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A Methodology and System For Big-Thick Data Collection

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dc.contributor.authorKayongo, Ivan
dc.contributor.authorZhao, Haonan
dc.contributor.authorMalcotti, Leonardo
dc.contributor.authorGiunchiglia, Fausto
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:25Z
dc.date.available2024-10-21T18:24:25Z
dc.date.issued2024
dc.description.abstractPervasive sensors have become essential in research for gathering real-world data. However, current studies often focus solely on objective data, neglecting subjective human contributions. We introduce an approach and system for collecting big-thick data, combining extensive sensor data (big data) with qualitative human feedback (thick data). This fusion enables effective collaboration between humans and machines, allowing machine learning to benefit from human behavior and interpretations. Emphasizing data quality, our system incorporates continuous monitoring and adaptive learning mechanisms to optimize data collection timing and context, ensuring relevance, accuracy, and reliability. The system comprises three key components: a) a tool for collecting sensor data and user feedback, b) components for experiment planning and execution monitoring, and c) a machine-learning component that enhances human-machine interaction.en
dc.identifier.doi10.18420/inf2024_33
dc.identifier.eissn2944-7682
dc.identifier.isbn978-3-88579-746-3
dc.identifier.issn2944-7682
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45192
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjectPersonal data collection
dc.subjectHuman-aware AI
dc.subjectBig-thick data
dc.subjectContext
dc.subjectdata quality
dc.titleA Methodology and System For Big-Thick Data Collectionen
dc.typeText/Conference Paper
gi.citation.endPage463
gi.citation.publisherPlaceBonn
gi.citation.startPage455
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitle8th International Workshop on Annotation of useR Data for UbiquitOUs Systems

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