Exploratory multimodal data analysis with standard multimedia player multimedia containers: a feasible solution to make multimodal research data accessible to the broad audience

Name: Exploratory multimodal data analysis with standard multimedia player multimedia containers: a feasible solution to make multimodal research data accessible to the broad audience
Author: Schoning, J., Gert, A. L., Açık, Alper, Kietzmann, T. C., Heidemann, G., Konig, P.

İsim	Exploratory multimodal data analysis with standard multimedia player multimedia containers: a feasible solution to make multimodal research data accessible to the broad audience
Yazar	Schoning, J., Gert, A. L., Açık, Alper, Kietzmann, T. C., Heidemann, G., Konig, P.
Basım Tarihi:	2017
Basım Yeri	- SCITEPRESS, Science and Technology Publications
Konu	Multimodal data analysis, Visualization, Sonification, Gaze data, EEG data
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-989-758-225-7
Kayıt Numarası	4d77fc85-108a-4889-a26e-94bbbf3a7ce3
Lokasyon	Psychology
Tarih	2017
Örnek Metin	The analysis of multimodal data comprised of images, videos and additional recordings, such as gaze trajectories, EEG, emotional states, and heart rate is presently only feasible with custom applications. Even exploring such data requires compilation of specific applications that suit a specific dataset only. This need for specific applications arises since all corresponding data are stored in separate files in custom-made distinct data formats. Thus accessing such datasets is cumbersome and time-consuming for experts and virtually impossible for non-experts. To make multimodal research data easily shareable and accessible to a broad audience, like researchers from diverse disciplines and all other interested people, we show how multimedia containers can support the visualization and sonification of scientific data. The use of a container format allows explorative multimodal data analyses with any multimedia player as well as streaming the data via the Internet. We prototyped this approach on two datasets, both with visualization of gaze data and one with additional sonification of EEG data. In a user study, we asked expert and non-expert users about their experience during an explorative investigation of the data. Based on their statements, our prototype implementation, and the datasets, we discuss the benefit of storing multimodal data, including the corresponding videos or images, in a single multimedia container. In conclusion, we summarize what is necessary for having multimedia containers as a standard for storing multimodal data and give an outlook on how artificial networks can be trained on such standardized containers.
Cilt	4

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Exploratory multimodal data analysis with standard multimedia player multimedia containers: a feasible solution to make multimodal research data accessible to the broad audience

Yazar Schoning, J., Gert, A. L., Açık, Alper, Kietzmann, T. C., Heidemann, G., Konig, P.

Basım Tarihi 2017

Basım Yeri - SCITEPRESS, Science and Technology Publications

Konu Multimodal data analysis, Visualization, Sonification, Gaze data, EEG data

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-989-758-225-7

Kayıt Numarası 4d77fc85-108a-4889-a26e-94bbbf3a7ce3

Lokasyon Psychology

Tarih 2017

Örnek Metin The analysis of multimodal data comprised of images, videos and additional recordings, such as gaze trajectories, EEG, emotional states, and heart rate is presently only feasible with custom applications. Even exploring such data requires compilation of specific applications that suit a specific dataset only. This need for specific applications arises since all corresponding data are stored in separate files in custom-made distinct data formats. Thus accessing such datasets is cumbersome and time-consuming for experts and virtually impossible for non-experts. To make multimodal research data easily shareable and accessible to a broad audience, like researchers from diverse disciplines and all other interested people, we show how multimedia containers can support the visualization and sonification of scientific data. The use of a container format allows explorative multimodal data analyses with any multimedia player as well as streaming the data via the Internet. We prototyped this approach on two datasets, both with visualization of gaze data and one with additional sonification of EEG data. In a user study, we asked expert and non-expert users about their experience during an explorative investigation of the data. Based on their statements, our prototype implementation, and the datasets, we discuss the benefit of storing multimodal data, including the corresponding videos or images, in a single multimedia container. In conclusion, we summarize what is necessary for having multimedia containers as a standard for storing multimodal data and give an outlook on how artificial networks can be trained on such standardized containers.

Cilt 4