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  • 8/7/2019 06-Sentient Cities

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

    description:

    starting arrangement of the chess board

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

    description:

    a visualization of the possible moves and scenearios available after the 1st move

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

    description:

    when the pieces are redcued, variations within the pattern that is available begin to emerge

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

    description:

    last few pieces of the chess match

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    06 - Thinking Machine6334: Sentient Cities as Cybernetic, Real-time, Control Systems: Theory and Practice of Urban Sensing

    description:

    1. How was the data collected? from all the possible moves that can be played on the board2. Why was the data collected? for the computer to make a strategical counter move to the players initial move

    3. What is interesting about the data? the data reprasents a dynamic set of information to a series of dffering parts within the game of chess.4. What stories about urban dynamics can the collected data tell?

    varying data from objects collected within an urban context, similar to chess, can prescribe a multitude of outcomes that would be otherwise difficult for thecommon person to decipher

    5. What sort of questions about urban dynamics can be answered by looking at the data?

    -6. Who is the target audience of the data visualization? chess players, and board game enthusiasts7. What are the audiences goals when approaching the visualization? to gain a better understanding into the counter moves that are established by the computer, and why certain moves are performed rather than other moves.

    8. What do they stand to learn? better moves and counter moves to chess9. What sort of control are they offered over the interface that delivers the information?

    The player of the game has full control over his side of the board10. How is the question of the magnitude of the data dealt with limiting the collected data, limiting the dimensionsons in the data set to be represented, or abstractingthe data? it focuses on the game of chess - no variations

    11. How does the original question to be addressed operate as the bench mark for eliminating unnecessary details in the data visualization? -12. How are the particular patterns highlighted through visualization techqniques in order of their importance?

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    13. Is the data of static or dynamic in nature? dynamic14. If the data is dynamic in nature, what happens when it starts to change? how does the audience interact with this live data? How is the data that changes over

    time unraveled? the data will always change based upon the variation of moves and scenarios that exist for each piece on the chess board. Like with playing chess, the audience

    needs to react to the resultant of the data, and adjust accordingly

    queries