@misc{HesseMatthiesSinzigetal.2019,
  author    = {Hesse, G{\"u}nter and Matthies, Christoph and Sinzig, Werner and Uflacker, Matthias},
  title     = {Adding Value by Combining Business and Sensor Data},
  series = {Database Systems for Advanced Applications},
  volume    = {11448},
  journal   = {Database Systems for Advanced Applications},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-18590-9},
  issn      = {0302-9743},
  doi       = {10.1007/978-3-030-18590-9_80},
  pages     = {528 -- 532},
  year      = {2019},
  abstract  = {Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data's full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs.},
  language  = {en}
}
@misc{SahlmannSchwotzer2018,
  author    = {Sahlmann, Kristina and Schwotzer, Thomas},
  title     = {Ontology-based virtual IoT devices for edge computing},
  series = {Proceedings of the 8th International Conference on the Internet of Things},
  journal   = {Proceedings of the 8th International Conference on the Internet of Things},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  isbn      = {978-1-4503-6564-2},
  doi       = {10.1145/3277593.3277597},
  pages     = {1 -- 7},
  year      = {2018},
  abstract  = {An IoT network may consist of hundreds heterogeneous devices. Some of them may be constrained in terms of memory, power, processing and network capacity. Manual network and service management of IoT devices are challenging. We propose a usage of an ontology for the IoT device descriptions enabling automatic network management as well as service discovery and aggregation. Our IoT architecture approach ensures interoperability using existing standards, i.e. MQTT protocol and SemanticWeb technologies. We herein introduce virtual IoT devices and their semantic framework deployed at the edge of network. As a result, virtual devices are enabled to aggregate capabilities of IoT devices, derive new services by inference, delegate requests/responses and generate events. Furthermore, they can collect and pre-process sensor data. These tasks on the edge computing overcome the shortcomings of the cloud usage regarding siloization, network bandwidth, latency and speed. We validate our proposition by implementing a virtual device on a Raspberry Pi.},
  language  = {en}
}
@misc{SahlmannSchefflerSchnor2018,
  author    = {Sahlmann, Kristina and Scheffler, Thomas and Schnor, Bettina},
  title     = {Ontology-driven Device Descriptions for IoT Network Management},
  series = {2018 Global Internet of Things Summit (GIoTS)},
  journal   = {2018 Global Internet of Things Summit (GIoTS)},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-5386-6451-3},
  doi       = {10.1109/GIOTS.2018.8534569},
  pages     = {295 -- 300},
  year      = {2018},
  abstract  = {One particular challenge in the Internet of Things is the management of many heterogeneous things. The things are typically constrained devices with limited memory, power, network and processing capacity. Configuring every device manually is a tedious task. We propose an interoperable way to configure an IoT network automatically using existing standards. The proposed NETCONF-MQTT bridge intermediates between the constrained devices (speaking MQTT) and the network management standard NETCONF. The NETCONF-MQTT bridge generates dynamically YANG data models from the semantic description of the device capabilities based on the oneM2M ontology. We evaluate the approach for two use cases, i.e. describing an actuator and a sensor scenario.},
  language  = {en}
}