Design of collaborative and context aware mobile applications considering normative requirements from legal science and computer science (NORA)

情境感知应用程序支持用户以情境方式提供额外的服务和功能，当然是基于他们的情境。移动的设备在这种情况下发挥着至关重要的作用，允许通过物理和生理传感器收集和处理直接从用户环境中获取的信息。例如，情境感知应用程序可以获取用户的当前位置、活动以及他们的情绪和压力水平。协作上下文感知应用程序收集并联合收割机组合多个用户的数据，从而改进对这些信息的识别和预测，这通常通过机器学习来实现。通过使用额外的实体，可以提取新的例程和关于人们行为的信息。不幸的是，这种信息的协作处理对隐私构成了重大风险，因为敏感和与个人有关的信息是在外部实体上处理的。因此，该项目的目标是设计协作上下文感知和移动的应用程序以及机器学习算法，同时考虑法律和计算机科学的规范要求。通过使用规范性要求具体化的方法（德语：Methode zur Konkretisierung Normativer Anforderungen（KONA）），将推导出法律的以及技术标准、要求和设计。在项目实施过程中，规范性要求将进一步扩展，以适用于具体的技术设计，解决法律的问题（例如，数据稀缺性和透明度）以及技术规范和标准（例如，识别精度和处理时间）。这种仍待开发的方法KONA将在两个移动的协作上下文感知应用程序以及机器学习算法上进行评估，以识别和预测上下文信息。

Context-aware applications support users with additional services and functionalities in a situational manner and based, of course on their context. Mobile devices play a vital role in such scenarios, allowing for gathering and processing of information via physical and physiological sensors, taken directly from users’ environments. Context-aware applications, for example, can obtain users’ current locations, activities, as well as their emotions and stress levels. Collaborative context-aware applications gather and combine data of multiple users improving the recognition and prediction of such information, commonly realized via machine learning. By using additional entities, new routines, and information on people’s behaviour can be extracted. Such collaborative processing of information, unfortunately, poses a significant risk to privacy, as sensitive and person-related information is processed on external entities. The goal of this project is, therefore, to design collaborative context-aware and mobile applications as well as machine learning algorithms while considering normative requirements of the law and computer science. By using the method for concretizing normative requirements (in German: Methode zur Konkretisierung Normativer Anforderungen (KONA)) legal as well as technical criteria, requirements, and designs will be derived. In the course of the project, normative requirements will be further extended to apply to concrete technical designs, addressing legal (e.g., data scarcity and transparency) as well as technical norms and criteria (e.g., recognition accuracy and processing times). This still-to-be-developed method KONA will be evaluated on two mobile collaborative context-aware applications as well as machine learning algorithms to recognize and predict contextual information.