As we navigate the physical and digital world, we unknowingly leave behind an immense trail of data. We are informed about this via lengthy documents (e.g., privacy policies) or short statements (e.g., cookie popups). However, even when we know that data is collected, we remain largely unaware of its nature; what information it contains and how it relates to us. Data is highly personal. It contains and reveals information about our behavior and experiences scattered over time, which can be abstract and opaque even to us. Dataslip is an interactive installation where the construct of personal data is translated into a material and tangible representation in the form of a receipt or ‘personal data slip’. The receipt contains detailed information and illustrative examples of the data generated from our interactions with five different categories of products and services: (1) personalized public transport cards, (2) supermarket loyalty cards, (3) credit and debit cards, (4) wearables, and (5) mobile apps. Its length is proportional to the amount of data collected about us. With dataslip, we aim to reduce the distance between individuals and their personal data, elicit confrontation and invite people to question their role within the personal data ecosystems in which they are embedded.@en

Age of Information (AoI) is a key metric to understand data freshness in Internet of Things (IoT) devices. In this paper we analyse an intermittently—powered IoT sensor-with mixed-memory (volatile and non-volatile) architecture—that uses a Time-Dependent Checkpointing (TDC) scheme. We derive the average Peak Age of Information (PAoI) and average AoI of the system, and use these metrics to understand which device parameters most significantly influence performance. We go on to consider how the average PAoI of a mixed-memory system compares with entirely volatile or entirely non-volatile architecture, and also introduce an alternative TDC strategy to improve system resilience in unpredictable environmental conditions.@en

Intermittent computing could be combined with low-powered visible light communication systems to facilitate novel sensor networks. This position paper provides a framework for future research by highlighting synergies between the technologies, and explores how techniques developed in intermittently-powered systems can be used to provide enhanced stability to ultra-low power visible light communication.

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