Conference Information
CAiSE 2020: International Conference on Advanced Information Systems Engineering
http://caise20.imag.fr/
Submission Date:
2019-11-22
Notification Date:
2020-02-28
Conference Date:
2020-06-08
Location:
Grenoble, France
Years:
32
CCF: b   CORE: a   QUALIS: a2   Viewed: 10973   Tracked: 32   Attend: 0

Conference Location
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Call For Papers
 Besides offering an exciting scientific program, CAiSE’20 will feature a best paper award, a special issue, and a PhD-thesis award:

    Best Paper Award‚ prize 1 000 € (sponsored by Springer)
    Special Issue of CAiSE’20 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.

Information about the Springer LNCS format can be found at: https://www.springer.com/comp/lncs/authors.html

Submission is done through EasyChair at the following page: https://easychair.org/conferences/?conf=caise2020

Submissions

The results described must be unpublished and must not be under review elsewhere.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’20 and published in the conference proceedings in the Springer Lecture Notes in Computer Science (LNCS).

We invite four types of original and scientific papers:

    Formal and/or 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 the potential‚ or, even better, the evaluated‚ benefits of the contribution.
    Empirical evaluation papers evaluate existing problem situations or validate proposed solutions with scientific means, i.e., by empirical studies, experiments, case studies, simulations, formal analyses, mathematical proofs, 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.
    Experience papers present problems or challenges encountered in practice, relate success and failure stories, or report on industrial practice. The focus is on ‘what’ and on lessons learned, not on an in-depth analysis of ‘why’. The practice must be clearly described and its context must be given. Readers should be able to draw conclusions for their own practice.
    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.

The type of the submission must be indicated in the first page of the paper, under the title. For all the submissions and depending on their type, we invite the authors to be explicit about the research method used.

Contributions are welcome in terms of models, methods, techniques, architecture and technologies. Each contribution should explicitly address the engineering or the operation of information systems. Each contribution should clearly identify the information systems problem addressed as well as the expected positive impact of the contribution to information system engineering or operation. We strongly advise authors to clearly emphasize those aspects in their paper, including the abstract.

Contributions about methods, models, techniques, architectures and platforms for supporting the engineering and evolution of information systems and organizations could include (but are not limited to):

    Novel approaches to IS Engineering
        Context-aware and adaptive IS with self-* properties
        Agile enterprise architecture and modeling
        Blockchain applications in IS
        Application of AI and big data in IS
        Robotic Process Automation
        Digital twins
        Data and business analytics
        IS for collaboration and social computing
        Service science and innovation

    Models, Methods and Techniques in IS Engineering
        Conceptual modeling, languages and design
        Requirements engineering
        Process modeling, analysis, and mining
        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

    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 PAIS systems
        Handling of real time data streams
        Content management and semantic Web

    Domain Specific and multi-aspect IS Engineering
        IT governance
        eGovernment
        Smart City management
        IS for healthcare
        Educational IS
        Value and supply chain management
        Industry 4.0
        Sustainability and social responsibility management
        Privacy, security, trust, and safety management
        Dark data processing
Last updated by Dou Sun in 2019-08-15
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
20073014013.3%
20061893317.5%
20052723613.2%
20041603924.4%
20032194520.5%
20021734224.3%
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