As a digital storyteller, producer and co-songwriter of the Digital Song Story(tm) "The Light @ 99th" - I have a goal to expand the scope of the conventional (and nearly exhausted) music video medium to become more immersive, more engaging and multidimensional. In July 2013 - I took a data visualization course from the School of Visual Arts in NYC. The question I started the class with was: How can data visualization help music & media artists tell more compelling thematic stories? This deck is a low-to-medium-fidelity prototype of how I intend to expand the storyworld of my Digital Song Story(tm) partly through data visualization and interaction design.

1. THE LIGHT @ 99TH
A Digital Song Story™
Hilla Katki - SVA InfoVisualization -
2013 Summer Intensive - IxD Dept.
WORK IN PROGRESS
© 2013 - MediaGroove LLC

2. Question I started
this class with:
How can data visualization help
music & media artists tell more
compelling thematic stories?

3. THEMES
The Light @ 99th is a song about WORK -
and the DAILY COMMUTE is a theme
that many can relate to

4. ©MediaGroove LLC - 2013
The Light @ 99th
As our lives revolve around work and
the demands of work on our waking
hours, the time spent commuting to
the office is the land of daydream for
some – and dread for others. As
seasons race pass during the limbo of
transit – gazing out the window at
hours of our life we’ll never get back –
what does our daily path tell us about
who we are?
Digital Song Story #1
Play it::

5. GOAL
Build a immersive, interactive and responsive web
experience - using HTML 5,WebGL, conventional
video and animation - blended with great
interaction design, and data-driven storytelling.

6. THAT’S 1.6 MILLION STORIES
From the macro-view to the individual journey -
how can we capture and share these experiences?
Every business day,
Manhattan swells with
1.6million
work commuters*
*Source - American Community Survey - US Census 2010
WORK & COMMUTING

7. Result:A mash-up of conventional and data-driven storytelling
USE SOUND ANDVISUALS
connected to DATA about COMMUTING
to BRING COMMUTER STORIESTO LIFE
CONCEPT

8. DATA SOURCES
Commuter Rail Into Manhattan -TimeTables / Ridership by Hour
“Workers who live in NewYork state show the highest rate of long commutes
(defined as 60 minutes or longer) at 16.2 percent, followed by Maryland and New
Jersey at 14.8 percent and 14.6 percent, respectively.”
Source: Census.gov ›American Community Survey (ACS) › Megacommuters: 600,000 in U.S. Travel 90 Minutes and 50 Miles
to Work, and 10.8 Million Travel an Hour Each Way

9. AUDIO PARAMETERS
1. SOURCE:
(A) Each transit type is assigned a unique Sound Loop (SL) -
derived from individual tracks of the song Light @ 99th.
2. BEHAVIORS:
(A) Controls:
Each SL is user-controlled, toggle on/off.
(B) Data = Amplitude:
Each SL’s volume is controlled by hourly ridership.
(C) Time Frame/Window:
Each transit data source is set to a 24hr. timeline -
compressed and mapped against a 2:30 looped clock.
(D)Sync:
Each SL is Beat-Matched to start on the first bar of a
looping 4 bar phrase.

10. AUDIO SOURCING
From ProTools, the individual tracks
were saved as sound loops

11. STORYBOARDING PROCESS
Blending conventional narrative with data-driven storytelling

12. DATA:
TIME SPENT
Extreme and Average
Commute Hours -
Converted to Days per Year
INTERACTION
EACH RAIL LINE WILL BE
INTERACTIVE - TRIGGERING A
DISCRETE, SYNCHRONIZED SOUND
LOOP FROMTHE TRACKS OFTHE SONG
Peak commute time:
1:37 X 2 =3:14hr per day
X 5= 16:10wk X 48wk =
32.33 commute days per year
AUDIO: SIMPLE BUILD OF 7
TRACKS FROM LIGHT @ 99th.
NOTE: SONG BEATS AND
INSTRUMENTS ARE NOT
SYNC’ed in THIS EXAMPLE
Timeline will depict ridership over 24 hrs - compressed to 2:30

13. Embedding data points into animation and live video
SONG STORY
DATA POINTS
FACTS ABOUT METRO NORTH RIDERSHIP
WILL BE EMBEDDED AS HOTSPOTS
THANK YOU
WORK IN PROGRESS
© 2013 - MediaGroove LLC