30th International Conference on Advanced Information Systems Engineering, Tallin, Estland

Abbrevation

CAiSE

Link

https://caise2018.ut.ee/call-for-papers/

City

Tallin

Country

Estonia

Deadline Paper

2017-12-01

Start Date

2018-06-11

End Date

2018-06-15

Abstract

Over the last years, Big Data and Artificial Intelligence technologies have gradually found their way into mainstream information systems. As these technologies mature and demonstrate their business value, they go from providing isolated functionality to becoming integrated into large and complex information systems, which entails that they have to be maintained and evolved in a sustainable manner. This maintenance imperative raises new challenges for information systems engineers due to the level of sophistication and the demanding infrastructure requirements that characterize these technologies. 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 Information Systems in The Big Data Era. This year’s theme acknowledges the disruptions brought about by the abundance of Big Data sources on government and business services, their users and customers, as well as the environments in which they are generated. This data abundance creates new opportunities to develop smart and personalized information systems, but also raises new challenges for information systems engineers, for example in the areas of scalable data cleaning, integration and processing, and real–time and predictive data analytics. Besides offering an exciting scientific program, CAiSE ’18 will feature a best paper award, a special issue, and a PhD–thesis award:201 Contributions about methods, models, techniques, architectures and platforms for supporting the engineering and evolution of information systems and organizations in the big data era 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 in and for IS Engineering Big Data architectures Cloud–based IS engineering Service oriented IS engineering Multi–agent IS engineering Robotic Process Automation Multi–platform IS engineeering Cyber–physical systems Big data and the Internet of Things Blockchains 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 eGovernment 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