The Design and Evaluation of Prototype Eco-Feedback     Displays for Fixture-Level Water Usage Data        Jon Froehlich1,...
This talk is about eco-feedback displays      for water usage in the home
This talk is also about the design process for eco-feedback visualizations                                               p...
But first, a quick primer on water
two-thirdsof the earth’s surface is covered by water
Brackish                                     Polar Ice         1%                              Drinkable                  ...
The amount of water on earth is not changingbut its location, quality andamount per person is changing
The amount of water on earth is not changingbut its location, quality andamount per person is changing
As the                               ‘s climate changes…    precipitation patterns             glacial and ice snowpack   ...
As populations                 growper-capita water availability is
water availability disproportionately felt in        urban environments[Barlow, 2007]
This places an enormous strain on                                drinkable water supplies[Inman and Jeffery, 2006; Gleick ...
growing      demand        in 2010, water consumption rose        to 938 billion gallons in beijing        water supply = ...
“china melting snow to meet                               freshwater demand”[Guardian, Dec 2010]
lake mead expected to                             drop below intake                             pipes in next five years[B...
water utilitiesgovernmentsshift focus
This is an area where HCI researchers and designers can help
eco-feedbacksensing and visualizing behavior to reduce environmental impact
Dubuque Water Portal:[Erickson et al., CHI 2012]
10,230gallons
Other          1248 gals          Dishwasher          102 gals10,230          Faucets          1105 gals          Showers ...
waterbot           [Arroyo et al., CHI 2005]
showme         [Kappel & Grechenig, Persuasive 2009]
upstream           [Kuznetsov & Paulos, CHI 2010]
waitek shower monitorhttp://www.waitek.co.nz/
Point-of-Consumption Eco-Feedback Displays sensing and feedback           provides real-timeunit co-located at fixture   f...
Point-of-consumption feedback is theprevailing method for providing water usage feedback at the fixture-level
direct sensing[Teague Labs, Arduino Water Meter, http://labs.teague.com/?p=722]
direct sensing   shower  62.4 gallons                  bathroom sink 1   bathroom sink 2                                  ...
direct sensing shower52.4 gallons         shower       62.4 gallons                             bathroom sink 1   bathroom...
Showers and faucets account                  for ~22% of water use in the                  average North American home[Vic...
direct sensing shower52.4 gallons         shower       62.4 gallons                             bathroom sink 1   bathroom...
indirect sensing shower52.4 gallons         shower       62.4 gallons                             bathroom sink 1   bathro...
A single sensor infers fixture-levelusage for the entire home                  [HydroSense, UbiComp 2009]
Emerging Water Sensing Disaggregation Methods
eco-feedbacksensing and visualizing behavior to reduce environmental impact
What do we do with all this data?
Key Questions1 What are the key gaps in water usage understanding?2 What aspects of disaggregated data are potential users...
Key Questions1 What are the key gaps in water usage understanding?2 What aspects of disaggregated data are potential users...
Two sets of designs:1   Design Dimensions    Isolate eco-feedback design dimensions in the context of water usage2   Desig...
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Respondents (N=651) dramatically underestimated the    amount of water used in common everyday activities.                ...
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Iterative Design ProcessSketch          Lo-to-Mid Fidelity   Higher Fidelity                     Mockup             Mockup
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Designing the Eco-Feedback Interfaces
How does one go about the process ofdesigning interfaces for eco-feedback?
Eco-Feedback Design SpaceINFORMATION ACCESS                                                             DATA REPRESENTATIO...
My own experiences    Existing frameworks                     Psychology                     (in persuasive tech and infov...
Eco-Feedback Design SpaceINFORMATION ACCESS                                                             DATA REPRESENTATIO...
data           information               representation         access    inputs                                        di...
data           information               representation         access    inputs                                        di...
data           information               representation         access    inputs                                        di...
data           information               representation         access    inputs                                        di...
data           information               representation         access    inputs                                        di...
Two sets of designs:1   Design Dimensions    Isolate eco-feedback design dimensions in the context of water usage2   Desig...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONSDesign Dimensions Explored1 Data Granularity                      Part of “Data  ...
data           information               representation         access    inputs                                        di...
data           information               representation         access    inputs                                        di...
data       representationtions                        aesthetic                                    pragmatic              ...
data       representationtions                        aesthetic                                    pragmatic              ...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS                         Data Granularitycoarse-grain                            ...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS         Time Granularity≤ hour    day     week      month     ≥ year
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS                 Measurement Unitresource        rate of     cost        time    ...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS            data       representationtions                        aesthetic      ...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS            data       representationtions
DESIGN SET 1: ISOLATING DESIGN DIMENSIONS      comparisonity                     comparison                         target...
comparisonity                     comparison                         target self                social                  go...
DESIGN SET 1: ISOLATING DESIGN DIMENSIONSDesign Dimensions Explored        Data   Granularity                 Individual F...
Two sets of designs:1   Design Dimensions    Isolate eco-feedback design dimensions in the context of water usage2   Desig...
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
Daily Patterns of Water Usage                                                        Washing Machine                      ...
DESIGN SET 2: DESIGN PROBESTime-Series Views
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBESSpatial View
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBESPer-Occupant View
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBES   Aquatic Ecosystem Design Influences                 ubifit                 Consolvo et al., ...
DESIGN SET 2: DESIGN PROBESAquatic Ecosystem View Movie           Water savings              New water                “Fra...
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBESRainflow View
DESIGN SET 2: DESIGN PROBESRainflow View Movie
DESIGN SET 2: DESIGN PROBESDesign Probes Explored                      Time-      Aquatic                      Series     ...
DESIGN SET 2: DESIGN PROBESOther Design Probes          Geographic Comparisons        Dashboards          Metaphorical Uni...
Evaluation
Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of wat...
Online Survey                Recruitment                o Online postings and word-of-mouth                Survey Design  ...
In-Home Interviews          Recruitment          o Online postings and word-of-mouth          o Specifically recruited fam...
For both the survey and interviews, 90% ofparticipants indicated an interest in conserving water   Average morning shower ...
Findings
Data Granularitycoarse-grain                                                                fine-grain               ≥neig...
Data Granularitycoarse-grain                                                                fine-grain               ≥neig...
Data Granularitycoarse-grain                                                                fine-grain               ≥neig...
Measurement Unit resource      rate of        cost         time       activity    metaphor            consumption71% of re...
Time Granularity     ≤ hour    day   week   month   ≥ yearMajority of respondents wanted ability toswitch between differen...
Comparisons were the most   uniformly desired pieces ofinformation of all the dimensions
Self-comparisonwas most preferred91%
Emergent Themes1 Competition and Cooperation2 Accountability and Blame3 Playfulness and Functionality4 Sense of Privacy5 D...
Competition and Cooperation       “                                                           ”       You can compare usag...
Accountability and Blame       “                                              ”       It holds each individual accountable...
Playfulness and Functionality       “                                                                  ”       I like the ...
Useful as an educational tool?
Privacy Spectrum   Least                      MostInvasive                      Invasive
It’s incredibly invasive.And other people’swater consumption isnot my business.     R25
Water usage formany purposes canbe very personal, andshouldn’t beautomatically shared    R25
Privacy Spectrum   Least                      MostInvasive                      Invasive
Display Location Preferences
If we placed thedisplay here, the kidscouldn’t see it.   I2.1
Display Location Preferences     kitchen      near thermostat  high traffic        areas   accessiblewhen needed
Primary Contributions1 First work to design and evaluate  feedback visualizations for disaggregated  water data2 An iterat...
Sensing and feedbackfor water quality notjust consumption
Data      Ideation /    Pilot                 FormativeIdeation                                      Refinement           ...
Closing Thought   Eco-feedback displays do not just visualizeconsumption, they document household activities
The Eco-Feedback Team!      Solai               Josh              Inness              Fabia          Mazhengmin     Marily...
Questions?                          @jonfroehlichdesign:   UNIVERSITY ofuse:build:    WASHINGTON
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data
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The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data

  1. 1. The Design and Evaluation of Prototype Eco-Feedback Displays for Fixture-Level Water Usage Data Jon Froehlich1,2, Leah Findlater1,2, Marilyn Ostergren1, Solai Ramanathan1, Josh Peterson1, Inness Wragg1, Eric Larson1, Fabia Fu1, Mazhengmin Bai1, Shwetak N. Patel1, James A. Landay1 design: UNIVERSITY of use: build: WASHINGTON
  2. 2. This talk is about eco-feedback displays for water usage in the home
  3. 3. This talk is also about the design process for eco-feedback visualizations persuasive technology personal informatics quantified self
  4. 4. But first, a quick primer on water
  5. 5. two-thirdsof the earth’s surface is covered by water
  6. 6. Brackish Polar Ice 1% Drinkable 1.7% Water 0.8% Ocean 96.5%[Glennon, Unquenchable: America’s water crisis and what to do about it, 2009; Gleick,World Policy Journal, 2009]
  7. 7. The amount of water on earth is not changingbut its location, quality andamount per person is changing
  8. 8. The amount of water on earth is not changingbut its location, quality andamount per person is changing
  9. 9. As the ‘s climate changes… precipitation patterns glacial and ice snowpack surface water availability[Gleick, World Policy Journal, 2009]
  10. 10. As populations growper-capita water availability is
  11. 11. water availability disproportionately felt in urban environments[Barlow, 2007]
  12. 12. This places an enormous strain on drinkable water supplies[Inman and Jeffery, 2006; Gleick et al., 2008 Vairavmoorthy, 2006]
  13. 13. growing demand in 2010, water consumption rose to 938 billion gallons in beijing water supply = 576 billion gallons[Guardian, Dec 2010]
  14. 14. “china melting snow to meet freshwater demand”[Guardian, Dec 2010]
  15. 15. lake mead expected to drop below intake pipes in next five years[Bloomberg News, Feb 2009]
  16. 16. water utilitiesgovernmentsshift focus
  17. 17. This is an area where HCI researchers and designers can help
  18. 18. eco-feedbacksensing and visualizing behavior to reduce environmental impact
  19. 19. Dubuque Water Portal:[Erickson et al., CHI 2012]
  20. 20. 10,230gallons
  21. 21. Other 1248 gals Dishwasher 102 gals10,230 Faucets 1105 gals Showers 1176 gals Laundrygallons 1,524 gals Toilets 1,872 gals Outdoor 3,212 gals
  22. 22. waterbot [Arroyo et al., CHI 2005]
  23. 23. showme [Kappel & Grechenig, Persuasive 2009]
  24. 24. upstream [Kuznetsov & Paulos, CHI 2010]
  25. 25. waitek shower monitorhttp://www.waitek.co.nz/
  26. 26. Point-of-Consumption Eco-Feedback Displays sensing and feedback provides real-timeunit co-located at fixture feedback on water usage
  27. 27. Point-of-consumption feedback is theprevailing method for providing water usage feedback at the fixture-level
  28. 28. direct sensing[Teague Labs, Arduino Water Meter, http://labs.teague.com/?p=722]
  29. 29. direct sensing shower 62.4 gallons bathroom sink 1 bathroom sink 2 4.2 gallons 0.8 gallons bath 6.5 gallons toilet 78.4 gallons
  30. 30. direct sensing shower52.4 gallons shower 62.4 gallons bathroom sink 1 bathroom sink 1 bathroom sink 2 3.2 gallons 4.2 gallons 0.8 gallons bath bath bathroom sink 2 6.5 gallons 6.5 gallons 2.4 gallons toilet 78.4 gallons
  31. 31. Showers and faucets account for ~22% of water use in the average North American home[Vickers, 2001]
  32. 32. direct sensing shower52.4 gallons shower 62.4 gallons bathroom sink 1 bathroom sink 1 bathroom sink 2 3.2 gallons 4.2 gallons 0.8 gallons bath bath bathroom sink 2 6.5 gallons 6.5 gallons 2.4 gallons toilet 78.4 gallons
  33. 33. indirect sensing shower52.4 gallons shower 62.4 gallons bathroom sink 1 bathroom sink 1 bathroom sink 2 3.2 gallons 4.2 gallons 0.8 gallons bath bath bathroom sink 2 6.5 gallons 6.5 gallons 2.4 gallons toilet 78.4 gallons [HydroSense, UbiComp 2009]
  34. 34. A single sensor infers fixture-levelusage for the entire home [HydroSense, UbiComp 2009]
  35. 35. Emerging Water Sensing Disaggregation Methods
  36. 36. eco-feedbacksensing and visualizing behavior to reduce environmental impact
  37. 37. What do we do with all this data?
  38. 38. Key Questions1 What are the key gaps in water usage understanding?2 What aspects of disaggregated data are potential users interested in and what sort of reactions do the visualizations provoke?3 How might these visualizations impact behavior?
  39. 39. Key Questions1 What are the key gaps in water usage understanding?2 What aspects of disaggregated data are potential users interested in and what sort of reactions do the visualizations provoke?3 How might these visualizations impact behavior?
  40. 40. Two sets of designs:1 Design Dimensions Isolate eco-feedback design dimensions in the context of water usage2 Design Probes Meant to elicit reactions about how displays would fit within a household and investigate issues such as privacy, competition, family dynamics.
  41. 41. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Data Ideation / Pilot EvaluationIdeation Refinement Gathering Sketch Studies
  42. 42. Respondents (N=651) dramatically underestimated the amount of water used in common everyday activities. underestimate toilet : by 15% shower : by 30% bath : by 55% low-flow shower : by 60% outdoor yard watering : by 83% to 95%[Froehlich, UW PhD Dissertation, 2011]
  43. 43. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation
  44. 44. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation Informed by gathered data Guided by eco-feedback design space
  45. 45. Iterative Design ProcessSketch Lo-to-Mid Fidelity Higher Fidelity Mockup Mockup
  46. 46. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Design critique sessions with team Three sets of pilot studies Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation Informed by gathered data Guided by eco-feedback design space
  47. 47. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Design critique sessions with team Three sets of pilot studies Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation Informed by gathered data Guided by eco-feedback design space Online interactive survey of designs (N=651 respondents) In-home interviews (10 households, 20 adults)
  48. 48. Designing the Eco-Feedback Interfaces
  49. 49. How does one go about the process ofdesigning interfaces for eco-feedback?
  50. 50. Eco-Feedback Design SpaceINFORMATION ACCESS DATA REPRESENTATION COMPARISON update aesthetic comparison frequency real-time monthly or less user poll pragmatic artistic target self social goal spatial proximity time comparison by to behavior co-located remote window <hour >year time past projected attentional temporal social-comp. demand glanceable high attention grouping ≤sec by hour by day by week by month ≥year geographically demographically selected target proximal similar social network effort to data goal-setting access low high granularity coarse-grain fine-grain strategy self-set system-set externally-setINTERACTIVITY visual difficulty to reach complexity simple complex comparison target easy hard degree of interactivity none high primary visual comparison variables statistic computation encoding textual graphical time window interface raw value @ this time [yest, last wk, mo, yr] customizability none high measurement time granularity average [hrly, daily, wkly, monthly, yrly] unit resource cost environmental activity time metaphor data grouping median over past [X] days impact mode user data granularity this day type [weekday, weekend] additions user annotations user corrections primary other this day of week (e.g., mondays) measurement unit view temporal spatial categoricalDISPLAY MEDIUM manifestation data grouping by by by by by by consumption SOCIAL ASPECTS webpage mobile wearable custom in-home resource person time space activity category phone app interface display display target person household community state country ambience MOTIVATIONAL/PERSUASIVE STRATEGIES not-ambient ambient private/ persuasive tactics from persuasive tactics include: public private public size psychology and applied social rewards goal-setting small large psychology disciplines: data punishment narrativeACTIONABILITY/UTILITY persuasive design public commitment likeability sharing none everyone written commitment reputation persuasive technology social- degree of loss aversion competition (see COMPARISON) behavioral science/economics comparison available unavailable actionability low high kairos social proof environmental psychology encouragement authority decision game design suggests suggests anomaly descriptive norms emotional appeals support actions social marketing purchase decisions alerts scarcity principle door-in-face health behavior change personal- framing unlock features ization no personalization highly personalized anchoring bias endowment effect defaults collection building information intent Informs one action informs many actions automation/ control no control system controls resource use [Froehlich et al., HCIC2009; CHI2010; UW PhD Dissertation 2011]
  51. 51. My own experiences Existing frameworks Psychology (in persuasive tech and infovis) (particularly behavioral economics and environ. psych)
  52. 52. Eco-Feedback Design SpaceINFORMATION ACCESS DATA REPRESENTATION COMPARISON update aesthetic comparison frequency real-time monthly or less user poll pragmatic artistic target self social goal spatial proximity time comparison by to behavior co-located remote window <hour >year time past projected attentional temporal social-comp. demand glanceable high attention grouping ≤sec by hour by day by week by month ≥year geographically demographically selected target proximal similar social network effort to data goal-setting access low high granularity coarse-grain fine-grain strategy self-set system-set externally-setINTERACTIVITY visual difficulty to reach complexity simple complex comparison target easy hard degree of interactivity none high primary visual comparison variables statistic computation encoding textual graphical time window interface raw value @ this time [yest, last wk, mo, yr] customizability none high measurement time granularity average [hrly, daily, wkly, monthly, yrly] unit resource cost environmental activity time metaphor data grouping median over past [X] days impact mode user data granularity this day type [weekday, weekend] additions user annotations user corrections primary other this day of week (e.g., mondays) measurement unit view temporal spatial categoricalDISPLAY MEDIUM manifestation data grouping by by by by by by consumption SOCIAL ASPECTS webpage mobile wearable custom in-home resource person time space activity category phone app interface display display target person household community state country ambience MOTIVATIONAL/PERSUASIVE STRATEGIES not-ambient ambient private/ persuasive tactics from persuasive tactics include: public private public size psychology and applied social rewards goal-setting small large psychology disciplines: data punishment narrativeACTIONABILITY/UTILITY persuasive design public commitment likeability sharing none everyone written commitment reputation persuasive technology social- degree of loss aversion competition (see COMPARISON) behavioral science/economics comparison available unavailable actionability low high kairos social proof environmental psychology encouragement authority decision game design suggests suggests anomaly descriptive norms emotional appeals support actions social marketing purchase decisions alerts scarcity principle door-in-face health behavior change personal- framing unlock features ization no personalization highly personalized anchoring bias endowment effect defaults collection building information intent Informs one action informs many actions automation/ control no control system controls resource use [Froehlich et al., HCIC2009; CHI2010; UW PhD Dissertation 2011]
  53. 53. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  54. 54. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  55. 55. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  56. 56. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  57. 57. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  58. 58. Two sets of designs:1 Design Dimensions Isolate eco-feedback design dimensions in the context of water usage2 Design Probes Meant to elicit reactions about how displays would fit within a household and investigate issues such as privacy, competition, family dynamics.
  59. 59. DESIGN SET 1: ISOLATING DESIGN DIMENSIONSDesign Dimensions Explored1 Data Granularity Part of “Data Representation” in2 Time Granularity the eco-feedback design space3 Measurement Unit4 Comparison
  60. 60. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  61. 61. data information representation access inputs display medium thebehavioral eco-feedback design space comparison models social actionability motivational strategies
  62. 62. data representationtions aesthetic pragmatic artistic visual complexity simple complex time granularity < hour > year data granularity coarse-grain fine-grain measurement unit resource cost environmental time activity metaphor impact primary view temporal spatial categorical
  63. 63. data representationtions aesthetic pragmatic artistic visual complexity simple complex time granularity < hour > year data granularity coarse-grain fine-grain measurement unit resource cost environmental time activity metaphor impact primary view temporal spatial categorical
  64. 64. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS Data Granularitycoarse-grain fine-grain ≥neighbor- home room activity fixture fixture ≤ valve hood category
  65. 65. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS Time Granularity≤ hour day week month ≥ year
  66. 66. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS Measurement Unitresource rate of cost time activity metaphor consumption36 gallons 3 gpm 9 cents 12 minutes 1 shower of water
  67. 67. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS data representationtions aesthetic pragmatic artistic visual complexity simple complex time window < hour > year data granularity coarse-grain fine-grain measurement unit resource cost environmental time activity metaphor impact primary view temporal spatial categorical
  68. 68. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS data representationtions
  69. 69. DESIGN SET 1: ISOLATING DESIGN DIMENSIONS comparisonity comparison target self social goal comparison by time past projected social comparison target geographically demographically selected social proximal similar network goal-setting strategy self-set system-set externally set difficulty to reach comparison target easy hard
  70. 70. comparisonity comparison target self social goal comparison by time past projected social comparison target geographically demographically selected social proximal similar network goal-setting strategy self-set system-set externally set difficulty to reach comparison target easy hard
  71. 71. DESIGN SET 1: ISOLATING DESIGN DIMENSIONSDesign Dimensions Explored Data Granularity Individual Fixture Fixture Category Activity Hot and Cold Time Granularity So Far Today So Far This Week So Far This Month Comparison Self Comparison To Others To A Goal Social/SelfMeasurement Unit In Gallons In Dollars Dollars / Gallons Including Sewage
  72. 72. Two sets of designs:1 Design Dimensions Isolate eco-feedback design dimensions in the context of water usage2 Design Probes Meant to elicit reactions about how displays would fit within a household and investigate issues such as privacy, competition, family dynamics.
  73. 73. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  74. 74. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  75. 75. Daily Patterns of Water Usage Washing Machine Shower Bath Faucets Toilets Gallons[Adapted from Butler, Building and Environment, 1993]
  76. 76. DESIGN SET 2: DESIGN PROBESTime-Series Views
  77. 77. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  78. 78. DESIGN SET 2: DESIGN PROBESSpatial View
  79. 79. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  80. 80. DESIGN SET 2: DESIGN PROBESPer-Occupant View
  81. 81. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  82. 82. DESIGN SET 2: DESIGN PROBES Aquatic Ecosystem Design Influences ubifit Consolvo et al., CHI2008 ubigreen Froehlich et al., CHI 2009 Consolvo et al., UbiComp2008
  83. 83. DESIGN SET 2: DESIGN PROBESAquatic Ecosystem View Movie Water savings New water “Frank” the fish water savings met met goal goal meets his mate savings tracker display is also “Frank” interactive so the fish fish respond to touch Frank and his mate have children and so on…
  84. 84. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  85. 85. DESIGN SET 2: DESIGN PROBESRainflow View
  86. 86. DESIGN SET 2: DESIGN PROBESRainflow View Movie
  87. 87. DESIGN SET 2: DESIGN PROBESDesign Probes Explored Time- Aquatic Series Eco-system Spatial Rainflow Per- Other Occupant
  88. 88. DESIGN SET 2: DESIGN PROBESOther Design Probes Geographic Comparisons Dashboards Metaphorical Unit Designs Recommendations
  89. 89. Evaluation
  90. 90. Informal interviews with water experts (e.g., SPU, Amy Vickers)UW Environmental Practicum on waterLiterature review of water resource management, environmental psychologyOur own online survey of water usage attitudes & knowledge (N=656 respondents) Design critique sessions with team Three sets of pilot studies Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation Informed by gathered data Guided by eco-feedback design space Online interactive survey of designs (N=651 respondents) In-home interviews (10 households, 20 adults)
  91. 91. Online Survey Recruitment o Online postings and word-of-mouth Survey Design o 63 questions (10 optional) o Question and answer order randomized when possible Collected Data o 712 completed surveys (651 from US or Canada) o Nearly 6,000 qualitative responses
  92. 92. In-Home Interviews Recruitment o Online postings and word-of-mouth o Specifically recruited families Interview Method o Semi-structured with two researchers o 90-minutes, 3-phases o Data coded by two researchers into themes Participants o 10 households (20 adults) o 11 female/9 male o Diff. socio-economic backgrounds & occupations o 18 had college degrees
  93. 93. For both the survey and interviews, 90% ofparticipants indicated an interest in conserving water Average morning shower uses 400 gallons of water
  94. 94. Findings
  95. 95. Data Granularitycoarse-grain fine-grain ≥neighbor- home room activity fixture fixture ≤ valve hood category This display lets you more easily identify the specific areas that need attention R536 Majority preferred the Individual Fixture Display
  96. 96. Data Granularitycoarse-grain fine-grain ≥neighbor- home room activity fixture fixture ≤ valve hood category This display lets you more easily identify the specific areas that need attention R536 Majority preferred the Individual Fixture Display
  97. 97. Data Granularitycoarse-grain fine-grain ≥neighbor- home room activity fixture fixture ≤ valve hood category 20% preferred the Activity Display
  98. 98. Measurement Unit resource rate of cost time activity metaphor consumption71% of respondents preferred to see both gallons and cost Seeing the gallon amount triggers the ‘save the environment’ impulse to conserve, while the dollar amount is helpful because almost everyone is motivated by money to some extentR143 I dont think very well in ‘thousands of gallons’, but $20 I can understand. That’s a case of beer down the drain, if you will R48
  99. 99. Time Granularity ≤ hour day week month ≥ yearMajority of respondents wanted ability toswitch between different time granularities
  100. 100. Comparisons were the most uniformly desired pieces ofinformation of all the dimensions
  101. 101. Self-comparisonwas most preferred91%
  102. 102. Emergent Themes1 Competition and Cooperation2 Accountability and Blame3 Playfulness and Functionality4 Sense of Privacy5 Display Placement
  103. 103. Competition and Cooperation “ ” You can compare usage to others, and create friendly competition “ ”R220 It pits the family members against each other rather than encouraging collaboration “ R485 [It] sets up a ‘competitive’ environment that we are trying not to create in our household R493
  104. 104. Accountability and Blame “ ” It holds each individual accountable for water usage “ ”R354 There’s no reason to add an element of ‘blame’ to conservation efforts within a family “ R98 Would seem to lead to plenty of arguments about usage R144
  105. 105. Playfulness and Functionality “ ” I like the idea of getting rewards for saving water “I8.2 ” It’s like unlocking badges in Foursquare. No matter how trivial it can be to make a fish appear on this screen, you still want to do it “I4.1 It doesn’t appeal to me as much. I don’t do Foursquare. This distracts me a little bit and it doesn’t make me think about my usage I4.2
  106. 106. Useful as an educational tool?
  107. 107. Privacy Spectrum Least MostInvasive Invasive
  108. 108. It’s incredibly invasive.And other people’swater consumption isnot my business. R25
  109. 109. Water usage formany purposes canbe very personal, andshouldn’t beautomatically shared R25
  110. 110. Privacy Spectrum Least MostInvasive Invasive
  111. 111. Display Location Preferences
  112. 112. If we placed thedisplay here, the kidscouldn’t see it. I2.1
  113. 113. Display Location Preferences kitchen near thermostat high traffic areas accessiblewhen needed
  114. 114. Primary Contributions1 First work to design and evaluate feedback visualizations for disaggregated water data2 An iterative design roadmap for others working in the space of eco-feedback or other behavior change technologies
  115. 115. Sensing and feedbackfor water quality notjust consumption
  116. 116. Data Ideation / Pilot FormativeIdeation Refinement Gathering Sketch Studies Evaluation
  117. 117. Closing Thought Eco-feedback displays do not just visualizeconsumption, they document household activities
  118. 118. The Eco-Feedback Team! Solai Josh Inness Fabia Mazhengmin Marilyn Eric Leah Shwetak JamesAcknowledgements:Seattle Public Utilities: Ray Hoffman, Director; Al Diettemann, Water Conservation Expert; Bob AlpersAmy Vickers, Water Conservation ExpertAustin Polebitski, Assistant Professor of Civil and Environmental Engineering, UMassDavid Hsu, Assistant Professor City and Regional Planning, UPennSara Sheridan for her early design work
  119. 119. Questions? @jonfroehlichdesign: UNIVERSITY ofuse:build: WASHINGTON

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