Visual Intelligence Density

Show simple item record

dc.contributor.author Bai, Xiaoyan en
dc.contributor.author White, David en
dc.contributor.author Sundaram, David en
dc.contributor.editor Yang, J en
dc.contributor.editor Ginige, A en
dc.contributor.editor Mayr, HC en
dc.contributor.editor Kutsche, R-D en
dc.date.accessioned 2012-03-12T21:52:17Z en
dc.date.issued 2009 en
dc.identifier.citation In Information Systems: Modeling, Development, and Integration. Editors: Yang J, Ginige A, Mayr HC, Kutsche R-D. Springer Lecture Notes in BIS: 280-291. Springer, Sydney, Australia 2009 en
dc.identifier.isbn 9783642011122 en
dc.identifier.uri http://hdl.handle.net/2292/14039 en
dc.description.abstract Advanced visualization systems have been widely adopted by decision makers for dealing with problems involving spatial, temporal and multidimensional features. While these systems tend to provide reasonable support for particular paradigms, domains, and data types, they are very weak when it comes to supporting multi-paradigm, multi-domain problems that deal with complex spatio-temporal multi-dimensional data. This has led to visualizations that are context insensitive, data dense, and sparse in intelligence. There is a crucial need for visualizations that capture the essence of the relevant information in limited visual spaces allowing decision makers to take better decisions with less effort and time. To address these problems and issues, we propose a visual decision making process that increases the intelligence density of information provided by visualizations. Furthermore, we propose and implement a framework and architecture to support the above process in a flexible manner that is independent of data, domain, and paradigm. en
dc.description.uri http://librarysearch.auckland.ac.nz/primo_library/libweb/action/display.do?fn=search&doc=uoa_voyager1910539&vid=UOA2_A en
dc.publisher Springer en
dc.relation.ispartof Information Systems: Modeling, Development, and Integration en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Visual Intelligence Density en
dc.type Book Item en
dc.identifier.doi 10.1007/978-3-642-01112-2_29 en
pubs.begin-page 280 en
dc.rights.holder Copyright: Springer en
pubs.edition Springer Lecture Notes in BIS en
pubs.end-page 291 en
pubs.place-of-publication Sydney, Australia en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.elements-id 85183 en
pubs.org-id Business and Economics en
pubs.org-id Info Systems & Operations Mgmt en
pubs.record-created-at-source-date 2010-09-01 en


Files in this item

There are no files associated with this item.

Find Full text

This item appears in the following Collection(s)

Show simple item record

Share

Search ResearchSpace


Browse

Statistics