Aufgrund von Vorbereitungen auf eine neue Version von KOPS, können am Montag, 6.2. und Dienstag, 7.2. keine Publikationen eingereicht werden. (Due to preparations for a new version of KOPS, no publications can be submitted on Monday, Feb. 6 and Tuesday, Feb. 7.)
Type of Publication: | Contribution to a conference collection |
URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-68784 |
Author: | Mansmann, Svetlana; Mansmann, Florian; Scholl, Marc H.; Keim, Daniel A. |
Year of publication: | 2007 |
Conference: | 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007), 2007, Aachen, Germany |
Published in: | 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007), Aachen, Germany, 2007 |
Summary: |
Analysts interact with OLAP data in a predominantly drill-down fashion, i.e. gradually descending from a coarsely grained overview towards the desired level of detail. Analysis tools enable visual exploration as a sequence of navigation steps in the data cubes and their dimensional hierarchies. However, most state-of-the-art solutions are limited either in their capacity to handle complex multidimensional data or in the ability of their visual metaphors to provide an overview+details context. This work proposes an explorative framework for OLAP data based on a simple but powerful approach to analyzing data cubes of virtually arbitrary complexity. The data is queried using an intuitive navigation in which each dimension is represented by its hierarchy schema. Any granularity level can be dragged into the visualization to serve as an disaggregation axis. The results of the iterative exploration are mapped to a specified visualization technique. We favor hierarchical layouts for their natural ability to show step-wise decomposition of aggregate values. The power of the tool to support various application scenarios is demonstrated by presenting use cases from different domains and the visualization techniques suitable for solving specific analysis tasks.
|
Subject (DDC): | 004 Computer Science |
Link to License: | Attribution-NonCommercial-NoDerivs 2.0 Generic |
Bibliography of Konstanz: | Yes |
MANSMANN, Svetlana, Florian MANSMANN, Marc H. SCHOLL, Daniel A. KEIM, 2007. Hierarchy-driven Exploration of Multidimensional Data Cubes. 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007). Aachen, Germany, 2007. In: 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007), Aachen, Germany, 2007
@inproceedings{Mansmann2007Hiera-5648, title={Hierarchy-driven Exploration of Multidimensional Data Cubes}, year={2007}, booktitle={12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007), Aachen, Germany, 2007}, author={Mansmann, Svetlana and Mansmann, Florian and Scholl, Marc H. and Keim, Daniel A.} }
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/5648"> <dc:contributor>Mansmann, Florian</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:bibliographicCitation>First publ. in: 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW 2007), Aachen, Germany, 2007</dcterms:bibliographicCitation> <dc:creator>Keim, Daniel A.</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:57:29Z</dcterms:available> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5648/1/MMSK_BTW2007.pdf"/> <dc:creator>Scholl, Marc H.</dc:creator> <dcterms:issued>2007</dcterms:issued> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5648/1/MMSK_BTW2007.pdf"/> <dc:language>eng</dc:language> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5648"/> <dcterms:title>Hierarchy-driven Exploration of Multidimensional Data Cubes</dcterms:title> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:creator>Mansmann, Florian</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:57:29Z</dc:date> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:contributor>Scholl, Marc H.</dc:contributor> <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights> <dc:format>application/pdf</dc:format> <dcterms:abstract xml:lang="eng">Analysts interact with OLAP data in a predominantly drill-down fashion, i.e. gradually descending from a coarsely grained overview towards the desired level of detail. Analysis tools enable visual exploration as a sequence of navigation steps in the data cubes and their dimensional hierarchies. However, most state-of-the-art solutions are limited either in their capacity to handle complex multidimensional data or in the ability of their visual metaphors to provide an overview+details context. This work proposes an explorative framework for OLAP data based on a simple but powerful approach to analyzing data cubes of virtually arbitrary complexity. The data is queried using an intuitive navigation in which each dimension is represented by its hierarchy schema. Any granularity level can be dragged into the visualization to serve as an disaggregation axis. The results of the iterative exploration are mapped to a specified visualization technique. We favor hierarchical layouts for their natural ability to show step-wise decomposition of aggregate values. The power of the tool to support various application scenarios is demonstrated by presenting use cases from different domains and the visualization techniques suitable for solving specific analysis tasks.</dcterms:abstract> <dc:contributor>Mansmann, Svetlana</dc:contributor> <dc:creator>Mansmann, Svetlana</dc:creator> </rdf:Description> </rdf:RDF>
MMSK_BTW2007.pdf | 559 |