A Scalable and Semantic Data as a Service Marketplace for Enhancing Cloud-Based Applications

Data handling and provisioning play a dominant role in the structure of modern cloud–fog-based architectures. Without a strict, fast, and deterministic method of exchanging data we cannot be sure about the performance and efficiency of transactions and applications. In the present work we propose an architecture for a Data as a Service (DaaS) Marketplace, hosted exclusively in a cloud environment. The architecture includes a storage management engine that ensures the Quality of Service (QoS) requirements, a monitoring component that enables real time decisions about the resources used, and a resolution engine that provides semantic data discovery and ranking based on user queries. We show that the proposed system outperforms the classic ElasticSearch queries in data discovery use cases, providing more accurate results. Furthermore, the semantic enhancement of the process adds extra results which extend the user query with a more abstract definition to each notion. Finally, we show that the real-time scaling, provided by the data storage manager component, limits QoS requirements by decreasing the latency of the read and write data requests

Understanding New Product Development and Value Creation for the Internet of Things

This thesis investigates IoT development processes and value creation from the perspective of the business. At the onset of the research there is a lack of existing research on how IoT products and services are designed and developed. IoT is distinctive to traditional product as it is the combination of physical components, smart components, and connectivity that allows for continuous value improvement. Consequently, New Product Development (NPD) process of IoT should reflect vital characteristics of networked artefacts and integrate the data science process. To achieve the research aim, the study is based on the literature review and an inductive approach, using a qualitative research methodology. Through a comprehensive literature review covering interdisciplinary subjects from economics, business, engineering, information systems, innovation, and design studies, a theoretical foundation of value creation activities, a NPD process and practice and design roles are developed. An exploratory multiple case study is adopted to gain a primary understanding of IoT design and development. Six cases are selected for the study from various sectors, including healthcare, smart home, drain maintenance, dairy, vertical farming, and tropical farming. Within the case study methodology, semi-structured interview, document reviews and graphic elicitation are adopted to capture each participant’s distinctive experience and design challenges within the context of the given project. Thematic analysis is used for a purely qualitative, rich, detailed yet complex, account of data analysis in IoT development. The transcribed interview script contents and obtained documents for all the cases are carefully analysed through within- and cross-case analysis strategies, using thematic analysis. To enhance the study trustworthiness, triangulation of multiple data sources, member checks, peer reviews and experts’ reviews are drawn upon. Through the discussion, the conceptual model of the IoT NPD process, the Mobius strip model, is developed, reflecting the attributes of complex development practice, challenges and value creation. The Mobius Strip Model implies three infinite loops of value creation and NPD activities each of which are a hardware centred, software centred, and data and algorithms centred IoT NPD. The hardware centred NPD cycle is hardware centred development which has stricter review gates compared to other two software centred and data/algorithms centred development cycles. The software centred NPD cycle is more flexible, efficient, and effective without major modification to the IoT system. The data and algorithms centred IoT NPD is slow and time-consuming, reflecting the challenges of the data science process. The IoT NPD process involves three different types of subject matter, hardware, software, and data/algorithms development. This research confirmed that value of IoT system can be created through a hardware centred, software centred, and data & algorithms centred which was reflected to a conceptual model. Service-Dominant Logic is applied as the fundamental theory that can explain IoT value creation, including delivering service and scaling up, value co-creation, and user-driven development. However, emerging theories, such as the value space framework, and data as critical resource for value creation, complement to comprehend IoT value creation. Design is not utilised to its full extent but limited as styling and a process within IoT development. Design as styling is mainly focused on designing, prototyping, and testing the product or user interface of web and app, and design as a process is utilised to identify user needs and develop solution ideation. This study provides businesses with an integrative understanding of the value creation, development process, and various challenges in IoT development. The proposed conceptual model of IoT NPD, 'The Mobius Strip Model’, contributes to a body of research by combining interdisciplinary knowledge within the process. The model provides a foundation for scholars to construct other knowledge upon, including business models, development risks, innovation, design, and product management studies