Growing spontaneous mobility demand and decreasing affinity to automobile ownership in young generations require integrated concepts for intermodal mobility. Especially in areas with insufficient capacity coverage by traditional public transport, adding alternative services, e.g. car sharing, seems promising. Currently, customers have to combine different means of transportation manually by checking several information sources, creating a combined itinerary and booking several, mode specific tickets. This paper presents an information system architecture, the so-called Mobility Broker, a joint platform for mobility services that enables provider collaboration to offer travelers the best possible combined service. Mobility Broker combines heterogeneous mobility service data, like time tables and car sharing places, using standardized open interfaces and well-known methods of data integration. The combined information allows intermodal routing for generating combined itineraries. Furthermore, it allows to use one ticket for heterogenous travelings. By this simplification of access to intermodal travel, we aim to foster the integration of alternative public transport modes. Thereby, the heterogeneous mobility service product characteristics and related synergy effects determine the approach fundamentally.
To improve data quality and save cost, clinical trials are nowadays performed using electronic data capture systems (EDCS) providing electronic case report forms (eCRF) instead of paper-based CRFs. However, such EDCS are insufficiently integrated into the medical workflow and lack in interfacing with other study-related systems. In addition, most EDCS are unable to handle image and biosignal data, although electrocardiography (EGC, as example for one-dimensional (1D) data), ultrasound (2D data), or magnetic resonance imaging (3D data) have been established as surrogate endpoints in clinical trials. In this paper, an integrated workflow based on OpenClinica, one of the world's largest EDCS, is presented. Our approach consists of three components for (i) sharing of study metadata, (ii) integration of large volume data into eCRFs, and (iii) automatic image and biosignal analysis. In all components, metadata is transferred between systems using web services and JavaScript, and binary large objects (BLOBs) are sent via the secure file transfer protocol and hypertext transfer protocol. We applied the close-looped workflow in a multicenter study, where long term (7 days/24 h) Holter ECG monitoring is acquired on subjects with diabetes. Study metadata is automatically transferred into OpenClinica, the 4 GB BLOBs are seamlessly integrated into the eCRF, automatically processed, and the results of signal analysis are written back into the eCRF immediately.
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