CFP CAISE 2021

The CAiSE’21 organization calls for full papers with a special emphasis on the theme of Intelligent Information Systems. This year’s theme acknowledges the high level of uncertainty that organisations have to deal with, and the increasing need to respond through Intelligent Information Systems that provide trusted, adaptive, agile, and autonomous solutions. In the backdrop of recent advancements in IoT, big data analytics, artificial intelligence, machine learning, and blockchain, the Information Systems Engineering research community is ideally positioned to bring together the technical and empirical aspects of Intelligent Information Systems and contribute to progress in the field.

Besides offering an exciting scientific program, CAiSE’21 will feature a best paper award, a special issue, and a PhD-thesis award:

• Best Paper Award‚ prize EUR 1000  (sponsored by Springer)
• Special Issue of CAiSE’21 in the Information Systems Journal
• PhD-Thesis Award‚ best PhD thesis of a past CAISE Doctoral Consortium author (co-sponsored by the CAiSE Steering Committee and Springer)

Papers should be submitted in PDF format. Submissions must conform to Springer‚ LNCS format and should not exceed 15 pages, including all text, figures, references and appendices. Submissions not conforming to the LNCS format, exceeding 15 pages, or being obviously out of the scope of the conference, will be rejected without review.

The results described must be unpublished and must not be under review elsewhere. Three to five keywords characterising the paper should be listed at the end of the abstract. Each paper will be reviewed by at least two program committee members and, if positively evaluated, by one additional program board member. The selected papers will be discussed among the paper reviewers on-line and additionally during the program board meeting. Accepted papers will be presented at CAiSE’21 and published in the conference proceedings in the Springer Lecture Notes in Computer Science (LNCS).

We invite three types of original and scientific papers. The type of the submission must be indicated in the submission system. Each contribution should explicitly address the engineering or the operation of information systems, clearly identify the information systems problem addressed, the expected impact of the contribution to information system engineering or operation, and the research method used. We strongly advise authors to clearly emphasize these aspects in their paper, including the abstract.

• Technical papers describe original solutions (theoretical, methodological or conceptual) in the field of IS Engineering. A technical paper should clearly describe the situation or problem tackled, the relevant state of the art, the position or solution suggested and its potential‚ as well as demonstrate the benefits of the contribution through a rigorous evaluation.
• Empirical papers evaluate existing problem situations including problems encountered in practice, or validate proposed solutions with scientific means, i.e., by empirical studies, experiments, case studies, experience reports, simulations, etc. Scientific reflection on problems and practices in industry also falls into this category. The topic of the evaluation presented in the paper as well as its causal or logical properties must be clearly stated. The research method must be sound and appropriate.
• Exploratory papers can describe completely new research positions or approaches, in order to face a generic situation arising because of new ICT tools, new kinds of activities or new IS challenges. They must describe precisely the situation and demonstrate why current methods, tools, ways of reasoning, or meta-models are inadequate. They must also rigorously present their approach and demonstrate its pertinence and correctness to addressing the identified situation.

SUBMIT PAPER

The topics of contribution include but are not limited to:

• Novel approaches to IS Engineering
  • Artificial Intelligence 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
  • Neuro-Information Systems
  • Context-aware, autonomous and adaptive IS
  • Agile enterprise architecture and modeling
• Models, Methods and Techniques in IS Engineering
  • Conceptual modeling, languages and design
  • Requirements engineering
  • Process modelling, analysis and improvement
  • Process automation, mining and monitoring
  • Models and methods for evolution and reuse
  • 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
  • AI and machine learning techniques and methods in IS
  • Human-centred 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
• Domain Specific and multi-aspect IS Engineering
  • IT governance
  • eGovernment
  • Smart City management
  • IS for healthcare
  • Educational Systems and Learning Analytics
  • Value and supply chain management
  • Industry 4.0
  • Sustainability and social responsibility management
  • Privacy, security, trust, and safety management