Abstract: amount of information like lifelogs needs concrete digitized data models on information sources and their connections. For lifel- ogging, we need to model one’s life in a way that a computer can translate and manage information where many research ef- forts are still needed to close the gap between real life models and computerized data models. This work studies a fundamen- tal lifelog data modeling method from a digitized information perspective that translates real life events as a composition of digitized and timestamped data streams. It should be noted that a variety of events occurred in one’s real life can’t be fully cap- tured by a limited numbers and types of sensors. It is also im- practical to ask a user to manually tag entire events and their minute detail relations. Thus we aim to develop the lifelog man- agement system architecture and service structures for people to facilitate mapping a sequence of sensor streams with real life activities. Technically we focus on time series data modeling and management as the first step toward lifelog data fusion and complex event detection.
lifelog data model,
real life logging