No Cover Image

Journal article 1689 views 407 downloads

Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection

Rita Borgo Orcid Logo, Joel Dearden Orcid Logo, Mark Jones Orcid Logo

IEEE Transactions on Visualization and Computer Graphics, Volume: 20, Issue: 12, Pages: 2261 - 2270

Swansea University Authors: Rita Borgo Orcid Logo, Joel Dearden Orcid Logo, Mark Jones Orcid Logo

DOI (Published version): 10.1109/TVCG.2014.2346428

Abstract

In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts...

Full description

Published in: IEEE Transactions on Visualization and Computer Graphics
Published: 2014
Online Access: http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf
URI: https://cronfa.swan.ac.uk/Record/cronfa18118
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2014-07-15T01:30:17Z
last_indexed 2023-01-31T03:23:44Z
id cronfa18118
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2023-01-30T14:47:31.5262885</datestamp><bib-version>v2</bib-version><id>18118</id><entry>2014-07-14</entry><title>Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection</title><swanseaauthors><author><sid>c4675d4072e4b2b3921ae57666f1d9ff</sid><ORCID>0000-0003-2875-6793</ORCID><firstname>Rita</firstname><surname>Borgo</surname><name>Rita Borgo</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>863620fedcf9cc672b4fc70ffa668099</sid><ORCID>0000-0002-2973-9592</ORCID><firstname>Joel</firstname><surname>Dearden</surname><name>Joel Dearden</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>2e1030b6e14fc9debd5d5ae7cc335562</sid><ORCID>0000-0001-8991-1190</ORCID><firstname>Mark</firstname><surname>Jones</surname><name>Mark Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2014-07-14</date><deptcode>SCS</deptcode><abstract>In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales. These all suffer from related problems. There is a limit to the dynamic range available for plotting numbers, and so the required dynamic range of the plot can exceed that of the depiction method. When that occurs, resolving, comparing and relating values across the display becomes problematical or even impossible for the user. With this in mind, we present an empirical study in which we compare logarithmic, linear, scale-stack bars and our new markers for 11 different stimuli grouped into 4 different tasks across all 8 marker types.</abstract><type>Journal Article</type><journal>IEEE Transactions on Visualization and Computer Graphics</journal><volume>20</volume><journalNumber>12</journalNumber><paginationStart>2261</paginationStart><paginationEnd>2270</paginationEnd><publisher/><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic/><keywords/><publishedDay>6</publishedDay><publishedMonth>11</publishedMonth><publishedYear>2014</publishedYear><publishedDate>2014-11-06</publishedDate><doi>10.1109/TVCG.2014.2346428</doi><url>http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf</url><notes/><college>COLLEGE NANME</college><department>Computer Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-01-30T14:47:31.5262885</lastEdited><Created>2014-07-14T19:00:57.1196930</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Rita</firstname><surname>Borgo</surname><orcid>0000-0003-2875-6793</orcid><order>1</order></author><author><firstname>Joel</firstname><surname>Dearden</surname><orcid>0000-0002-2973-9592</orcid><order>2</order></author><author><firstname>Mark</firstname><surname>Jones</surname><orcid>0000-0001-8991-1190</orcid><order>3</order></author></authors><documents><document><filename>0018118-15042015121032.pdf</filename><originalFilename>Order__of__Magnitude__Markers.pdf</originalFilename><uploaded>2015-04-15T12:10:32.0770000</uploaded><type>Output</type><contentLength>2048930</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2015-04-14T00:00:00.0000000</embargoDate><copyrightCorrect>true</copyrightCorrect></document></documents><OutputDurs/></rfc1807>
spelling 2023-01-30T14:47:31.5262885 v2 18118 2014-07-14 Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection c4675d4072e4b2b3921ae57666f1d9ff 0000-0003-2875-6793 Rita Borgo Rita Borgo true false 863620fedcf9cc672b4fc70ffa668099 0000-0002-2973-9592 Joel Dearden Joel Dearden true false 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 2014-07-14 SCS In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales. These all suffer from related problems. There is a limit to the dynamic range available for plotting numbers, and so the required dynamic range of the plot can exceed that of the depiction method. When that occurs, resolving, comparing and relating values across the display becomes problematical or even impossible for the user. With this in mind, we present an empirical study in which we compare logarithmic, linear, scale-stack bars and our new markers for 11 different stimuli grouped into 4 different tasks across all 8 marker types. Journal Article IEEE Transactions on Visualization and Computer Graphics 20 12 2261 2270 6 11 2014 2014-11-06 10.1109/TVCG.2014.2346428 http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2023-01-30T14:47:31.5262885 2014-07-14T19:00:57.1196930 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Rita Borgo 0000-0003-2875-6793 1 Joel Dearden 0000-0002-2973-9592 2 Mark Jones 0000-0001-8991-1190 3 0018118-15042015121032.pdf Order__of__Magnitude__Markers.pdf 2015-04-15T12:10:32.0770000 Output 2048930 application/pdf Version of Record true 2015-04-14T00:00:00.0000000 true
title Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
spellingShingle Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
Rita Borgo
Joel Dearden
Mark Jones
title_short Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
title_full Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
title_fullStr Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
title_full_unstemmed Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
title_sort Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
author_id_str_mv c4675d4072e4b2b3921ae57666f1d9ff
863620fedcf9cc672b4fc70ffa668099
2e1030b6e14fc9debd5d5ae7cc335562
author_id_fullname_str_mv c4675d4072e4b2b3921ae57666f1d9ff_***_Rita Borgo
863620fedcf9cc672b4fc70ffa668099_***_Joel Dearden
2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones
author Rita Borgo
Joel Dearden
Mark Jones
author2 Rita Borgo
Joel Dearden
Mark Jones
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 20
container_issue 12
container_start_page 2261
publishDate 2014
institution Swansea University
doi_str_mv 10.1109/TVCG.2014.2346428
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf
document_store_str 1
active_str 0
description In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales. These all suffer from related problems. There is a limit to the dynamic range available for plotting numbers, and so the required dynamic range of the plot can exceed that of the depiction method. When that occurs, resolving, comparing and relating values across the display becomes problematical or even impossible for the user. With this in mind, we present an empirical study in which we compare logarithmic, linear, scale-stack bars and our new markers for 11 different stimuli grouped into 4 different tasks across all 8 marker types.
published_date 2014-11-06T03:21:08Z
_version_ 1763750621855350784
score 11.035634

Similar Items