Demand for flexibility in electricity systems and the transition to the Smart Grid is increasing
opportunities for demand response (DR). However, there are many barriers which prevent …

Data integration, data sharing, and standardized analyses are important enablers for data‐
driven medical research. Circadian medicine is an emerging field with a particularly high …

The massive generation, extensive sharing, and deep exploitation of data in the big data era
have raised unprecedented privacy threats. To address privacy concerns, various privacy …

Location statistics collective release provides essential information to understand crucial
phenomena, including points of interest and movement patterns. Sharing location statistics …

Although time-series data collected from users can be utilized to provide services for various
applications, they could reveal sensitive information about users. Recently, local differential …

In real-time monitoring systems, fine-grained measurements would pose great privacy
threats to the participants as real-time measurements could disclose accurate people-centric …

Electric load profiles are highly relevant for battery storage research and industry as they
determine system design and operation strategies. However, data obtained from electrical …

Many recent applications depend on time series of data containing personal information. For
example, the smart grid collects and distributes time series of energy-consumption data from …

Realizing a Smart Grid without sacrificing the privacy of consumers is a challenging
problem. Data-centric approaches like Puffer fish ensure privacy by transforming data so that …

Publishing and sharing data is crucial for the data mining community, allowing collaboration
and driving open innovation. However, many researchers cannot release their data due to …