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A Mobile Service Engine Enabling Complex Data Collection Applications

机译:支持复杂数据收集应用程序的移动服务引擎

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The widespread distribution of smart mobile devices offers promising perspectives for the timely collection of huge amounts of data. When realizing sophisticated mobile data collection applications, numerous technical issues arise. For example, as many real-world projects require the support of different mobile operating systems, platform-specific peculiarities must be properly handled. Existing approaches often rely on specifically tailored mobile applications. As a drawback, changes to the data collection procedure result in costly code adaptations. To remedy this drawback, a model-driven approach is proposed, enabling end-users (i.e., domain experts) to create mobile data collection applications themselves. This model relies on complex questionnaires called instruments. An instrument not only contains all information about the data to be collected, but additionally comprises information on how it shall be processed on different mobile operating systems. For this purpose, we developed an advanced mobile (kernel) service being capable of processing sophisticated instruments on various platforms. This paper discusses fundamental kernel requirements and introduces the developed architecture. Altogether, the mobile service allows for the effective use of smart mobile devices in data collection application scenarios (e.g., clinical trials).
机译:智能移动设备的广泛分布为及时收集大量数据提供了广阔的前景。当实现复杂的移动数据收集应用程序时,出现了许多技术问题。例如,由于许多现实世界项目需要不同移动操作系统的支持,因此必须正确处理特定于平台的特性。现有方法通常依赖于专门定制的移动应用程序。缺点是,对数据收集过程的更改会导致代码修改成本高昂。为了弥补这一缺点,提出了一种模型驱动的方法,使最终用户(即领域专家)能够自己创建移动数据收集应用程序。该模型依赖于称为工具的复杂调查表。仪器不仅包含有关要收集的数据的所有信息,而且还包含有关应如何在不同的移动操作系统上对其进行处理的信息。为此,我们开发了一种先进的移动(内核)服务,能够在各种平台上处理复杂的仪器。本文讨论了基本的内核要求,并介绍了开发的体系结构。总之,移动服务允许在数据收集应用场景(例如临床试验)中有效使用智能移动设备。

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