Abstract
The ongoing digitalisation efforts of businesses are a driving force to expose processes as services to third parties to enable the integration into third-party applications (e.g., booking of a trip or requesting the quote for a complex product). To standardize processes and related data, increasingly semantic web technologies are used. This leads to a shared conceptualization of the business domains and results in a linked data service ecosystem for domain-specific services, allowing third parties to aggregate services to novel applications - even across different domains. Using semantic web technologies enables the standardized communication on machine level. But the integration of the user into the overall process is still a manual task. The aggregation of services to complex applications is mostly done at the service level. The User Interfaces (UI) for collecting input data for the processes are usually still hand-crafted for different user groups and environments.
Our claim is, that given a linked data service ecosystem, the UI for a business process can be modelled once and be automatically generated for the integration into different contexts. The models can be combined to automatically build complex UIs for combined linked data applications – thus, supporting the aggregation of applications on the user interface level. This paper presents an ontology-based, model-driven approach for modelling UIs for the automatic generation of dialog-based applications, providing output understood by associated linked data services. In addition, the paper shows that the approach is suited to combine UI models as components to build aggregated linked data service UIs.
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Hitz, M., Kessel, T., Pfisterer, D. (2018). Automatic UI Generation for Aggregated Linked Data Applications by Using Sharable Application Ontologies. In: Pires, L., Hammoudi, S., Selic, B. (eds) Model-Driven Engineering and Software Development. MODELSWARD 2017. Communications in Computer and Information Science, vol 880. Springer, Cham. https://doi.org/10.1007/978-3-319-94764-8_14
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