Within our research on robotic gas detection, we have focused on making a prototype based on Boston Dynamics SPOT, because it takes a lot of difficulties out of prototyping. For instance, it has its own obstacle avoidance algorithm, good drivers are available for ROS2, and SPOT is meant for outdoor navigation. Being a legged robot means that it can easily traverse curbs, shrubberies, unstable soil and even stairs. For this document, we are going to use the insights that we used when looking for a solution for SPOT.
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Locative mapping with smartphones is the process of collecting geo data using mobile applications that tells something about a place, based on user input. Results are typically visualized using maps. Usually when such data is collected, the researcher is interested in more than just the location of a person. Perhaps the researcher would like to ask some questions, add a photo or make a voice recording. Questions such as what types of data you want to collect and with whom greatly influence how to design this data collection process. In this HowTo we aim to guide you through such a process and help you make the best decision what software is best for your project. We further elaborate on how such a data collection process can be paired with participatory methods to get a deeper level of understanding of the data collected.
This project researches risk perceptions about data, technology, and digital transformation in society and how to build trust between organisations and users to ensure sustainable data ecologies. The aim is to understand the user role in a tech-driven environment and her perception of the resulting relationships with organisations that offer data-driven services/products. The discourse on digital transformation is productive but does not truly address the user’s attitudes and awareness (Kitchin 2014). Companies are not aware enough of the potential accidents and resulting loss of trust that undermine data ecologies and, consequently, forfeit their beneficial potential. Facebook’s Cambridge Analytica-situation, for instance, led to 42% of US adults deleting their accounts and the company losing billions. Social, political, and economic interactions are increasingly digitalised, which comes with hands-on benefits but also challenges privacy, individual well-being and a fair society. User awareness of organisational practices is of heightened importance, as vulnerabilities for users equal vulnerabilities for data ecologies. Without transparency and a new “social contract” for a digital society, problems are inevitable. Recurring scandals about data leaks and biased algorithms are just two examples that illustrate the urgency of this research. Properly informing users about an organisation’s data policies makes a crucial difference (Accenture 2018) and for them to develop sustainable business models, organisations need to understand what users expect and how to communicate with them. This research project tackles this issue head-on. First, a deeper understanding of users’ risk perception is needed to formulate concrete policy recommendations aiming to educate and build trust. Second, insights about users’ perceptions will inform guidelines. Through empirical research on framing in the data discourse, user types, and trends in organisational practice, the project develops concrete advice - for users and practitioners alike - on building sustainable relationships in a resilient digital society.
