research-article

Data is Personal: Attitudes and Perceptions of Data Visualization in Rural Pennsylvania

Authors:

Sofia E. Ayuso,

Omar El-EtrAuthors Info & Claims

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: 244, Pages 1 - 12

https://doi.org/10.1145/3290605.3300474

Published: 02 May 2019 Publication History

Abstract

Many of the guidelines that inform how designers create data visualizations originate in studies that unintentionally exclude populations that are most likely to be among the 'data poor'. In this paper, we explore which factors may drive attention and trust in rural populations with diverse economic and educational backgrounds - a segment that is largely underrepresented in the data visualization literature. In 42 semi-structured interviews in rural Pennsylvania (USA), we find that a complex set of factors intermix to inform attitudes and perceptions about data visualization - including educational background, political affiliation, and personal experience. The data and materials for this research can be found at https://osf.io/uxwts/

References

[1]

Basak Alper, Nathalie Henry Riche, Fanny Chevalier, Jeremy Boy, and Metin Sezgin. 2017. Visualization Literacy at Elementary School. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17. 5485--5497. Data is Personal CHI 2019, May 4--9, 2019, Glasgow, Scotland UK

Digital Library

[2]

Kevin Arceneaux, Martin Johnson, and Chad Murphy. 2012. Polarized political communication, oppositional media hostility, and selective exposure. The Journal of Politics 74, 1 (2012), 174--186.

[3]

Scott Bateman, Regan L Mandryk, Carl Gutwin, Aaron Genest, David Mcdine, and Christopher Brooks. 2010. Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts. In Proceedings of the 2010 CHI Conference on Human Factors in Computer Systems - CHI 2010. 2573--2582.

Digital Library

[4]

Michael A. Bedek, Alexander Nussbaumer, and Dietrich Albert Luca Huszar. 2017. Discovering Cognitive Biases in a Visual Analytics Environment. IEEE VIS 2017 Workshop: Dealing with Cognitive Biases in Visualisations (2017).

[5]

Michelle A. Borkin, Zoya Bylinskii, Nam Wook Kim, Constance May Bainbridge, Chelsea S Yeh, Daniel Borkin, Hanspeter Pfister, and Aude Oliva. 2016. Beyond Memorability: Visualization Recognition and Recall. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 519--528.

Digital Library

[6]

Michelle A Borkin, Azalea A Vo, Zoya Bylinskii, Phillip Isola, Shashank Sunkavalli, Aude Oliva, and Hanspeter Pfister. 2013. What makes a visualization memorable? IEEE Transactions on Visualization and Computer Graphics 19,12(2013),2306--15.

Digital Library

[7]

Michael Bostock, Vadim Ogievetsky, and Jeffrey Heer. 2011. D3 data-driven documents. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2301--2309.

Digital Library

[8]

Jeremy Boy, Anshul Vikram Pandey, John Emerson, Margaret Satterthwaite, Oded Nov, and Enrico Bertini. 2017. Showing People Behind Data. InProceedingsofthe2017CHIConferenceonHumanFactorsinComputing Systems - CHI '17. 5462--5474.

Digital Library

[9]

Jeremy Boy, Ronald A. Rensink, Enrico Bertini, and Jean Daniel Fekete. 2014. A principled way of assessing visualization literacy. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 1963--1972.

[10]

Jenna Burrell. 2018. Thinking relationally about digital inequality in rural regions of the U.S. First Monday 23, 6 (2018).

[11]

Kathy Charmaz and Linda Liska Belgrave. 2007. Grounded theory. The Blackwell encyclopedia of sociology (2007).

[12]

Luca Chittaro. 2006. Visualizing information on mobile devices. Computer 39, 3 (2006), 40--45.

Digital Library

[13]

C.A. Christofides, Pats Neelakantan, and Todd Behr. 2006. Examining the Rural-Urban Income Gap. Technical Report. Center for Rural Pennyslvania.

[14]

Evanthia Dimara, Anastasia Bezerianos, and Pierre Dragicevic. 2017. The Attraction Effect in Information Visualization. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017), 471--480.

Digital Library

[15]

Micheline Elias and Anastasia Bezerianos. 2011. Exploration views: Understanding dashboard creation and customization for visualization novices. In Lecture Notes in Computer Science, Vol. 6949 LNCS. 274--291. arXiv:9780201398298

Digital Library

[16]

Mi Feng, Cheng Deng, Evan M. Peck, and Lane Harrison. 2018. The Effects of Adding Search Functionality to Interactive Visualizations on the Web. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Article 137, 13 pages.

Digital Library

[17]

Anindya Ghose, Avi Goldfarb, and Sang Pil Han. 2012. How is the mobile Internet different? Search costs and local activities. Information Systems Research 24, 3 (2012), 613--631.

[18]

Kaushik Ghosh, Tapan S Parikh, and Apala Lahiri Chavan. 2003. Design considerations for a financial management system for rural, semi-literate users. In CHI'03 Extended Abstracts on Human Factors in Computing Systems. ACM, 824--825.

Digital Library

[19]

John K Gilbert. 2005. Visualization: A metacognitive skill in science and science education. In Visualization in Science Education. Springer, 9--27.

[20]

John K Gilbert. 2008. Visualization: An emergent field of practice and enquiry in science education. In Visualization: Theory and Practice in Science Education. Springer, 3--24.

[21]

Amy K Glasmeier, Chris Benner, and Chandrani Ohdedar. 2008. Broadband Internet Use in Rural Pennsylvania. Technical Report. The Center for Rural Pennsylvania.

[22]

LarsGrammel.2012. Userinterfacessupportinginformationvisualization novices in visualization construction. Ph.D. Dissertation. RWTH Aachen University. http://dspace.library.uvic.ca:8080/handle/1828/4359

[23]

Lars Grammel, Melanie Tory, and Margaret Anne Storey. 2010. How information visualization novices construct visualizations. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 943--952.

Digital Library

[24]

Anzu Hakone, Lane Harrison, Alvitta Ottley, Nathan Winters, Caitlin Gutheil, Paul K.J. Han, and Remco Chang. 2017. PROACT: Iterative Design of a Patient-Centered Visualization for Effective Prostate Cancer Health Risk Communication. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017), 601--610.

Digital Library

[25]

Sherry Hamby, Elizabeth Taylor, Alli Smith, Kimberly Mitchell, and Lisa Jones. 2018. Technology in Rural Appalachia: Cultural Strategies of Resistance and Navigation. International Journal of Communication 12 (2018), 1248--1268. http://ijoc.org.

[26]

Steve Haroz, Robert Kosara, and Steven L Franconeri. 2015. ISOTYPE Visualization - Working Memory, Performance, and Engagement with Pictographs. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15. 1191--1200.

Digital Library

[27]

Lane Harrison, Katharina Reinecke, and Remco Chang. 2015. Infographic aesthetics: Designing for the first impression. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI '15. ACM, 1187--1190.

Digital Library

[28]

Lane Harrison, Drew Skau, Steven Franconeri, Aidong Lu, and Remco Chang. 2013. Influencing visual judgment through affective priming. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI '13. 2949--2958.

Digital Library

[29]

Joseph Henrich, Steven J Heine, and Ara Norenzayan. 2010. Most people are not WEIRD. Nature 466, 7302 (2010), 29.

[30]

Jessica Hullman, Yea-Seul Kim, Francis Nguyen, Lauren Speers, and Maneesh Agrawala. 2018. Improving Comprehension of Measurements Using Concrete Re-Expression Strategies. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18. 1--12.

Digital Library

[31]

Helen Kennedy and Rosemary Lucy Hill. 2018. The feeling of numbers: Emotions in everyday engagements with data and their visualisation. Sociology 52, 4 (2018), 830--848.

[32]

Yea-Seul Kim, Jessica Hullman, and Maneesh Agrawala. 2016. Generating Personalized Spatial Analogies for Distances and Areas. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI '16 (2016), 38--48.

Digital Library

[33]

Yea-Seul Kim, Katharina Reinecke, and Jessica Hullman. 2017. Explaining the Gap. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17. 1375--1386.

Digital Library

[34]

Yea Seul Kim, Katharina Reinecke, and Jessica Hullman. 2018. Data Through Others' Eyes: The Impact of Visualizing Others' Expectations on Visualization Interpretation. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2018), 760--769. CHI 2019, May 4--9, 2019, Glasgow, Scotland UK Evan M. Peck, Sofia E. Ayuso, and Omar El-Etr

[35]

Laura M. Koesten, Emilia Kacprzak, Jenifer F. A. Tennison, and Elena Simperl. 2017. The Trials and tribulations of working with structured data- A study on information seeking behavior. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17. 1277--1289.

Digital Library

[36]

Ha-kyung Kong, Zhicheng Liu, and Karrie Karahalios. 2018. Frames and Slants in Titles of Visualizations on Controversial Topics. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18. 438:1--438:12.

Digital Library

[37]

Sukwon Lee, Sung Hee Kim, Ya Hsin Hung, Heidi Lam, Youn Ah Kang, and Ji Soo Yi. 2016. How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking. IEEETransactionsonVisualizationandComputerGraphics 22, 1 (2016), 499--508.

[38]

Sukwon Lee, Sung-Hee Kim, and Bum Chul Kwon. 2017. VLAT: Development of a visualization literacy assessment test. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017), 551--560.

Digital Library

[39]

Ralph Lengler. 2006. Identifying the competencies of 'Visual Literacy' - A prerequisite for knowledge visualization. In Proceedings of the International Conference on Information Visualisation. 232--236.

Digital Library

[40]

Gitte Lindgaard, Gary Fernandes, Cathy Dudek, and J. Brown. 2006. Attention web designers: You have 50 milliseconds to make a good first impression! Behaviour & Information Technology 25, 2 (2006), 115--126.

[41]

Adam V. Maltese, Joseph A Harsh, and Dubravka Svetina. 2015. Data visualization literacy: Investigating data interpretation along the novice--expert continuum. Journal of College Science Teaching 45, 1 (2015), 83--83.

[42]

Hamid Mansoor and Lane Harrison. 2017. Data Visualization Literacy and Visualization Biases : Cases for Merging Parallel Threads. IEEE VIS 2017 Workshop: Dealing with Cognitive Biases in Visualisations (2017).

[43]

Alvitta Ottley, Evan M Peck, Lane T Harrison, Daniel Afergan, Caroline Ziemkiewicz, Holly A Taylor, Paul KJ Han, and Remco Chang. 2016. Improving Bayesian reasoning: The effects of phrasing, visualization, and spatial ability. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 529--538.

Digital Library

[44]

Paul Parsons. 2017. Promoting Representational Fluency for Cognitive Bias Mitigation in Information Visualization. IEEE VIS 2017 Workshop: Dealing with Cognitive Biases in Visualisations (2017).

[45]

Andrew Perrin. 2017. Digital gap between rural and nonrural America persists | Pew Research Center. https://www.pewresearch.org/fact-tank/2017/05/19/ digital-gap-between-rural-and-nonrural-america-persists/

[46]

Lee Rainie, Pavani Reddy, and Peter Bell. 2004. Rural Areas and the Internet | Pew Research Center. http: //www.pewinternet.org/2004/02/17/rural-areas-and-the-internet/

[47]

Pew Research. 2014. Further Decline in Credibility Ratings for Most News Organizations. http://www.people-press.org/2012/08/16/ further-decline-in-credibility-ratings-for-most-news-organizations/ /

[48]

Jonathan C Roberts, Panagiotis D Ritsos, Sriram Karthik Badam, Dominique Brodbeck, Jessie Kennedy, and Niklas Elmqvist. 2014. Visualization beyond the desktop--the next big thing. IEEE Computer Graphics and Applications 34, 6 (2014), 26--34.

[49]

Puripant Ruchikachorn and Klaus Mueller. 2015. Learning visualizations by analogy: Promoting visual literacy through visualization morphing. IEEE Transactions on Visualization and Computer Graphics 21, 9 (2015), 1028--1044.

Digital Library

[50]

Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, and Jeffrey Heer. 2017. Vega-lite: A grammar of interactive graphics. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017), 341--350.

Digital Library

[51]

Arvind Satyanarayan, Ryan Russell, Jane Hoffswell, and Jeffrey Heer. 2016. Reactive vega: A streaming dataflow architecture for declarative interactive visualization. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 659--668.

Digital Library

[52]

Christina Simeone, Theodora Okiro, and Deshaun Bennett. 2018. Reimagining Pennsylvania's Coal Communities. Technical Report. Kleinman Center for Energy Policy, University of Pennsylvania. https: //kleinmanenergy.upenn.edu/sites/default/files/proceedingsreports/ ReimaginingPennsylvaniasCoalCommunities{_}0.pdf

[53]

AaronSmith.2013. TechnologyAdoptionbyLowerIncomePopulations | Pew Research Center. http://www.pewinternet.org/2013/10/08/ technology-adoption-by-lower-income-populations/

[54]

Eric Tsetsi and Stephen A. Rains. 2017. Smartphone Internet access and use:Extendingthedigitaldivideandusagegap. MobileMedia&Communication 2013 (2017), 1--17.

[55]

André Calero Valdez, Martina Ziefle, and Michael Sedlmair. 2018. Priming and Anchoring Effects in Visualization. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2018), 584--594.

[56]

Calero Valdez, Martina Ziefle, and Michael Sedlmair. 2017. A Framework for Studying Biases in Visualization Research. IEEE VIS 2017 Workshop: Dealing with Cognitive Biases in Visualisations (2017).

[57]

Fernanda B Viegas and Martin Wattenberg. 2006. Communicationminded visualization: A call to action. IBM Systems Journal 45, 4 (2006), 801.

Digital Library

[58]

Emily Wall, Leslie M Blaha, Celeste Lyn Paul, Kristin Cook, and Alex Endert. 2017. Four perspectives on human bias in visual analytics. IEEE VIS 2017 Workshop: Dealing with Cognitive Biases in Visualisations October (2017).

[59]

Kanit Wongsuphasawat, Dominik Moritz, Anushka Anand, Jock Mackinlay, Bill Howe, and Jeffrey Heer. 2016. Voyager: Exploratory analysis via faceted browsing of visualization recommendations. IEEE TransactionsonVisualization&ComputerGraphics 22,1(2016),649--658.

[60]

Wenfan Yan. 2006. Adult Education in Rural Pennsylvania. Technical Report. The Center for Rural Pennyslvania.

[61]

Liangzhi Yu. 2010. How poor informationally are the information poor? Journal of Documentation 66, 6 (2010), 906--933. arXiv:http://dx.doi.org/10.1108/BIJ-10--2012-0068

[62]

Liangzhi Yu. 2011. The divided views of the information and digital divides: A call for integrative theories of information inequality. Journal of Information Science 37, 6 (2011), 660--679.

Digital Library

Cited By

Fansher MWalls LHao CSubramonyam HBoduroglu AShah PWitt J(2025)Narrative visualizations: Depicting accumulating risks and increasing trust in dataCognitive Research: Principles and Implications10.1186/s41235-025-00613-w10:1Online publication date: 21-Feb-2025
https://doi.org/10.1186/s41235-025-00613-w
Lan XLiu Y(2025)“I Came Across a Junk”: Understanding Design Flaws of Data Visualization from the Public's PerspectiveIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345634131:1(393-403)Online publication date: Jan-2025
https://doi.org/10.1109/TVCG.2024.3456341
Donawa APowell CWang RChih MPatel RZinner RAronoff-Spencer EBaker C(2024)Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple’s ResearchKit and CareKit: Usability StudyJMIR Formative Research10.2196/578018(e57801)Online publication date: 26-Sep-2024
https://doi.org/10.2196/57801
Show More Cited By

Index Terms

Data is Personal: Attitudes and Perceptions of Data Visualization in Rural Pennsylvania
1. Human-centered computing
  1. Visualization
    1. Visualization theory, concepts and paradigms

Recommendations

Designing a personal information visualization tool
NordiCHI '10: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

Interacting with computers has become part of our daily lives. This interaction results in large amounts of personal information, spread throughout places and applications. As a consequence, it is quite difficult to get an overall view of all our ...
Visualizing personal digital collections
JCDL '10: Proceedings of the 10th annual joint conference on Digital libraries

This paper describes the use of relational database management system (RDBMS) and treemap visualization to represent and analyze a group of personal digital collections created in the context of work and with no external metadata. We evaluated the ...
Making a 'Place' for ICTs in Rural Communities: The role of village halls in digital inclusion
C&T '19: Proceedings of the 9th International Conference on Communities & Technologies - Transforming Communities

In this paper we look at how ICTs can become integrated into the workings of rural communities; how they might find their place -- both metaphorically in terms of the sense of community, and literally as a particular space. This is set in the context of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

9077 pages

ISBN:9781450359702

DOI:10.1145/3290605

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 May 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Badges

Best Paper

Author Tags

Qualifiers

Research-article

Conference

CHI '19

Sponsor:

SIGCHI

CHI '19: CHI Conference on Human Factors in Computing Systems

May 4 - 9, 2019

Glasgow, Scotland Uk

Acceptance Rates

CHI '19 Paper Acceptance Rate 703 of 2,958 submissions, 24%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

101
Total Citations
View Citations
3,021
Total Downloads

Downloads (Last 12 months)472
Downloads (Last 6 weeks)97

Reflects downloads up to 08 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Fansher MWalls LHao CSubramonyam HBoduroglu AShah PWitt J(2025)Narrative visualizations: Depicting accumulating risks and increasing trust in dataCognitive Research: Principles and Implications10.1186/s41235-025-00613-w10:1Online publication date: 21-Feb-2025
https://doi.org/10.1186/s41235-025-00613-w
Lan XLiu Y(2025)“I Came Across a Junk”: Understanding Design Flaws of Data Visualization from the Public's PerspectiveIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345634131:1(393-403)Online publication date: Jan-2025
https://doi.org/10.1109/TVCG.2024.3456341
Donawa APowell CWang RChih MPatel RZinner RAronoff-Spencer EBaker C(2024)Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple’s ResearchKit and CareKit: Usability StudyJMIR Formative Research10.2196/578018(e57801)Online publication date: 26-Sep-2024
https://doi.org/10.2196/57801
Johnson JItiola ARahman SSmith CSoprovich AWozniak LMarshall D(2024)Exploring patient perspectives on EQ-5D-5L data visualization within an individualized decision aid for total knee arthroplasty (TKA) in Alberta, CanadaBMC Musculoskeletal Disorders10.1186/s12891-024-07304-525:1Online publication date: 29-Feb-2024
https://doi.org/10.1186/s12891-024-07304-5
Wu KQuadri GWang AOsei-Tutu DPetersen EKoushik VSzafir D(2024)Our Stories, Our Data: Co-designing Visualizations with People with Intellectual and Developmental DisabilitiesProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675615(1-17)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3675615
Kim HLe KLim GKim DHong YKim J(2024)DataDive: Supporting Readers' Contextualization of Statistical Statements with Data ExplorationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645155(623-639)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645155
Ge LHedayati MCui YDing YBonilla KJoshi AOttley ABach BKwon BRapp DPeck EPadilla LCorrell MBorkin MHarrison LKay M(2024)Toward a More Comprehensive Understanding of Visualization LiteracyExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3636289(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3636289
Quadri GWang AWang ZAdorno JRosen PSzafir D(2024)Do You See What I See? A Qualitative Study Eliciting High-Level Visualization ComprehensionProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642813(1-26)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642813
Tran AGuo GTaylor JChan KRaymond EDisalvo C(2024)Situating Datasets: Making Public Eviction Data Actionable for Housing JusticeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642452(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642452
Lisnic MLex AKogan M(2024)"Yeah, this graph doesn't show that": Analysis of Online Engagement with Misleading Data VisualizationsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642448(1-14)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642448
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten