Author(s):
- Jimmy Moore
- Pascal Goffin
- Jason Wiese
- Miriah Meyer
Abstract:
Personal informatics research helps people track personal data for the purposes of self-reflection and gaining self-knowledge. This field, however, has predominantly focused on the data collection and insight-generation elements of self-tracking, with less attention paid to flexible data analysis. As a result, this inattention has led to inflexible analytic pipelines that do not reflect or support the diverse ways people want to engage with their data. This paper contributes a review of personal informatics and visualization research literature to expose a gap in our knowledge for designing flexible tools that assist people engaging with and analyzing personal data in personal contexts, what we call the personal informatics analysis gap. We explore this gap through a multistage longitudinal study on how asthmatics engage with personal air quality data, and we report how participants: were motivated by broad and diverse goals; exhibited patterns in the way they explored their data; engaged with their data in playful ways; discovered new insights through serendipitous exploration; and were reluctant to use analysis tools on their own. These results present new opportunities for visual analysis research and suggest the need for fundamental shifts in how and what we design when supporting personal data analysis.
Documentation:
https://doi.org/10.1109/TVCG.2021.3114798
References:
[1] Ian Li, Anind Dey, and Jodi Forlizzi. A stage-based
model of personal informatics systems. In Proceed-
ings of the SIGCHI conference on human factors in
computing systems, pages 557–566, 2010.
[2] Sunny Consolvo, Katherine Everitt, Ian Smith, and
James A Landay. Design requirements for technolo-
gies that encourage physical activity. In Proceed-
ings of the SIGCHI conference on Human Factors
in computing systems, pages 457–466, 2006.
[3] Sunny Consolvo, David W McDonald, Tammy
Toscos, Mike Y Chen, Jon Froehlich, Beverly Har-
rison, Predrag Klasnja, Anthony LaMarca, Louis
LeGrand, Ryan Libby, et al. Activity sensing in
the wild: a field trial of ubifit garden. In Proceed-
ings of the SIGCHI conference on human factors in
computing systems, pages 1797–1806, 2008.
[4] Daniel Epstein, Felicia Cordeiro, Elizabeth Bales,
James Fogarty, and Sean Munson. Taming data com-
plexity in lifelogs: exploring visual cuts of personal
informatics data. In DIS ’14, pages 667–676. ACM.
[5] Matthew Mauriello, Michael Gubbels, and Jon E
Froehlich. Social fabric fitness: the design and
evaluation of wearable e-textile displays to support
group running. In Proceedings of the SIGCHI Con-
ference on Human Factors in Computing Systems,
pages 2833–2842, 2014.
[6] Jimmy Moore, Pascal Goffin, Miriah Meyer, Philip
Lundrigan, Neal Patwari, Katherine Sward, and
Jason Wiese. Managing in-home environments
through sensing, annotating, and visualizing air
quality data. Proceedings of the ACM on Interac-
tive, Mobile, Wearable and Ubiquitous Technologies
(IMWUT)(Ubicomp ’18), 2(3), Sept 2018.
[7] Sunyoung Kim and Eric Paulos. inair: measuring
and visualizing indoor air quality. In UBICOMP
’09, pages 81–84.
[8] Sunyoung Kim and Eric Paulos. Inair: sharing in-
door air quality measurements and visualizations. In
Proceedings of the SIGCHI Conference on Human
Factors in Computing Systems, pages 1861–1870,
2010.
[9] Sunyoung Kim, Eric Paulos, and Jennifer Mankoff.
inair: a longitudinal study of indoor air quality mea-
surements and visualizations. In Proceedings of the
SIGCHI Conference on Human Factors in Comput-
ing Systems, pages 2745–2754, 2013.
[10] Biyi Fang, Qiumin Xu, Taiwoo Park, and Mi Zhang.
Airsense: an intelligent home-based sensing system
for indoor air quality analytics. In UBICOMP ’16,
pages 109–119.
[11] Sidhant Gupta, M.S. Reynolds, and S.N. Patel. Elec-
triSense: single-point sensing using EMI for elec-
trical event detection and classification in the home.
Proceedings of the 12th ACM international con-
ference on Ubiquitous computing, pages 139–148,
2010.
[12] Tim Campbell, Eric Larson, Gabe Cohn, Jon
Froehlich, Ramses Alcaide, and Shwetak N. Patel.
Wattr: A method for self-powered wireless sensing
of water activity in the home. In UBICOMP ’10,
pages 169–172, New York, NY, USA, 2010. ACM.
[13] Christopher C Tsai, Gunny Lee, Fred Raab, Gre-
gory J Norman, Timothy Sohn, William G Griswold,
and Kevin Patrick. Usability and feasibility of pmeb:
a mobile phone application for monitoring real time
caloric balance. Mobile networks and applications,
12(2-3):173–184, 2007.
[14] Chia-Fang Chung, Qiaosi Wang, Jessica Schroeder,
Allison Cole, Jasmine Zia, James Fogarty, and
Sean A Munson. Identifying and planning for indi-
vidualized 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):7, 2019.
[15] Chia-Fang Chung, Elena Agapie, Jessica Schroeder,
Sonali Mishra, James Fogarty, and Sean A Munson.
When personal tracking becomes social: Examining
the use of instagram for healthy eating. In Proceed-
ings of the 2017 CHI Conference on human factors
in computing systems, pages 1674–1687, 2017.
[16] S Tejaswi Peesapati, Victoria Schwanda, Johnathon
Schultz, Matt Lepage, So-yae Jeong, and Dan
Cosley. Pensieve: supporting everyday reminis-
cence. In Proceedings of the SIGCHI Conference
on Human Factors in Computing Systems, pages
2027–2036, 2010.
[17] Janne Lindqvist, Justin Cranshaw, Jason Wiese, Ja-
son Hong, and John Zimmerman. I’m the mayor of
my house: examining why people use foursquare-a
social-driven location sharing application. In Pro-
ceedings of the SIGCHI conference on human fac-
tors in computing systems, pages 2409–2418, 2011.
[18] Daniel A Epstein, An Ping, James Fogarty, and
Sean A Munson. A lived informatics model of
personal informatics. In UBICOMP ’15, pages 731–
742. ACM.
[19] 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. Mapping and taking stock of the personal
informatics literature. IMWUT ’20, 4(4), 2020.
[20] Dandan Huang, Melanie Tory, Bon Adriel Aseniero,
Lyn Bartram, Scott Bateman, Sheelagh Carpendale,
Anthony Tang, and Robert Woodbury. Personal Vi-
sualization and Personal Visual Analytics. IEEE
Transactions on Visualization and Computer Graph-
ics, 21(3):420–433, mar 2015.
[21] Yuet Ling Wong, Krishna Madhavan, and Niklas
Elmqvist. Towards characterizing domain experts
as a user group. IEEE BELIV’18, pages 1–10.
[22] Michael Sedlmair, Miriah Meyer, and Tamara Mun-
zner. Design study methodology: Reflections from
the trenches and the stacks. IEEE TVCG ’12,
18(12):2431–2440.
[23] Jimmy Moore, Pascal Goffin, Jason Wiese, and
Miriah Meyer. An interview method for engage-
ment with personal sensor data. arXiv:2107.11441
[cs.HC], Jul. 2021.
[24] Peter Tolmie, Andy Crabtree, Tom Rodden, James
Colley, and Ewa Luger. “this has to be the cats”: Per-
sonal data legibility in networked sensing systems.
In CSCW ’16, pages 491–502. ACM.
[25] Joel E Fischer, Andy Crabtree, Tom Rodden,
James A Colley, Enrico Costanza, Michael O Jewell,
and Sarvapali D Ramchurn. 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, pages 5933–5944.
ACM, 2016.
[26] Katie A Siek, Kay H Connelly, Yvonne Rogers,
Paul Rohwer, Desiree Lambert, and Janet L Welch.
When do we eat? an evaluation of food items in-
put into an electronic food monitoring application.
IEEE PervasiveHealth ’06, pages 1–10.
[27] James J Lin, Lena Mamykina, Silvia Lindtner, Gre-
gory Delajoux, and Henry B Strub. Fish’n’steps:
Encouraging physical activity with an interactive
computer game. In UBICOMP ’06, pages 261–278.
Springer.
[28] Frank Bentley, Konrad Tollmar, Peter Stephenson,
Laura Levy, Brian Jones, Scott Robertson, Ed Price, Richard Catrambone, and Jeff Wilson. Health
mashups: Presenting statistical patterns between
wellbeing data and context in natural language to
promote behavior change. ACM Transactions on
Computer-Human Interaction (TOCHI), 20(5):1–27,
2013.
[29] Hamed Haddadi and Ian Brown. Quantified self and
the privacy challenge. Technology Law Futures, 6,
2014.
[30] Jason Wiese, Sauvik Das, Jason I Hong, and John
Zimmerman. Evolving the ecosystem of personal
behavioral data. Human–Computer Interaction,
32(5-6):447–510, 2017.
[31] Eun Kyoung Choe, Nicole B Lee, Bongshin Lee,
Wanda Pratt, and Julie A Kientz. Understanding
quantified-selfers’ practices in collecting and explor-
ing personal data. In Proceedings of the SIGCHI
conference on human factors in computing systems,
pages 1143–1152, 2014.
[32] Simon L Jones. Exploring correlational informa-
tion in aggregated quantified self data dashboards.
UBICOMP/ISWC ’15 Adjunct, pages 1075–1080.
[33] Simon L Jones and Ryan Kelly. Dealing with infor-
mation overload in multifaceted personal informat-
ics systems. Human–Computer Interaction, 33(1):1–
48, 2018.
[34] Tamara Munzner, Chris Johnson, Robert Moorhead,
Hanspeter Pfister, Penny Rheingans, and Terry S
Yoo. Nih-nsf visualization research challenges re-
port summary. IEEE Computer Graphics and Ap-
plications, 26(2):20–24, 2006.
[35] T. Munzner. A nested model for visualization design
and validation. IEEE Transactions on Visualization
and Computer Graphics, 15(6):921–928, 2009.
[36] Sean McKenna, Dominika Mazur, James Agutter,
and Miriah Meyer. Design activity framework for
visualization design. IEEE TVCG ’14, 20(12):2191–
2200.
[37] Nina McCurdy, Jason Dykes, and Miriah Meyer.
Action design research and visualization design. In
Proceedings of the Sixth Workshop on Beyond Time
and Errors on Novel Evaluation Methods for Visu-
alization, pages 10–18, 2016.
[38] Miriah Meyer and Jason Dykes. Criteria for rigor
in visualization design study. IEEE TVCG ’19,
26(1):87–97.
[39] Michael Sedlmair. Design study contributions come
in different guises: Seven guiding scenarios. In
BELIV ’16, page 152–161, New York, NY, USA.
[40] Sean Kandel, Andreas Paepcke, Joseph M Heller-
stein, and Jeffrey Heer. Enterprise data analysis and
visualization: An interview study. IEEE TVCG ’12,
18(12):2917–2926.
[41] Sara Alspaugh, Nava Zokaei, Andrea Liu, Cindy
Jin, and Marti A. Hearst. Futzing and Moseying:
Interviews with Professional Data Analysts on Ex-
ploration Practices. IEEE TVCG ’19, 25(1):22–31.
[42] Eser Kandogan, Aruna Balakrishnan, Eben M
Haber, and Jeffrey S Pierce. From data to insight:
work practices of analysts in the enterprise. IEEE
computer graphics and applications, 34(5):42–50,
2014.
[43] Miryung Kim, Thomas Zimmermann, Robert De-
Line, and Andrew Begel. The emerging role of data
scientists on software development teams. In ICSE
’16, pages 96–107. ACM.
[44] Danyel Fisher, Rob DeLine, Mary Czerwinski, and
Steven Drucker. Interactions with big data analytics.
interactions, 19(3):50–59, 2012.
[45] Peter Pirolli and Stuart Card. The sensemaking pro-
cess and leverage points for analyst technology as
identified through cognitive task analysis. In Pro-
ceedings of international conference on intelligence
analysis, volume 5, pages 2–4. McLean, VA, USA,
2005.
[46] Paula Cowley, Lucy Nowell, and Jean Scholtz.
Glass box: An instrumented infrastructure for sup-
porting human interaction with information. In
IEEE ICSS ’15, pages 296c–296c.
[47] Emily S Patterson, Emilie M Roth, and David D
Woods. Predicting vulnerabilities in computer-
supported inferential analysis under data over-
load. Cognition, Technology & Work, 3(4):224–237,
2001.
[48] William Wright, David Schroh, Pascale Proulx,
Alex Skaburskis, and Brian Cort. The sandbox for
analysis: concepts and methods. In Proceedings
of the SIGCHI conference on Human Factors in
computing systems, pages 801–810, 2006.
[49] Peter Pirolli and Stuart Card. Information foraging.
Psychological review, 106(4):643, 1999.
[50] Daniel M Russell, Mark J Stefik, Peter Pirolli, and
Stuart K Card. The cost structure of sensemaking.
In Proceedings of the INTERACT’93 and CHI’93
conference on Human factors in computing systems,
pages 269–276, 1993.
[51] Sean Kandel, Andreas Paepcke, Joseph Hellerstein,
and Jeffrey Heer. Wrangler: Interactive visual spec-
ification of data transformation scripts. In Proceed-
ings of the SIGCHI Conference on Human Factors
in Computing Systems, pages 3363–3372, 2011.
[52] Alex Bigelow, Carolina Nobre, Miriah Meyer, and
Alexander Lex. Origraph: interactive network wran-
gling. In IEEE VAST ’19, pages 81–92.
[53] Michael Bostock, Vadim Ogievetsky, and Jeffrey
Heer. D3data-driven documents. IEEE TVCG ’11,
17(12):2301–2309.
[54] Jock Mackinlay. Automating the design of graphical
presentations of relational information. TOG ’86,
5(2):110–141.
[55] Kanit Wongsuphasawat, Dominik Moritz, Anushka
Anand, Jock Mackinlay, Bill Howe, and Jeffrey
Heer. Voyager: Exploratory analysis via faceted
browsing of visualization recommendations. IEEE
TVCG ’15, 22(1):649–658.
[56] Kanit Wongsuphasawat, Dominik Moritz, Anushka
Anand, Jock Mackinlay, Bill Howe, and Jeffrey
Heer. Towards a general-purpose query language for
visualization recommendation. HILDA ’16, pages
1–6.
[57] Jock Mackinlay, Pat Hanrahan, and Chris Stolte.
Show me: Automatic presentation for visual analy-
sis. IEEE TVCG ’07, 13(6):1137–1144.
[58] Robert A Amar and John T Stasko. Knowledge
precepts for design and evaluation of information
visualizations. IEEE TVCG ’05, 11(4):432–442.
[59] Bum chul Kwon, Brian Fisher, and Ji Soo Yi. Vi-
sual analytic roadblocks for novice investigators. In
IEEE VAST ’11, pages 3–11.
[60] Po-Ming Law, Rahul C Basole, and Yanhong Wu.
Duet: Helping data analysis novices conduct pair-
wise comparisons by minimal specification. IEEE
TVCG ’18, 25(1):427–437.
[61] Lars Grammel, Melanie Tory, and Margaret-Anne
Storey. How information visualization novices con-
struct visualizations. IEEE transactions on visu-
alization and computer graphics, 16(6):943–952,
2010.
[62] Martin Wattenberg. Visualizing the stock market.
In CHI’99 extended abstracts on Human factors in
computing systems, pages 188–189, 1999.
[63] Martin Wattenberg. Baby names, visualization, and
social data analysis. In IEEE INFOVIS ’05., pages
1–7.
[64] Fernanda B Viegas, Martin Wattenberg, Frank
Van Ham, Jesse Kriss, and Matt McKeon.
Manyeyes: a site for visualization at internet scale.
IEEE TVCG ’07, 13(6):1121–1128.
[65] Jeffrey Heer, Fernanda B Viégas, and Martin Wat-
tenberg. Voyagers and voyeurs: Supporting asyn-
chronous collaborative visualization. Communica-
tions of the ACM, 52(1):87–97, 2009.
[66] Catalina M Danis, Fernanda B Viegas, Martin Wat-
tenberg, and Jesse Kriss. Your place or mine? visu-
alization as a community component. In Proceed-
ings of the SIGCHI conference on Human factors in
computing systems, pages 275–284, 2008.
[67] Jeffrey Heer and Danah Boyd. Vizster: Visualizing
online social networks. In INFOVIS ’05, pages 32–
39. IEEE.
[68] Samuel Huron, Sheelagh Carpendale, Alice Thudt,
Anthony Tang, and Michael Mauerer. Constructive
visualization. In DIS ’14, pages 433–442. ACM.
[69] Michael J Danziger. Information visualization for
the people. PhD thesis, Massachusetts Institute
of Technology, Department of Comparative Media
Studies, 2008.
[70] Rohit Ashok Khot, Jeewon Lee, Deepti Aggarwal,
Larissa Hjorth, and Florian ’Floyd’ Mueller. Tasty-
Beats: Designing palatable representations of phys-
ical activity. In Proceedings of the 33rd Annual
ACM Conference on Human Factors in Computing
Systems, pages 2933–2942, New York, NY, USA,
apr 2015. ACM.
[71] Rohit Ashok Khot, Florian Mueller, and Larissa
Hjorth. SweatAtoms: Materializing physical ac-
tivity. ACM International Conference Proceeding
Series, 2013.
[72] Simon Stusak, Aurelien Tabard, Franziska Sauka,
Rohit Ashok Khot, and Andreas Butz. Activity
sculptures: Exploring the impact of physical visual-
izations on running activity. IEEE Transactions on
Visualization and Computer Graphics, 20(12):2201–
2210, 2014.
[73] Alice Thudt, Uta Hinrichs, Samuel Huron, and Shee-
lagh Carpendale. Self-reflection and personal physi-
calization construction. In Proceedings of the 2018
CHI Conference on Human Factors in Computing
Systems, pages 1–13, 2018.
[74] Alice Thudt, Dominikus Baur, Samuel Huron, and
Sheelagh Carpendale. Visual Mementos: Reflecting
Memories with Personal Data. IEEE TVCG ’16,
22(1):369–378.
[75] Steven Houben, Connie Golsteijn, Sarah Gallacher,
Rose Johnson, Saskia Bakker, Nicolai Marquardt,
Licia Capra, and Yvonne Rogers. Physikit: Data
Engagement Through Physical Ambient Visualiza-
tions in the Home. In Proceedings of the 2016 CHI
Conference on Human Factors in Computing Sys-
tems, pages 1608–1619, New York, NY, USA, may
2016. ACM.
[76] David Holstius, John Kembel, Amy Hurst, Peng-
Hui Wan, and Jodi Forlizzi. Infotropism: living and
robotic plants as interactive displays. In Proceed-
ings of the 5th conference on Designing interactive
systems: processes, practices, methods, and tech-
niques, pages 215–221, 2004.
[77] Fadi Botros, Charles Perin, Bon Adriel Aseniero,
and Sheelagh Carpendale. Go and Grow. In Pro-
ceedings of the International Working Conference
on Advanced Visual Interfaces, pages 112–119, New
York, NY, USA, jun 2016. ACM.
[78] Bongshin Lee, Eun Kyoung Choe, Petra Isenberg,
Kim Marriott, John Stasko, and Theresa-Marie
Rhyne. Reaching Broader Audiences With Data
Visualization. IEEE Comp. Gr. & App., 40(2):82–
90, ’20.
[79] Philipp Koytek, Charles Perin, Jo Vermeulen, Elis-
abeth André, and Sheelagh Carpendale. MyBrush: Brushing and Linking with Personal Agency. IEEE
TVCG ’18, 24(1):605–615.
[80] Bon Adriel Aseniero, Charles Perin, Wesley Willett,
Anthony Tang, and Sheelagh Carpendale. Activity
River: Visualizing Planned and Logged Personal
Activities for Reflection. ACM International Con-
ference Proceeding Series, 2020.
[81] Ethan Kerzner, Sarah Goodwin, Jason Dykes, Sara
Jones, and Miriah Meyer. A framework for creative
visualization-opportunities workshops. IEEE TVCG
’18, 25(1):748–758.
[82] National Institute of Biomedical Imaging Bioengi-
neering. Pediatric Research Using Integrated Sensor
Monitoring Systems, 2015.
[83] Lena Mamykina, Elizabeth Mynatt, Patricia David-
son, and Daniel Greenblatt. Mahi: investigation of
social scaffolding for reflective thinking in diabetes
management. In Proceedings of the SIGCHI Con-
ference on Human Factors in Computing Systems,
pages 477–486, 2008.
[84] Samantha Kolovson, Calvin Liang, Sean A Mun-
son, and Kate Starbird. Personal data and power
asymmetries in us collegiate sports teams. Proceed-
ings of the ACM on Human-Computer Interaction,
4(GROUP):1–27, 2020.
[85] Utah Physicians for a Healthy Environment.
Slc – ranked among the worst globally for air
quality, https://www.uphe.org/2020/09/14/slc-
ranked-among-the-worst-globally-for-air-quality/.
Accessed:2021-03-19.
[86] David Kirsh. The context of work. Hu-
man–Computer Interaction, 16(2-4):305–322,
2001.
[87] William Lidwell, Kritina Holden, and Jill Butler.
Universal principles of design. Rockport Pub, 2010.
[88] Y. Rogers. New theoretical approaches for human-
computer interaction. Annual review of information
science and technology, 38(1):87–143, ’04.
[89] James J Gibson. The ecological approach to visual
perception. hills-dale. NJ: Lawrence, 1986.
[90] Donald A Norman. Affordance, conventions, and
design. interactions, 6(3):38–43, 1999.
[91] Peter Thorvald. Triggers, entry points, and affor-
dances: How to improve their cognitive congenial-
ity, 2006.
[92] Tanja Blascheck, Lindsay Macdonald Vermeulen,
Jo Vermeulen, Charles Perin, Wesley Willett,
Thomas Ertl, and Sheelagh Carpendale. Exploration
strategies for discovery of interactivity in visualiza-
tions. IEEE TVCG ’19, 25(2):1407–1420.
[93] Jagoda Walny, Sarah Storteboom, Richard Pusch,
Steven Munsu Hwang, Søren Knudsen, Sheelagh
Carpendale, and Wesley Willett. Pixelclipper: Sup-
porting public engagement and conversation about
visualizations. IEEE Comp.Gr.& App.’20, 40(2):57–
70.
[94] Eva Hornecker, Paul Marshall, and Yvonne Rogers.
From entry to access: How shareability comes about.
In DPPI ’07, page 328–342. ACM.
[95] Eun Kyoung Choe, Bongshin Lee, Haining Zhu,
Nathalie Henry Riche, and Dominikus Baur. Un-
derstanding self-reflection: how people reflect on
personal data through visual data exploration. Per-
vasiveHealth ’17, pages 173–182.
[96] Fabio Miranda, Marcos Lage, Harish Doraiswamy,
Charlie Mydlarz, Justin Salamon, Yitzchak Lock-
erman, Juliana Freire, and Claudio T Silva. Time
lattice: A data structure for the interactive visual
analysis of large time series. Comp. Gr. Forum,
37(3):23–35, 2018.
[97] Evan M Peck, Sofia E Ayuso, and Omar El-Etr.
Data is personal: Attitudes and perceptions of data
visualization in rural pennsylvania. In Proceedings
of the 2019 CHI Conference on Human Factors in
Computing Systems, pages 1–12, 2019.
[98] Matthew Brehmer and Tamara Munzner. A multi-
level typology of abstract visualization tasks. IEEE
transactions on visualization and computer graph-
ics, 19(12):2376–2385, 2013.
[99] Mackinlay Card. Readings in information visual-
ization: using vision to think. Morgan Kaufmann,
1999.
[100] Ben Shneiderman. Designing for fun: How can we
design user interfaces to be more fun? Interactions,
11(5):48–50, September 2004.
[101] Naa Amponsah Dodoo and Seounmi Youn. Snap-
ping and chatting away: Consumer motivations for
and outcomes of interacting with snapchat ar ad lens.
Telematics and Informatics, 57:101514, 2021.
[102] Joseph Tu and Ekaterina Durmanova. Curioscape:
A curiosity-driven escape room board game. CHI
PLAY ’20: Extended Abstracts, pages 94–97.
[103] Harry Slater. [update] the cu-
riosity cube diaries – volume 1,
https://www.pocketgamer.com/articles/046406/update-
the-curiosity-cube-diaries-volume-i/, accessed:
2021-03-21. Accessed:2021-03-21.
[104] Sebastian Deterding. Situated motivational affor-
dances of game elements: A conceptual model. CHI
’11 Gamification Workshop, (July), 2011.
[105] Ferran Altarriba Bertran, Elena Márquez Segura,
Jared Duval, and Katherine Isbister. Chasing play
potentials: Towards an increasingly situated and
emergent approach to everyday play design. pages
1265–1277, ’19.
[106] William W Gaver, John Bowers, Andrew Boucher,
Hans Gellerson, Sarah Pennington, Albrecht
Schmidt, Anthony Steed, Nicholas Villars, and Brendan Walker. The drift table: designing for
ludic engagement. CHI EA’04, pages 885–900.
[107] Aaron Scott. How playcentric research methods are
contributing to new understanding and opportunities
for design. The Routledge companion to design
research, pages 400–414, 2014.
[108] Steven P Dow, Kate Heddleston, and Scott R Klem-
mer. The efficacy of prototyping under time con-
straints. In ACM conf. on Creativity and cognition
’09, pages 165–174.
[109] Mattia Thibault. Play as a modelling system-a semi-
otic analysis of the overreaching prestige of games.
In GamiFIN, pages 105–110, 2017.
[110] Sebastian Deterding, Dan Dixon, Rilla Khaled, and
Lennart Nacke. From game design elements to
gamefulness: Defining “gamification”. In Proceed-
ings of the 15th International Academic MindTrek
Conference: Envisioning Future Media Environ-
ments, MindTrek ’11, page 9–15, New York, NY,
USA, 2011. Association for Computing Machinery.
[111] Guy H Orcutt, Harold W Watts, and John B Ed-
wards. Data aggregation and information loss. The
American Economic Review ’68, 58(4):773–787.
[112] Jeffrey Heer and Maneesh Agrawala. Design consid-
erations for collaborative visual analytics. INFOVIS
’08, 7(1):49–62.