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Context: Agile practices as well as UX methods are nowadays well-known and often adopted to develop complex software and products more efficiently and effectively. However, in the so called VUCA environment, which many companies are confronted with, the sole use of UX research is not sufficient to find the best solutions for customers. The implementation of Design Thinking can support this process. But many companies and their product owners don’t know how much resources they should spend for conducting Design Thinking.
Objective: This paper aims at suggesting a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent for Design Thinking activities.
Method: A case study was conducted for the development of the DEW index. Design Thinking was introduced into the regular development cycle of an industry Scrum team. With the support of UX and Design Thinking experts, a formula was developed to determine the appropriate effort for Design Thinking.
Results: The developed “Discovery Effort Worthiness Index” provides an easy-to-use tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. A company can map the corresponding Design Thinking methods to the results of the DEW Index calculation, and product owners can select the appropriate measures from this mapping. Therefore, they can optimize the effort spent for discovery and validation.
Continuous monitoring of individual vital parameters can provide information for the assessment of one’s health and indications of medical problems in the context of personalized medicine. Correlations between parameters and health issues are to be evaluated. As one project in this topic area, a telemedicine platform is implemented to gather data of outpatients via wearables and accumulate them for physicians and researchers to review. This work extracts requirements, draws use case scenarios, and shows the current system architecture consisting of a patient application, a physician application with a web server, and a backend server application. In further work, the prototype will assist to develop a vendor-free and open monitoring solution. A conclusion on functionality and usability will be evaluated in an imminent first study.
Massive data transfers in modern data-intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-Data processing (NDP) and a shift to code-to-data designs may represent a viable solution as packaging combinations of storage and compute elements on the same device has become feasible. The shift towards NDP system architectures calls for revision of established principles. Abstractions such as data formats and layouts typically spread multiple layers in traditional DBMS, the way they are processed is encapsulated within these layers of abstraction. The NDP-style processing requires an explicit definition of cross-layer data formats and accessors to ensure in-situ executions optimally utilizing the properties of the underlying NDP storage and compute elements. In this paper, we make the case for such data format definitions and investigate the performance benefits under RocksDB and the COSMOS hardware platform.