Conference Information
CAiSE 2021: International Conference on Advanced Information Systems Engineering
https://caise21.org/
Submission Date:
2020-11-28
Notification Date:
2021-02-27
Conference Date:
2021-06-28
Location:
Melbourne, Australia
Years:
33
CCF: b   CORE: a   QUALIS: a2   Viewed: 14765   Tracked: 39   Attend: 2

Conference Location
Call For Papers
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The results described must be unpublished and must not be under review elsewhere.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.
Last updated by Dou Sun in 2020-06-07
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
20073014013.3%
20061893317.5%
20052723613.2%
20041603924.4%
20032194520.5%
20021734224.3%
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