Giunchiglia, Fausto and Kim, Pil Ho (2012) Lifelog Data Model and Management: Study on Research Challenges. Trento : Università degli Studi di Trento.
￼Utilizing a computer to manage an enormous amount of information like lifelogs needs concrete digitized data models on information sources and their connections. For lifelogging, we need to model one’s life in a way that a computer can translate and manage information where many research efforts are still needed to close the gap between real life models and computerized data models. This work studies a fundamental lifelog data modeling method from a digitized information perspective that translates real life events into 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 captured by limited numbers and types of sensors. It is also impractical to ask a user to manually tag entire events and their minute detail relations. Thus we aim to develop the lifelog management 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.
|Item Type: ||Departmental Technical Report|
|FP7 Grant Agreement Number: ||info:eu-repo/grantAgreement/EC/FP7/287704|
|Department or Research center: ||Information Engineering and Computer Science|
|Subjects: ||Q Science > QA Mathematics > QA076 Computer software|
|Uncontrolled Keywords: ||event, information management, lifelog, lifelog data model, real life logging|
|Additional Information: ||Also published in "International Journal of Computer Information Systems and Industrial Management Applications", vol. 5, pp. 115-125, 2012.|
|Report Number: ||DISI-12-019|
|Repository staff approval on: ||05 Jul 2012 11:20|
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