Lifelog Data Model and Management: Study on Research Challenges

Giunchiglia, Fausto and Kim, Pil Ho (2012) Lifelog Data Model and Management: Study on Research Challenges. Trento : Università degli Studi di Trento.

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    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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