MAPPING CULTURE

5. FINDINGS AND DISCUSSION
5.1 Approach
As discussed in our interim report, the data used in the analysis are generated by both
‘synthetic’ and ‘analytic’ approaches. In terms of the ‘synthetic’ data, we used the 2012
Floorspace and Employment Survey (FES) data supplied by the City of Sydney, which
mainly covered the venues of cultural/creative industries in the City of Sydney LGA.
Each record in the FES includes an ANZSIC (Australian and New Zealand Standard
Industry Classification) code that identified the main industry associated with that
venue. We mapped, respectively, our spatial and value chain categories to ANZSIC
codes. We then used that mapping to link those categories to specific venues, and
imported these augmented data into ArcGIS . Our goal was to demonstrate how
cultural venues in the FES data can be summarised and mapped according to two
types of cultural classification – what we refer to above as ‘spatial’ and ‘value chain’
flows (Section 3).
With regard to the ‘analytic’ data, we used the separate spreadsheets of cultural
venues supplied by the City of Sydney, including lists of theatres, cinemas, music
venues, and cultural buildings, the data collected from the crowd-sourced survey, and
additional ad hoc searches of industry directories, websites, festival brochures and
past research reports on cultural infrastructure and venues. Since, we had no ANZSIC
or other classificatory information, we manually applied individual spatial and value
chain designations to these records. The complete list of both ‘synthetic’ and ‘analytic’
data sources used in the project can be found in Appendix 4.
Table 5 shows the total entries of venues that we initially collected for this project. The
extract from the 2012 FES database contains 5,260 venues, each with a primary
ANZSIC designation. Our list of venues compiled from City of Sydney sources that do
not include floorspace data is 1,128 in total. Other venues extracted from the FES data
in shapefile format – such as those that are not conspicuously cultural but can be
used for cultural events (e.g. public parks) – totalled 268. We also expected that an
additional 50-100 non-overlapping venues would be identified via our crowdsourcing
survey. Table 5 summarises our initial data source statistics.
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