reality / Augmented Reality
  *   Context-aware, autonomous and adaptive IS
Models, Methods and Techniques in IS Engineering

  *   Ontologies and Ontology Engineering
  *   Conceptual modeling, languages and design
  *   Requirements engineering
  *   Business process modeling, analysis and improvement
  *   Process automation, mining and monitoring
  *   Models and methods for evolution and reuse
  *   Low-code/no-code technology
  *   Domain and method engineering
  *   Product lines, variability and configuration management
  *   Compliance and alignment handling
  *   Active and interactive models
  *   Quality of IS models for analysis and design
  *   Visualization techniques in IS
  *   Decision models and business intelligence
  *   Knowledge graphs
  *   Human-centered techniques
Architectures and Platforms for IS Engineering

  *   Distributed, mobile and open architecture
  *   Big Data architectures
  *   Cloud- and edge-based IS engineering
  *   Service oriented and multi-agent IS engineering
  *   Multi-platform IS engineering
  *   Cyber-physical systems and Internet of Things (IoT)
  *   Workflow and Process Aware Information Systems (PAIS)
  *   Handling of real time data streams
  *   Content management and semantic Web
  *   Crowdsourcing platforms
  *   Conversational agents (chatbots)
  *   Microservices design and deployment
Domain-specific and Multi-aspect IS Engineering

  *   IT governance
  *   eGovernment
  *   Autonomous and smart systems (smart city management, smart vehicles, etc.)
  *   IS for healthcare
  *   Educational Systems and Learning Analytics
  *   Value and supply chain management
  *   Industry 4.0/Industry 5.0
  *   Sustainability and social responsibility management
  *   Privacy, security, trust, and safety management

For more details, please visit: https://conferences.big.tuwien.ac.at/caise2025/index.php


Best regards,

Roman
Roman Lukyanenko
Associate Professor of Commerce
McIntire School of Commerce
University of Virginia
https://www.commerce.virginia.edu/faculty/ufc4tu

Recent: Universal Modeling<https://link.springer.com/article/10.1007/s10270-024-01207-8> -  Transparency in Design Science<https://libraopen.lib.virginia.edu/downloads/gt54kn21t> - Open citizen science<https://theoryandpractice.citizenscienceassociation.org/articles/10.5334/cstp.676> - Trust in AI<https://link.springer.com/article/10.1007/s12525-022-00605-4> - Data Narratives for Analytics<https://pubsonline.informs.org/doi/10.1287/isre.2022.1141> (Video<https://www.youtube.com/watch?v=DgKUUG_CYy4>) - OA Articles<https://orcid.org/0000-0001-8125-5918> - RG<https://www.researchgate.net/profile/Roman-Lukyanenko> - GoogleScholar<https://scholar.google.com/citations?user=t0ysd44AAAAJ&hl=en&oi=ao>

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