London 2013 rgs_arrowsmith

Visualising heterogeneous cinema data sets

Big, Open Data and the Practice of GIScienceRGS-IBG Annual Conference, London 29 August 2013

Colin Arrowsmith, School of Mathematical and Geospatial Science, RMIT University, Melbourne, Victoria, Australia

Deb Verhoeven and Alwyn Davidson, School of Communication and Creative Arts, Deakin University, Melbourne, Victoria, Australia

2

A big data project

“Only at the movies: Kinomatics”

School of Mathematical and Geospatial Sciences

3

Objective

To investigate spatial patterns of film diffusion across the world.

–How do films circulate around the world?

–Does spatial clustering affect film screening?

–How does seasonality affect screening?

School of Mathematical and Geospatial Sciences

Dimensions of “Big data”

• Variety

• Velocity

• Volume

IBM “Bringing big data to the Enterprise”

(http://www-01.ibm.com/software/au/data/bigdata/)

• Visualization

School of Mathematical and Geospatial Sciences 4

Working with “Big data”

• Database downloaded from commercial film data collector

• 2 to 2.5 million showtime records per week

• 30000 movies downloaded after seven months

• 28000 cinema venues and 118000 screens

• 63.5 million records equating to 4.8 Gbytes of data


Database schema


Projects exploring approaches for visualising and analysing big film data

• Geographic methods– Post-war cinema venues in Australia (change-over-time)

– Global cartograms for cinema (point-in-time)

– Global patterns of movement

• Non-geographic (conceptual)– Multivariate visualisations (change-over-time)

– Film circulation (Markov-Chains)


Geographic examples

• Post-war cinema venues in Australia (change-over-time)

• Global cartograms for cinema (point-in-time)

• Global patterns


Static maps of post war cinema venues in Australia

• Basis for data was scanned “Film Weekly” summaries

• Base year of 1948 derived

• New and closed cinemas determined

• Significant post-processing


Film Weekly scan


Rural scale changes

1948 to 1953

1963 to 1968 1968 to 1971

1953 to 1958 1958 to 1963


Rural scale changes

1948 to 1953

1963 to 1968 1968 to 1971

1953 to 1958 1958 to 1963


Urban scale changes (Melbourne)

1948 to 1953

1963 to 1968 1968 to 1971

1953 to 1958 1958 to 1963


Global cinema cartograms

• Cartogram is a map where a thematic variable is substituted for area (or distance)

• Population substituted for area


CartogramsGlobal cinema numbers

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Global screen numbers

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Continent-wide patterns


Global patterns


Life of Pi

30 November 2012 7 December 2012

14 December 2012 21 December 2012 19

Life of Pi

28 December 2012 4 January 2013

11 January 2013 17 January 2013 20

Life of Pi (November 2012 to January 2013)


Life of Pi (November 2012 to January 2013)


Non-geographic examples

• Multivariate visualisations (change-over-time)

• Film circulation (Markov-Chains)


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Visualisations


Movement approaches: The Greek cinema circuit

• Objective

– To explore historical changes in the diasporic Greek cinema distribution of Finos and Anzervos films during the period 1956 to 1963

• Rationale

– To demonstrate the role of geographic analysis in understanding cinema circuit behaviour


Data acquisition

• Archival newspaper and oral history research

• Government records

– censorship records

– theatre licence and company records

• Geo-location using street address or via GPS


Anzervos


Finos


Anzervos (section)


Finos (section)


Key chains identified

No. of venues

Anzervos Finos

1 B C B A

2 BC CB BC AD

3 BCB CBC BCB BCA

4 BCBC MGPC BCBC BCBA


Circos – circular visualisations

• Film sequence (Fort of Freedom):

– BCBBBBBCAABBBBBB by screening

or

– BCBCAB venue sequencing


Change in sequence (Anzervos)

The Fort of FreedomAli Pasha and Mrs Frossini


Change in sequence (Finos)

AsteroMusic, Povery and Pride


Change of venue date



Ali Pasha and Mrs Frosini

SJA

AACC

CBBBBBBCB

0

0.5

1

1.5

2

2.5

3

3.5

0 10 20 30 40 50 60 70

Days

Mo

nth

s

The Fort of Freedom

BBBBBA

ACBBBBBCB

0

5

10

15

20

25

30

35

0 5 10 15 20 25 30 35 40

Days

Mo

nth

s



Music, Poverty and Pride

F

KKDDDDABBBBBB

BBBBB

IIAAG

CP

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120

Days

Mo

nth

s

Astero

DKFJJJJJJ

BBBBBB

DOO

BBBBBAA

AABBCBBBBBBCBBB

0

5

10

15

20

25

30

35

0 50 100 150 200 250

Days

Mo

nth

s


• The olives are where films finished: green= Sydney venue, purple = Melbourne venue

• Leaves are screenings: yellow is QLD, light green is NSW, darker green is VIC, dark brown is SA

• The distance is days between screenings and done to scale

Finos

OLIVE TREES

Anzervos


Issues working with “big” complex cinema data

•Multiple sources of data

•Working at multiple scales

•Working with historic data

•Multiple definitions

•Need for visualising both geographic and conceptual relationships


Technology

London 2013 rgs_arrowsmith