The Internet of Things (IoT) and the Industrial Internet of Things (IIoT) are fast-growing emerging topics of technical, social, and economic significance that not only affect work practices but also daily routines and habits. The IoT and IIoT comprise a network of smart physical things and devices (such as production machines and home appliances). The number of “things” connected via the internet or the intranet is constantly increasing. It is estimated that approximately 20 billion IoT devices will be online by 2020.
Internet of Things and IIoT devices communicate with one another through software technology with the aim of making them more autonomous and cooperative. In addition to technological advances in hardware for the efficient acquisition and communication of context and status data, software solutions in particular offer great potential for influencing many areas of everyday life and work; to this end, humans should be taken into account when designing new digital systems. The central element here is the use of digital data, which are now available in greater quantities and at a better quality than ever before. Currently, the amount of data produced daily is 2.5 quintillion bytes–this will continue to increase in coming years. These data contain much valuable information, which can only be obtained through appropriate data analyses and visualization and correct embedding in their context.
The term “data work” has evolved as a superordinate area that combines all aspects of work with data to derive meaningful information, such as data consolidation, data processing, data refinement, data analysis, and data visualization. This thesis focuses on end-user data work in the context of IoT and IIoT systems that supports users using their digital data by providing tailorable information visualizations and data analysis. From a Human Computer Interaction (HCI) perspective, this thesis examines how IoT and IIoT systems have to be designed to enable end-users to make digital data meaningful and usable. In this regard, and combining the areas of IoT system design, end-user development (EUD) and information visualization, the main goals of this thesis are:
• To gain a deeper understanding of the use and appropriation of IoT and IIoT technology in different contexts,
• To gain insights about the use of digital data for daily routines, habits and work practices; and
• To evaluate possibilities for the development of a system design for end-user data work.
This work is based on empirical field studies that investigate different settings (domestic and industrial) in the context of IoT and IIoT. Seen through the lens of appropriation, relevant practices for deploying and using IoT and IIoT technology, especially the practices of working with digital data to support routines, habits, and processes, are identified and discussed for different application areas. This has resulted in the development of system requirements to support the process of making abstract digital data accountable and meaningful for users in their everyday life and work practices.
Grounded in these results, a concept of an end-user data work tool that allows the consolidation of digital data across system boundaries, lets users adjust the system to their context, supports flexible data visualizations, and empowers collaborative data work is presented.