A Stage-Based Model

  of Personal Informatics Systems
  Ian Li
  Anind Dey
  Jodi Forlizzi

  HCII, Carnegie Mellon Unive...
Gnothi seauton.




Ian Li, Anind Dey, Jodi Forlizzi   A Stage-Based Model of Personal Informatics   CHI 2010
   2
Know thyself.




Ian Li, Anind Dey, Jodi Forlizzi   A Stage-Based Model of Personal Informatics   CHI 2010
   3
Self-knowledge is valuable.




Ian Li, Anind Dey, Jodi Forlizzi   A Stage-Based Model of Personal Informatics   CHI 2010
...
A way to get self-knowledge
  Collect information about yourself, 

  e.g., oneʼs behaviors, habits, and thoughts.

  Refle...
Personal Informatics
  A class of systems that help people 

  collect and reflect on their behavior 

  to gain self-knowl...
Physical Activity

  Finance

  Electricity

  Diabetes

  Health

  Mood


                http://personalinformatics.org...
Alice
                                                  •  20 years old
                                                  ...
1. Alice prepares.




Ian Li, Anind Dey, Jodi Forlizzi   A Stage-Based Model of Personal Informatics   CHI 2010
   9
2. Alice collects data.
                                                                                             Mon  ...
3. Alice transcribes data. 
  Transcribe to Excel




                                           M
       T
 W Th
 F
 Sa
 ...
4. Alice reflects on the data.

                                                                         Active



        ...
5. Alice takes action.
                                                                                 Walk in the park
 ...
Model of Personal Informatics
              PREPARATION          COLLECTION         INTEGRATION          REFLECTION       ...
Model of Personal Informatics
              PREPARATION          COLLECTION         INTEGRATION          REFLECTION       ...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
Personal Informatics
  Self-tracking
  Personal analytics
  Living by numbers




Ian Li, Anind Dey, Jodi Forlizzi   A Sta...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Other research have explored these different
  stages...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Other projects have combined collection and
  reflecti...
Why a model 

  of Personal Informatics?
  A growing field with many HCI challenges
  •  Tools are used over a long period ...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
Survey
  What personal informatics tools they use

  What problems they encountered




Ian Li, Anind Dey, Jodi Forlizzi  ...
Survey Questions
  •  How difficult is it to collect this personal
     information?
  •  What was your initial motivation ...
Participants
  Advertised the survey in blogs about
  personal informatics.

  68 users of personal informatics tools

  1...
Types of Information
  Automatically collected
  •  Financial institutions (banks, credit cards)
  •  Utility companies (e...
Types of Information
  Manually collected
  •  Fewer participants, but greater variety

  Calendar events, status updates,...
Reasons
  Interested in personal data
  •  “data nerd”
  •  “a student of information visualization”
  •  “this data is ab...
Analysis
  Identified barriers that people experienced.

  Affinity diagrams to identify themes 

  Derived a model composed...
Introduction
   Personal Informatics Systems
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   ...
PREPARATION          COLLECTION         INTEGRATION          REFLECTION        ACTION




Ian Li, Anind Dey, Jodi Forlizzi...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Preparation
  The stage before people start collectin...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Preparation Barriers
  •  Choosing the right informat...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Collection
  The stage when people collect informatio...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Collection Barriers
  •  Using the tool
  •  Remember...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Collection Barriers
  •  Using the tool
             ...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Integration
  The stage when the information from the...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Integration Barriers
  •  Organization
  •  Scattered...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Integration Barriers
                                ...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Reflection
  The stage when people reflect on their
  p...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Reflection Barriers
  •  Lack of time
  •  Self-critic...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Reflection Barriers
                                  ...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Action
  The stage when people choose what they are
 ...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  Action Barriers
  •  Not knowing what to do with the
...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  1. Barriers cascade
  2. Stages are iterative




Ian...
1. Barriers Cascade
  Problems in the earlier stages can affect the
  later stages.




Ian Li, Anind Dey, Jodi Forlizzi  ...
1. Barriers Cascade.




                                           M
       T
 W Th
 F
 Sa
 Su
 M
                   T


...
1. Barriers Cascade.




                                           M
       T
 W Th
 F
 Sa
 Su
 M
                   T


...
1. Barriers Cascade
  P44 lacked time and motivation during
  Collection stage.

  About Reflection stage, he said:
  “I wi...
1. Barriers Cascade
  Design Guideline
  Consider all the stages when designing PI
  systems.
                            ...
2. Stages are Iterative
  Users may need to incorporate 

  new types of data, tools, and processes 

  as they progress t...
2. Stages are Iterative




                                           M
       T
 W Th
 F
 Sa
 Su
 M
                   T...
2. Stages are Iterative




                                           M
       T
 W Th
 F
 Sa
 Su
 M
                   T...
2. Stages are iterative.
  P48 switched between Google spreadsheets,
  Daytum, and your.flowingdata to collect
  restaurant...
2. Stages are Iterative.
  Design Guideline
  Flexibility is important.

  •  Support easy importing and exporting of
    ...
PREPARATION   COLLECTION   INTEGRATION    REFLECTION    ACTION




  1. Barriers cascade.
  2. Stages are iterative.
  3. ...
3. User- vs. System-driven

     User-driven
                                                                 System-drive...
3. User- vs. System-driven
                                                  Mon     
1573
                               ...
3. User- vs. System-driven



                                                                    User-driven
            ...
3. User- vs. System-driven
  Design Guideline
  Consider the tradeoffs between user-driven
  and system-driven stages.



...
4. Facets
  Peopleʼs lives are composed of many facets.
  •  Home life vs. work life
  •  Daily interactions with other pe...
4. Facets
  Users expressed desire to see associations
  between different facets of their lives.
  •  “To understand tren...
4. Facets
  Most personal informatics are uni-faceted.

  Some personal informatics systems have
  multi-faceted collectio...
4. Facets
                                    Location
                         Activity
              People
            ...
4. Facets
  Design Guideline
  Supporting multiple facets may help users
  find associations between facets of their
  live...
Model of Personal Informatics
  5 Stages

  4 Properties
  •  Design guidelines




Ian Li, Anind Dey, Jodi Forlizzi   A S...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
Case Studies
  1.  Twitter-based systems
  2.  Mint (http://mint.com)
  3.  IMPACT




Ian Li, Anind Dey, Jodi Forlizzi   ...
IMPACT
  Different from most personal informatics
  systems for physical activity:

  •  Collects physical activity inform...
Two prototypes – Two studies
  IMPACT 1.0
                                                    IMPACT 2.0
  Manual collecti...
Collection vs. Reflection
                                                                  Short-term                 Long...
The model and IMPACT
  The model helped analyze the different
  aspects of IMPACT.

  IMPACT highlights the necessity to c...
Introduction
   Personal Informatics
   Surveys and Interviews
     
The Stages
     
Properties of the Stages
   Case Stu...
Contribution: Barriers and Model
  Identified a list of problems
  •  Highlights the many HCI challenges of
     building e...
Contribution: Design Guidelines
  Described 4 properties with implications for
  design of personal informatics systems
  ...
Thank you!
  http://personalinformatics.org/
  http://personalinformatics.org/lab/model

  Ian Li        
ianli@cmu.edu
  ...
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A Stage-Based Model of Personal Informatics Systems (CHI 2010 Talk)

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People strive to obtain self-knowledge. A class of systems called personal informatics is appearing that help people collect and reflect on personal information. However, there is no comprehensive list of problems that users experience using these systems, and no guidance for making these systems more effective. To address this, we conducted surveys and interviews with people who collect and reflect on personal information. We derived a stage-based model of personal informatics systems composed of five stages (preparation, collection, integration, reflection, and action) and identified barriers in each of the stages. These stages have four essential properties: barriers cascade to later stages; they are iterative; they are user-driven and/or system-driven; and they are uni-faceted or multi-faceted. From these properties, we recommend that personal informatics systems should 1) be designed in a holistic manner across the stages; 2) allow iteration between stages; 3) apply an appropriate balance of automated technology and user control within each stage to facilitate the user experience; and 4) explore support for associating multiple facets of people’s lives to enrich the value of systems.

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A Stage-Based Model of Personal Informatics Systems (CHI 2010 Talk)

  1. 1. A Stage-Based Model
 of Personal Informatics Systems Ian Li Anind Dey Jodi Forlizzi HCII, Carnegie Mellon University Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010
  2. 2. Gnothi seauton. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 2
  3. 3. Know thyself. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 3
  4. 4. Self-knowledge is valuable. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 4
  5. 5. A way to get self-knowledge Collect information about yourself, 
 e.g., oneʼs behaviors, habits, and thoughts. Reflect on the information about yourself. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 5
  6. 6. Personal Informatics A class of systems that help people 
 collect and reflect on their behavior 
 to gain self-knowledge Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 6
  7. 7. Physical Activity Finance Electricity Diabetes Health Mood http://personalinformatics.org/tools Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 7
  8. 8. Alice •  20 years old •  Family history of heart disease •  Wants to be more active, but doesnʼt know how because sheʼs busy Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 8
  9. 9. 1. Alice prepares. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 9
  10. 10. 2. Alice collects data. Mon 1573 Tue 4392 Wed 4537 Thu 5842 Fri 10258 Sat 7528 Sun 1368 Mon 1497 Tue 1837 Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 10
  11. 11. 3. Alice transcribes data. Transcribe to Excel M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 11
  12. 12. 4. Alice reflects on the data. Active Inactive Inactive M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 12
  13. 13. 5. Alice takes action. Walk in the park instead of watching TV M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 13
  14. 14. Model of Personal Informatics PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 14
  15. 15. Model of Personal Informatics PREPARATION COLLECTION INTEGRATION REFLECTION ACTION 1.  Barriers cascade. 2.  Stages are iterative. Design
 3.  User- vs. System-driven Guidelines 4.  Facets Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 15
  16. 16. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 16
  17. 17. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 17
  18. 18. Personal Informatics Self-tracking Personal analytics Living by numbers Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 18
  19. 19. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Other research have explored these different stages in isolation: •  Collection •  MyLifeBits (Gemmell et al. 2006) •  SenseCam (Hodges et al. 2006) •  Reflection •  Casual InfoVis (Pousman et al. 2007) Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 19
  20. 20. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Other projects have combined collection and reflection on personal information •  Physical Activity: FishʼnʼSteps (Lin ʼ06), Shakra (Maitland ʼ06), UbiFit (Consolvo ʻ08) •  Sustainability: StepGreen (Mankoff ʼ08), UbiGreen (Froehlich ʼ09) •  Many systems for finance, health, physical activity, productivity, etc. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 20
  21. 21. Why a model 
 of Personal Informatics? A growing field with many HCI challenges •  Tools are used over a long period of time. •  User is involved throughout the process. No comprehensive list of problems Developers need a guide for development 
 and assessment of these tools Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 21
  22. 22. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 22
  23. 23. Survey What personal informatics tools they use What problems they encountered Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 23
  24. 24. Survey Questions •  How difficult is it to collect this personal information? •  What was your initial motivation to reflect on this collected personal information? •  What patterns have you found? Transcript of the survey is at: http://personalinformatics.org/lab/survey Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 24
  25. 25. Participants Advertised the survey in blogs about personal informatics. 68 users of personal informatics tools 11 participated in follow-up interviews over instant messenger Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 25
  26. 26. Types of Information Automatically collected •  Financial institutions (banks, credit cards) •  Utility companies (electricity, heating) •  Computers (email and browsing history) Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 26
  27. 27. Types of Information Manually collected •  Fewer participants, but greater variety Calendar events, status updates, work activities, blog posts, weight, exercise, browser bookmarks, time at work, mood, journal, sleeping habits, food consumption, productivity, health, medication intake, symptoms, miles ran, sports activities, blood pressure, blood sugar level, dream journal, step counts, relationship status, books read, transportation Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 27
  28. 28. Reasons Interested in personal data •  “data nerd” •  “a student of information visualization” •  “this data is about ME (her emphasis).” Trigger events (e.g., problems with physical activity, nutrition, weight, etc.) Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 28
  29. 29. Analysis Identified barriers that people experienced. Affinity diagrams to identify themes Derived a model composed of: •  5 stages •  4 properties http://www.flickr.com/photos/ludens/3185982588/ Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 29
  30. 30. Introduction Personal Informatics Systems Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 30
  31. 31. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 31
  32. 32. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Preparation The stage before people start collecting information. •  What information to record •  How to record the information Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 32
  33. 33. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Preparation Barriers •  Choosing the right information to collect •  Finding the right tool to use Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 33
  34. 34. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Collection The stage when people collect information about themselves (e.g., inner thoughts, behavior, social interactions, and their immediate environment). Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 34
  35. 35. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Collection Barriers •  Using the tool •  Remembering •  Lack of time •  Motivation •  Finding data •  Accuracy Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 35
  36. 36. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Collection Barriers •  Using the tool One problem is:
 •  Remembering “Keeping up the •  Lack of time motivation to do so; •  Motivation like finding payback for the investment of •  Finding data time and effort.” •  Accuracy Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 36
  37. 37. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Integration The stage when the information from the Collection stage is prepared, combined, and transformed for the user to reflect on. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 37
  38. 38. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Integration Barriers •  Organization •  Scattered visualizations •  Transcribing data •  Multiple inputs Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 38
  39. 39. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Integration Barriers “Itʼd be neat if I could •  Organization graph [the data] •  Scattered straight from the web site instead of visualizations manually typing in the •  Transcribing data data to a •  Multiple inputs spreadsheet.” Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 39
  40. 40. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Reflection The stage when people reflect on their personal information. •  Users may reflect immediately (short-term) •  Or after several days or weeks (long-term) Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 40
  41. 41. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Reflection Barriers •  Lack of time •  Self-criticism •  Visualization •  Interpretation •  Sparse data •  No context Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 41
  42. 42. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Reflection Barriers “Itʼs hard to get a •  Lack of time holistic view of the •  Self-criticism data since the time filters are at most one •  Visualization month and Iʼd like to •  Interpretation look at several •  Sparse data months at once.” •  No context Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 42
  43. 43. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Action The stage when people choose what they are going to do with their new-found understanding of themselves. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 43
  44. 44. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Action Barriers •  Not knowing what to do with the information •  Alerts •  Incentives •  Suggestions Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 44
  45. 45. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 45
  46. 46. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION 1. Barriers cascade 2. Stages are iterative Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 46
  47. 47. 1. Barriers Cascade Problems in the earlier stages can affect the later stages. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 47
  48. 48. 1. Barriers Cascade. M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 48
  49. 49. 1. Barriers Cascade. M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 49
  50. 50. 1. Barriers Cascade P44 lacked time and motivation during Collection stage. About Reflection stage, he said: “I wish I could report successes on this front, but my lack of regular collection has made this difficult.” Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 50
  51. 51. 1. Barriers Cascade Design Guideline Consider all the stages when designing PI systems. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 51
  52. 52. 2. Stages are Iterative Users may need to incorporate 
 new types of data, tools, and processes 
 as they progress through the stages. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 52
  53. 53. 2. Stages are Iterative M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 53
  54. 54. 2. Stages are Iterative M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 54
  55. 55. 2. Stages are iterative. P48 switched between Google spreadsheets, Daytum, and your.flowingdata to collect restaurants visited. But the tools did not allow importing data. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 55
  56. 56. 2. Stages are Iterative. Design Guideline Flexibility is important. •  Support easy importing and exporting of data. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 56
  57. 57. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION 1. Barriers cascade. 2. Stages are iterative. 3. User- or system-driven 4. Facets Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 57
  58. 58. 3. User- vs. System-driven User-driven System-driven Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 58
  59. 59. 3. User- vs. System-driven Mon 1573 Tue 4392 Wed 4537 Thu 5842 Fri 10258 Sat 7528 Sun 1368 Mon 1497 Tue 1837 User-driven System-driven Collection Integration Reflection Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 59
  60. 60. 3. User- vs. System-driven User-driven System-driven Collection Integration Reflection Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 60
  61. 61. 3. User- vs. System-driven Design Guideline Consider the tradeoffs between user-driven and system-driven stages. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 61
  62. 62. 4. Facets Peopleʼs lives are composed of many facets. •  Home life vs. work life •  Daily interactions with other people •  Health •  Finance Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 62
  63. 63. 4. Facets Users expressed desire to see associations between different facets of their lives. •  “To understand trends in symptoms, behaviors, and circumstances.” P26 •  “If it were easily collected, information on food intake, calories, fat, etc., would make an interesting starting point for analysis.” P49 who tracks medication intake Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 63
  64. 64. 4. Facets Most personal informatics are uni-faceted. Some personal informatics systems have multi-faceted collection, but only support uni-faceted reflection. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 64
  65. 65. 4. Facets Location Activity People Office Shopping Family Active Inactive Inactive M T W Th F Sa Su M T Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 65
  66. 66. 4. Facets Design Guideline Supporting multiple facets may help users find associations between facets of their lives. → Explore support for multiple facets. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 66
  67. 67. Model of Personal Informatics 5 Stages 4 Properties •  Design guidelines Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 67
  68. 68. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 68
  69. 69. Case Studies 1.  Twitter-based systems 2.  Mint (http://mint.com) 3.  IMPACT Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 69
  70. 70. IMPACT Different from most personal informatics systems for physical activity: •  Collects physical activity information 
 and context (e.g., type of activity, location, people) •  Visualizations to help users become aware
 of factors in their lives that affect their physical activity. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 70
  71. 71. Two prototypes – Two studies IMPACT 1.0 IMPACT 2.0 Manual collection Semi-automated collection Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 71
  72. 72. Collection vs. Reflection Short-term Long-term Reflection Reflection IMPACT 1.0 Manual GOOD NOT GOOD Collection IMPACT 2.0 Automated NOT GOOD GOOD Collection Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 72
  73. 73. The model and IMPACT The model helped analyze the different aspects of IMPACT. IMPACT highlights the necessity to consider the interactions between the different stages
 (e.g., Collection vs. Reflection) IMPACT shows value of multi-faceted support Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 73
  74. 74. Introduction Personal Informatics Surveys and Interviews The Stages Properties of the Stages Case Studies Conclusion Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 74
  75. 75. Contribution: Barriers and Model Identified a list of problems •  Highlights the many HCI challenges of building effective personal informatics tools Defined a model of personal informatics •  Common framework for describing, comparing, and evaluating such systems Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 75
  76. 76. Contribution: Design Guidelines Described 4 properties with implications for design of personal informatics systems 1.  Consider the design of all the stages. 2.  Flexibility between tools is important. 3.  Balance automation and user control. 4.  Explore support for finding relationships between facets of oneʼs life. Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 76
  77. 77. Thank you! http://personalinformatics.org/ http://personalinformatics.org/lab/model Ian Li ianli@cmu.edu Anind Dey anind@cs.cmu.edu Jodi Forlizzi forlizzi@cs.cmu.edu Funded by Ian Li, Anind Dey, Jodi Forlizzi A Stage-Based Model of Personal Informatics CHI 2010 77
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