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Visual-interactive Querying for Multivariate Research Data Repositories using Bag-of-words

Scherer, Maximilian ; Landesberger von Antburg, Tatiana ; Schreck, Tobias (2013)
Visual-interactive Querying for Multivariate Research Data Repositories using Bag-of-words.
JCDL 2013. Proceedings.
doi: 10.1145/2467696.2467705
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Large amounts of multivariate data are collected in different areas of scientific research and industrial production. These data are collected, archived and made publicly available by research data repositories. In addition to meta-data based access, content-based approaches are highly desirable to effectively retrieve, discover and analyze data sets of interest. Several such methods, that allow users to search for particular curve progressions, have been proposed. However, a major challenge when providing content-based access - interactive feedback during query formulation - has not received much attention yet. This is important because it can substantially improve the user's search effectiveness. In this paper, we present a novel interactive feedback approach for content-based access to multivariate research data. Thereby, we enable query modalities that were not available for multivariate data before. We provide instant search results and highlight query patterns in the result set. Real-time search suggestions give an overview of important patterns to look for in the data repository. For this purpose, we develop a bag-of-words index for multivariate data as the back-end of our approach. We apply our method to a large repository of multivariate data from the climate research domain. We describe a use-case for the discovery of interesting patterns in maritime climate research using our new visual-interactive query tools.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2013
Autor(en): Scherer, Maximilian ; Landesberger von Antburg, Tatiana ; Schreck, Tobias
Art des Eintrags: Bibliographie
Titel: Visual-interactive Querying for Multivariate Research Data Repositories using Bag-of-words
Sprache: Englisch
Publikationsjahr: 2013
Verlag: ACM, New York
Veranstaltungstitel: JCDL 2013. Proceedings
DOI: 10.1145/2467696.2467705
Kurzbeschreibung (Abstract):

Large amounts of multivariate data are collected in different areas of scientific research and industrial production. These data are collected, archived and made publicly available by research data repositories. In addition to meta-data based access, content-based approaches are highly desirable to effectively retrieve, discover and analyze data sets of interest. Several such methods, that allow users to search for particular curve progressions, have been proposed. However, a major challenge when providing content-based access - interactive feedback during query formulation - has not received much attention yet. This is important because it can substantially improve the user's search effectiveness. In this paper, we present a novel interactive feedback approach for content-based access to multivariate research data. Thereby, we enable query modalities that were not available for multivariate data before. We provide instant search results and highlight query patterns in the result set. Real-time search suggestions give an overview of important patterns to look for in the data repository. For this purpose, we develop a bag-of-words index for multivariate data as the back-end of our approach. We apply our method to a large repository of multivariate data from the climate research domain. We describe a use-case for the discovery of interesting patterns in maritime climate research using our new visual-interactive query tools.

Freie Schlagworte: Forschungsgruppe Visual Search and Analysis (VISA), Business Field: Visual decision support, Multivariate data, Scientific research data, Repositories, Content based retrieval, Query interfaces, Bag-of-words
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 12 Nov 2018 11:16
Letzte Änderung: 22 Jul 2021 18:31
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