Theme: Responsible Information Systems
- Abstract submission: 23 November 2018
- Paper submission: 30 November 2018 – 23:59 PST (strict)
- Notification to authors: 28 February 2019
Modern companies and governments are increasingly software-managed as they become more digitalized and automated. The effects of digitalization enabled new economic models and transformed entire industries. Trends like IoT, big data analytics, artificial intelligence, machine learning, as well as blockchain technology are expected to push digital transformation even further. Changes occur at an ever-increasing pace, require from organizations high velocity decision-making and flexible information systems that can rapidly align to these changes. While many of these technologies bear huge potential for information systems, increasing flexibility and supporting decision-making, they also raise privacy, security, and ethical concerns and require trustworthiness. This poses new challenges for information systems engineers.
The CAiSE conference will continue its tradition as the premiere venue for innovative and rigorous research across the whole spectrum of Information Systems Engineering, while placing a special emphasis on the theme of Responsible Information Systems. This year‚ the conference theme acknowledges the need for designing information systems that are not only flexible enough for digital transformation, but are also responsible by considering privacy, security, and ethical concerns and providing trustworthiness.
Besides offering an exciting scientific program, CAiSE’19 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’19 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:
Submission is done through EasyChair at the following page:
The results described must be unpublished and must not be under review elsewhere.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’19 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 systems
- Agile enterprise models and architecture
- Distributed, mobile and open architecture
- IS for collaboration
- Social computing
- Customer analytics
- Big data application in IS
- Application of AI in IS
- Data and business analytics
- Use of new visualization techniques in IS
- Service science and innovation
- Models, Methods and Techniques in IS Engineering
- Conceptual modeling, languages and design
- Requirements engineering
- Business process modeling, analysis, and engineering
- Process mining
- Models and methods for evolution and reuse
- Domain and method engineering
- Variability and configuration management
- Compliance and alignment handling
- Active and interactive models
- Quality of IS models for analysis and design
- Architectures and Platforms for IS Engineering
- Big Data architectures
- Cloud-based IS engineering
- Service oriented IS engineering
- Multi-agent IS engineering
- Robotic Process Automation
- Multi-platform IS engineering
- Cyber-physical systems
- Big data and the Internet of Things
- Digital twins
- Workflow and PAIS systems
- Handling of real time data streams
- Content management and semantic Web
- Domain Specific and multi-aspect IS Engineering
- IT governance
- Smart City management
- Industrial ecology management
- IS for healthcare
- Educational IS
- Value and supply chain management
- Industry 4.0
- Sustainability and social responsibility management
- Predictive information systems
- Big Data and privacy
- Security and safety management
- Dark data processing