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An Interview Method for Engaging Personal Data

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Published:30 December 2021Publication History
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Abstract

Whether investigating research questions or designing systems, many researchers and designers need to engage users with their personal data. However, it is difficult to successfully design user-facing tools for interacting with personal data without first understanding what users want to do with their data. Techniques for raw data exploration, sketching, or physicalization can avoid the perils of tool development, but prevent direct analytical access to users' rich personal data. We present a new method that directly tackles this challenge: the data engagement interview. This interview method incorporates an analyst to provide real-time personal data analysis, granting interview participants the opportunity to directly engage with their data, and interviewers to observe and ask questions throughout this engagement. We describe the method's development through a case study with asthmatic participants, share insights and guidance from our experience, and report a broad set of insights from these interviews.

References

  1. 2014. Smoothed Z Score Algorithm, Stack Overflow. https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/22640362#22640362. Accessed: 2017--05-15.Google ScholarGoogle Scholar
  2. Richard Arias-Hernandez, Linda T. Kaastra, Tera M. Green, and Brian Fisher. 2011. Pair Analytics: Capturing Reasoning Processes in Collaborative Visual Analytics. In 2011 44th Hawaii International Conference on System Sciences. IEEE, 1--10. https://doi.org/10.1109/HICSS.2011.339Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Frank Bentley, Konrad Tollmar, Peter Stephenson, Laura Levy, Brian Jones, Scott Robertson, Ed Price, Richard Catrambone, and Jeff Wilson. 2013. Health Mashups: Presenting Statistical Patterns between Wellbeing Data and Context in Natural Language to Promote Behavior Change. ACM Transactions on Computer-Human Interaction 20, 5 (2013), 1--27. https://doi.org/10.1145/2503823Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Hugh Beyer and Karen Holtzblatt. 1999. Contextual design. interactions 6, 1 (1999), 32--42.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Matthew Brehmer and Tamara Munzner. 2013. A multi-level typology of abstract visualization tasks. IEEE transactions on visualization and computer graphics 19, 12 (2013), 2376--2385.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Jeffrey Browne, Bongshin Lee, Sheelagh Carpendale, Nathalie Riche, and Timothy Sherwood. 2011. Data analysis on interactive whiteboards through sketch-based interaction. Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces, ITS'11 December 2014 (2011), 154--157. https://doi.org/10.1145/2076354.2076383Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Bill Buxton. 2007. The anatomy of sketching. Sketching User Experiences. Getting the Design Right and the Right Design. Morgan Kauffman (2007) (2007), 105--113.Google ScholarGoogle Scholar
  8. Bill Buxton. 2010. Sketching user experiences: getting the design right and the right design. Morgan kaufmann.Google ScholarGoogle Scholar
  9. Tim Campbell, Eric Larson, Gabe Cohn, Jon Froehlich, Ramses Alcaide, and Shwetak N. Patel. 2010. WATTR: A Method for Self-powered Wireless Sensing of Water Activity in the Home. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing (Copenhagen, Denmark) (UbiComp '10). ACM, New York, NY, USA, 169--172. https://doi.org/10.1145/1864349.1864378Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Mackinlay Card. 1999. Readings in information visualization: using vision to think. Morgan Kaufmann.Google ScholarGoogle Scholar
  11. Eun Kyoung Choe, Saeed Abdullah, Mashfiqui Rabbi, Edison Thomaz, Daniel A. Epstein, Felicia Cordeiro, Matthew Kay, Gregory D. Abowd, Tanzeem Choudhury, James Fogarty, Bongshin Lee, Mark Matthews, and Julie A. Kientz. 2017. Semi-Automated Tracking: A Balanced Approach for Self-Monitoring Applications. IEEE Pervasive Computing 16, 1 (jan 2017), 74--84. https://doi.org/10.1109/MPRV.2017.18Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Eun Kyoung Choe, Bongshin Lee, Haining Zhu, Nathalie Henry Riche, and Dominikus Baur. 2017. Understanding self-reflection: how people reflect on personal data through visual data exploration. In Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. ACM, 173--182.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Eun Kyoung Choe, Nicole B Lee, Bongshin Lee, Wanda Pratt, and Julie A Kientz. 2014. Understanding quantified-selfers' practices in collecting and exploring personal data. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1143--1152.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Chia-Fang Chung, Elena Agapie, Jessica Schroeder, Sonali Mishra, James Fogarty, and Sean A Munson. 2017. When personal tracking becomes social: Examining the use of Instagram for healthy eating. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 1674--1687.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Chia-Fang Chung, Qiaosi Wang, Jessica Schroeder, Allison Cole, Jasmine Zia, James Fogarty, and Sean A Munson. 2019. Identifying and Planning for Individualized Change: Patient-Provider Collaboration Using Lightweight Food Diaries in Healthy Eating and Irritable Bowel Syndrome. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 3, 1 (2019), 1--27.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Sunny Consolvo, Katherine Everitt, Ian Smith, and James A Landay. 2006. Design requirements for technologies that encourage physical activity. In Proceedings of the SIGCHI conference on Human Factors in computing systems. 457--466.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Sunny Consolvo, David W McDonald, Tammy Toscos, Mike Y Chen, Jon Froehlich, Beverly Harrison, Predrag Klasnja, Anthony LaMarca, Louis LeGrand, Ryan Libby, et al. 2008. Activity sensing in the wild: a field trial of ubifit garden. In Proceedings of the SIGCHI conference on human factors in computing systems. 1797--1806.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Felicia Cordeiro, Daniel A Epstein, Edison Thomaz, Elizabeth Bales, Arvind K Jagannathan, Gregory D Abowd, and James Fogarty. 2015. Barriers and negative nudges: Exploring challenges in food journaling. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. 1159--1162.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Nils Dahlbäck, Arne Jönsson, and Lars Ahrenberg. 1993. Wizard of Oz studies---why and how. Knowledge-based systems 6, 4 (1993), 258--266.Google ScholarGoogle Scholar
  20. Tamraparni Dasu and Theodore Johnson. 2003. Exploratory data mining and data cleaning. Vol. 479. John Wiley & Sons.Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Janet Dickson, Jim McLennan, and Mary M Omodei. 2000. Effects of concurrent verbalization on a time-critical, dynamic decision-making task. The Journal of general psychology 127, 2 (2000), 217--228.Google ScholarGoogle ScholarCross RefCross Ref
  22. Daniel Epstein, Felicia Cordeiro, Elizabeth Bales, James Fogarty, and Sean Munson. 2014. Taming data complexity in lifelogs: exploring visual cuts of personal informatics data. In Proceedings of the 2014 conference on Designing interactive systems. ACM, 667--676.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Daniel A. Epstein, Clara Caldeira, Mayara Costa Figueiredo, Xi Lu, Lucas M. Silva, Lucretia Williams, Jong Ho Lee, Qingyang Li, Simran Ahuja, Qiuer Chen, Payam Dowlatyari, Craig Hilby, Sazeda Sultana, Elizabeth V. Eikey, and Yunan Chen. 2020. Mapping and Taking Stock of the Personal Informatics Literature. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 4, Article 126 (Dec. 2020), 38 pages. https://doi.org/10.1145/3432231Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Daniel A Epstein, Monica Caraway, Chuck Johnston, An Ping, James Fogarty, and Sean A Munson. 2016. Beyond abandonment to next steps: understanding and designing for life after personal informatics tool use. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. 1109--1113.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Daniel A Epstein, An Ping, James Fogarty, and Sean A Munson. 2015. A lived informatics model of personal informatics. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 731--742.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Biyi Fang, Qiumin Xu, Taiwoo Park, and Mi Zhang. 2016. AirSense: an intelligent home-based sensing system for indoor air quality analytics. In Proceedings of the 2016 ACM International joint conference on pervasive and ubiquitous computing. 109--119.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Joel E. Fischer, Andy Crabtree, James A. Colley, Tom Rodden, and Enrico Costanza. [n.d.]. Data Work: How Energy Advisors and Clients Make IoT Data Accountable. CSCW 2017 26, 4--6 ([n.d.]), 597--626. https://doi.org/10.1007/s10606-017-9293-xGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  28. Joel E Fischer, Andy Crabtree, Tom Rodden, James A Colley, Enrico Costanza, Michael O Jewell, and Sarvapali D Ramchurn. 2016. Just whack it on until it gets hot: Working with IoT Data in the Home. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 5933--5944.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Marsha E Fonteyn, Benjamin Kuipers, and Susan J Grobe. 1993. A description of think aloud method and protocol analysis. Qualitative health research 3, 4 (1993), 430--441.Google ScholarGoogle Scholar
  30. Mirta Galesic and Rocio Garcia-Retamero. 2011. Graph literacy: a cross-cultural comparison. Medical Decision Making 31, 3 (2011), 444--457.Google ScholarGoogle ScholarCross RefCross Ref
  31. Sidhant Gupta, M.S. Reynolds, and S.N. Patel. 2010. ElectriSense: single-point sensing using EMI for electrical event detection and classification in the home. Proceedings of the 12th ACM international conference on Ubiquitous computing (2010), 139--148. https://doi.org/10.1145/1864349.1864375Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Dandan Huang, Melanie Tory, Bon Adriel Aseniero, Lyn Bartram, Scott Bateman, Sheelagh Carpendale, Anthony Tang, and Robert Woodbury. 2014. Personal visualization and personal visual analytics. IEEE Transactions on Visualization and Computer Graphics 21, 3 (2014), 420--433.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Samuel Huron, Pauline Gourlet, Uta Hinrichs, Trevor Hogan, and Yvonne Jansen. 2017. Let's Get Physical: Promoting Data Physicalization in Workshop Formats. Proceedings of the ACM Conference on Designing Interactive Systems 3, Umr 9217 (2017), 1409--1422. https://doi.org/10.1145/3064663.3064798Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Noah Iliinsky and Julie Steele. 2011. Designing data visualizations: Representing informational Relationships. " O'Reilly Media, Inc.".Google ScholarGoogle Scholar
  35. Yvonne Jansen, Pierre Dragicevic, Petra Isenberg, Jason Alexander, Abhijit Karnik, Johan Kildal, Sriram Subramanian, and Kasper Hornbæk. 2015. Opportunities and Challenges for Data Physicalization. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15. ACM Press, New York, New York, USA, 3227--3236. https://doi.org/10.1145/2702123.2702180Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Chun E Jia, Hong Ping Zhang, Yan Lv, Rui Liang, Yun Qiu Jiang, Heather Powell, Juan Juan Fu, Lei Wang, Peter Gerard Gibson, and Gang Wang. 2013. The Asthma Control Test and Asthma Control Questionnaire for assessing asthma control: systematic review and meta-analysis. Journal of Allergy and Clinical Immunology 131, 3 (2013), 695--703.Google ScholarGoogle ScholarCross RefCross Ref
  37. Simon L Jones. 2015. Exploring correlational information in aggregated quantified self data dashboards. In Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers. ACM, 1075--1080.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Sean Kandel, Andreas Paepcke, Joseph Hellerstein, and Jeffrey Heer. 2011. Wrangler: Interactive visual specification of data transformation scripts. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 3363--3372.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Matthew Kay, Eun Kyoung Choe, Jesse Shepherd, Benjamin Greenstein, Nathaniel Watson, Sunny Consolvo, and Julie A Kientz. 2012. Lullaby: a capture & access system for understanding the sleep environment. In Proceedings of the 2012 ACM conference on ubiquitous computing. 226--234.Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. John F Kelley. 1984. An iterative design methodology for user-friendly natural language office information applications. ACM Transactions on Information Systems (TOIS) 2, 1 (1984), 26--41.Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Jenny Kennedy, Bjorn Nansen, Michael Arnold, Rowan Wilken, and Martin Gibbs. 2015. Digital housekeepers and domestic expertise in the networked home. Convergence 21, 4 (2015), 408--422.Google ScholarGoogle ScholarCross RefCross Ref
  42. Elisabeth T Kersten-van Dijk, Joyce HDM Westerink, Femke Beute, and Wijnand A IJsselsteijn. 2017. Personal informatics, self-insight, and behavior change: A critical review of current literature. Human-Computer Interaction 32, 5--6 (2017), 268--296.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Ethan Kerzner, Sarah Goodwin, Jason Dykes, Sara Jones, and Miriah Meyer. 2019. A Framework for Creative Visualization-Opportunities Workshops. IEEE Transactions on Visualization and Computer Graphics 25, 1 (jan 2019), 748--758. https://doi.org/10.1109/TVCG.2018.2865241Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Sunyoung Kim and Eric Paulos. 2009. inAir: measuring and visualizing indoor air quality. In Proceedings of the 11th international conference on Ubiquitous computing. 81--84.Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Sunyoung Kim and Eric Paulos. 2010. InAir: sharing indoor air quality measurements and visualizations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1861--1870.Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Sunyoung Kim, Eric Paulos, and Jennifer Mankoff. 2013. inAir: a longitudinal study of indoor air quality measurements and visualizations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2745--2754.Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. David Kirsh. 2001. The Context of Work. Human-Computer Interaction 16, 2--4 (2001), 305--322.Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Thomas Kluyver, Benjamin Ragan-Kelley, Fernando Pérez, Brian E Granger, Matthias Bussonnier, Jonathan Frederic, Kyle Kelley, Jessica B Hamrick, Jason Grout, Sylvain Corlay, et al. 2016. Jupyter Notebooks-a publishing format for reproducible computational workflows.. In ELPUB. 87--90.Google ScholarGoogle Scholar
  49. Bongshin Lee, Rubaiat Habib Kazi, and Greg Smith. 2013. SketchStory: Telling more engaging stories with data through freeform sketching. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2416--2425. https://doi.org/10.1109/TVCG.2013.191Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Sukwon Lee, Bum Chul Kwon, Jiming Yang, Byung Cheol Lee, and Sung-Hee Kim. 2019. The correlation between users' cognitive characteristics and visualization literacy. Applied Sciences 9, 3 (2019), 488.Google ScholarGoogle ScholarCross RefCross Ref
  51. Beth L Leech. 2002. Asking questions: Techniques for semistructured interviews. PS: Political science and politics 35, 4 (2002), 665--668.Google ScholarGoogle Scholar
  52. Timo Lenzner, Cornelia Neuert, and W Otto. 2016. Cognitive pretesting. GESIS Survey Guidelines (2016), 3.Google ScholarGoogle Scholar
  53. Ian Li, Anind Dey, and Jodi Forlizzi. 2010. A stage-based model of personal informatics systems. In Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 557--566.Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Ian Li, Anind K. Dey, and Jodi Forlizzi. 2012. Using context to reveal factors that affect physical activity. ACM Transactions on Computer-Human Interaction 19, 1 (2012), 1--21. https://doi.org/10.1145/2147783.2147790Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Janne Lindqvist, Justin Cranshaw, Jason Wiese, Jason Hong, and John Zimmerman. 2011. I'm the mayor of my house: examining why people use foursquare-a social-driven location sharing application. In Proceedings of the SIGCHI conference on human factors in computing systems. 2409--2418.Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Mariana Marasoiu, Alan F. Blackwell, Advait Sarkar, and Martin Spott. 2016. Clarifying hypotheses by sketching data. Proceedings of EG/VGTC Conference on Visualization (EuroVis 2016) (2016).Google ScholarGoogle Scholar
  57. Grant McCracken. 1988. The long interview. Vol. 13. Sage.Google ScholarGoogle Scholar
  58. Javier Monforte and Joan Úbeda Colomer. 2021. Tinkering with the two-to-one interview: Reflections on the use of two interviewers in qualitative constructionist inquiry. Methods in Psychology (2021). https://doi.org/10.1016/j.metip.2021.100082Google ScholarGoogle ScholarCross RefCross Ref
  59. Jimmy Moore. 2021. The Data Engagement Interview Guide. Accessed: 2021--10-15.Google ScholarGoogle Scholar
  60. Jimmy Moore, Pascal Goffin, Miriah Meyer, Philip Lundrigan, Neal Patwari, Katherine Sward, and Jason Wiese. 2018. Managing In-home Environments through Sensing, Annotating, and Visualizing Air Quality Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)(Ubicomp '18) 2, 3 (Sept 2018), 28 pages. https://doi.org/10.1145/3264938Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Jimmy Moore, Pascal Goffin, Jason Wiese, and Miriah Meyer. 2021. Exploring the personal informatics analysis gap: "There's a lot of bacon". In submission IEEE VIS 2021 x, x (September 2021), 18 pages. https://doi.org/10.1109/TVCG.2021.3114798Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Tamara Munzner. 2014. Visualization analysis and design. CRC press.Google ScholarGoogle Scholar
  63. National Institute of Biomedical Imaging Bioengineering. 2015. Pediatric Research Using Integrated Sensor Monitoring Systems. https://www.nibib.nih.gov/research-funding/prismsGoogle ScholarGoogle Scholar
  64. Cimaron Neugebaur. [n.d.]. Salt Lake City has the worse air quality in the nation, https://kutv.com/news/local/salt-lake-city-has-the-worst-air-quality-in-the-nation, Accessed: 2021--10-15. https://kutv.com/news/local/salt-lake-city-has-the-worst-air-quality-in-the-nation Accessed:2021-10-15.Google ScholarGoogle Scholar
  65. S Tejaswi Peesapati, Victoria Schwanda, Johnathon Schultz, Matt Lepage, So-yae Jeong, and Dan Cosley. 2010. Pensieve: supporting everyday reminiscence. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2027--2036.Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Stanley Presser, Mick P Couper, Judith T Lessler, Elizabeth Martin, Jean Martin, Jennifer M Rothgeb, and Eleanor Singer. 2004. Methods for testing and evaluating survey questions. Public opinion quarterly 68, 1 (2004), 109--130.Google ScholarGoogle ScholarCross RefCross Ref
  67. Tye Rattenbury, Joseph M Hellerstein, Jeffrey Heer, Sean Kandel, and Connor Carreras. 2017. Principles of data wrangling: Practical techniques for data preparation. " O'Reilly Media, Inc.".Google ScholarGoogle Scholar
  68. Jessica Schroeder, Ravi Karkar, Natalia Murinova, James Fogarty, and Sean A Munson. 2019. Examining Opportunities for Goal-Directed Self-Tracking to Support Chronic Condition Management. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 4 (2019), 1--26.Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. Douglas Schuler and Aki Namioka. 1993. Participatory design: Principles and practices. CRC Press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. Michael Sedlmair, Miriah Meyer, and Tamara Munzner. 2012. Design study methodology: Reflections from the trenches and the stacks. IEEE transactions on visualization and computer graphics 18, 12 (2012), 2431--2440.Google ScholarGoogle Scholar
  71. Ben Shneiderman. 2004. Designing for fun: how can we design user interfaces to be more fun? interactions 11, 5 (2004), 48--50.Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Lie Ming Tang and Judy Kay. 2017. Harnessing Long Term Physical Activity Data---How Long-Term Trackers Use Data and How an Adherence-Based Interface Supports New Insights. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 2, Article 26 (June 2017), 28 pages. https://doi.org/10.1145/3090091Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. Alice Thudt, Uta Hinrichs, Samuel Huron, and Sheelagh Carpendale. 2018. Self-Reflection and Personal Physicalization Construction. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 (2018), 1--13. https://doi.org/10.1145/3173574.3173728Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. Peter Tolmie, Andy Crabtree, Tom Rodden, James Colley, and Ewa Luger. 2016. "This has to be the cats": Personal Data Legibility in Networked Sensing Systems. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. ACM, 491--502.Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Susan B Trickett, Wai-Tat Fu, Chrisitan D Schunn, and J Gregory Trafton. 2000. From Dipsy-Doodle to Streaming Motions: Changes in Representation in the Analysis of Visual Scientific Data. In Proceedings of the Annual Meeting of the Cognitive Science Society, Vol. 22.Google ScholarGoogle Scholar
  76. Christopher C Tsai, Gunny Lee, Fred Raab, Gregory J Norman, Timothy Sohn, William G Griswold, and Kevin Patrick. 2007. Usability and feasibility of PmEB: a mobile phone application for monitoring real time caloric balance. Mobile networks and applications 12, 2--3 (2007), 173--184.Google ScholarGoogle Scholar
  77. Janne van Kollenburg, Sander Bogers, Heleen Rutjes, Eva Deckers, Joep Frens, and Caroline Hummels. 2018. Exploring the Value of Parent Tracked Baby Data in Interactions with Healthcare Professionals: A Data-Enabled Design Exploration. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1--12. https://doi.org/10.1145/3173574.3173871Google ScholarGoogle ScholarDigital LibraryDigital Library
  78. Jagoda Walny, Sheelagh Carpendale, Nathalie Henry Riche, Gina Venolia, and Philip Fawcett. 2011. Visual thinking in action: Visualizations as used on whiteboards. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2508--2517. https://doi.org/10.1109/TVCG.2011.251Google ScholarGoogle ScholarDigital LibraryDigital Library
  79. Wesley Willett and Samuel Huron. 2016. A Constructive Classroom Exercise for Teaching InfoVis. In Pedagogy of Data Visualization Workshop at IEEE VIS 2016 (Pedagogy of Data Visualization Workshop at IEEE VIS 2016). Baltimore, United States. https://hal.inria.fr/hal01511020Google ScholarGoogle Scholar
  80. Timothy D Wilson. 1994. The proper protocol: Validity and completeness of verbal reports. Psychological Science 5, 5 (1994), 249--252.Google ScholarGoogle ScholarCross RefCross Ref

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            cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
            Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 5, Issue 4
            Dec 2021
            1307 pages
            EISSN:2474-9567
            DOI:10.1145/3508492
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            • Published: 30 December 2021
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