Personal informatics systems that help people collect and reflect on various kinds of personal data are rapidly growing. However, research in this area primarily focuses on quantitative data, such as physiological data, exercising behaviors, and financial transaction. And a limited number of studies have been done to support self-reflection on one’s past experiences. We designed a conceptual journaling application Pensive, in the hope of facilitating the collection and reflection of personal experience.

  • Fig1. Pensive dashboard

    Pensive supports manual journaling as well as automatic data import from the user’s authorized social network accounts. Users can add semantic annotations to each journal entry by tagging related people, location (context) and topics; they can also add emoticons representing their emotions.

  • Fig2. create a new story

    User can create a story in Pensive and apply meaningful tags to it, they can also give a rating of importance to the story as well as the mood relating to it. User can also search for related stories using keywords and create reference to them in the current story.

  • Fig3. connecting related stories

    Connecting related stories together is an important feature of Pensive.

  • Fig1. Review a story

  • Fig2. search for stories

    User can search for stories from several dimensions, including person, location and keywords.

  • Fig3. search results

    User can also comment on the search results.

  • Fig1. Emotion curve view of monthly stories

    Pensive visualizes the stories in three ways: curve chart, bubble chart and listing. The monthly view shows the general patterns of how the emotions change and the summary for each emotion.

  • Fig2. Emotion curve view of Weekly stories

    The weekly view shows more details of the stories.

  • Fig3. Emotion curve view of daily stories

  • Fig4. Bubble view of monthly stories

    The bubble view summarizes the major themes of the stories by grouping stories with the same tag together, and use colors and sizes to indicate the weight of each emotions.

Concept: Afarin Pirzadeh, Li He, Erik A. Stolterman

Interaction & Visual Design: Li He