LAUSR

The special issue is motivated by the extensive growth of interest for embedding so-called Big Data, Wireless Sensor Networks (WSN), Cyber-Physical Systems (CPS) and Internet-ofThings (IoT) capabilities into traditional Enterprise Information Systems (EIS) architectures. In the EIS world, those new capabilities would significantly expand the scope of planning and monitoring to end-to-end processes, encompassing full supply chain, while also including new stakeholders or events having the impact to these processes. Networks of physical objects with sensing, data collection, transmission and actuation capabilities, and vast endpoints in the cloud, offering large amounts of heterogeneous data, become increasingly important enterprise resources and sources for fundamental analytics. The large number of identifiable devices, used also on a sharing basis, is expected to become a commodity in the future, also providing a technology tool for emergence of so-called ‘sensing enterprise’ (Noran, Romero, and Zdravković 2014). Technology stack seem to be already there, with large number of cloud-based IoT platforms, offering connectivity, storage, analytics and visualization in a secure way and at scale. However, critical issues still remain open. First, such diversity will pose tremendous challenges related to the interoperability issues. The new technological landscape, provided by the Future Internet systems will thus establish interoperability problems as critical and possibly consider the interoperability as an inherent capability of the future information systems. Second, while the interoperability is self-obvious challenge, implementation problem is inherited from the traditional EISs and even multiplied when considering significantly increased complexity of the EISs operating in IoT world. In order to capitalize on the technological trend of data sources commoditization and thus start evolving from digital to sensing enterprises, existing EISs need to change. Such change may imply any of the following: complete EIS re-design and re-deployment, full integration with off-the-shelf tools or empowering existing systems with specific interoperability infrastructures. The objective of this Special Issue is to present state-of-the-art research in using Model-Driven Engineering approaches, techniques, tools and practices to overcome issues arising from transition from traditional process-focused to data-intensive EIS, where this transition is facilitated by any of the three above mentioned approaches. The Issue is also expected to highlight new challenges and opportunities, related to the new role of EISs in the ‘datafied’ world we are living in, today.