Using Innovative technology for planning Associate Professor Rochelle Eime

Sport Participation in Australia Problem: Lack of integration of sport participation data with other data Lack of systematic use of data to inform decision making Lack of national sport participation data Data: AccessIntegrationAnalysisKnowledge Solution Integration of data Analysis to inform program and policy development at organisational and national level Goal: more active, more often

Sport and Recreation Spatial Innovative use of latest technologies, GIS mapping capabilities and research to generate knowledge and insight for the sport and recreation, health and education sectors. Data collection, data integration, statistical analysis, data visualisation via geographical information system (GIS) programming and mapping, and dissemination of knowledge Provides increased capacity for strategic planning and development of participation programs and facilities

Critical factors for sport and recreation Participants Health PopulationFacilities

4 key areas Participation levels and trends Influences on participation Value of sport: the health benefits of participation Places to play: the nexus between facilities and participation

Range of data Leisure time physical activity data- 10 years Sport participation data- SSA’s- up to 5 years Player, coach and official Over 2.6 million records to date Sport and recreation facility data Population demographics Population projection data Health data Physical activity levels Education

Outputs GIS- Organisations directly use GIS to spatially visualise and analyse Sector-wide data Their own data Derived and customised indicators Research Individual research summary reports Sector level peer review publications Examples: Participation trends over time Participation age profiles Facility provision Attrition/drop-out Transition from modified sport program to competition

Technology OpenLayers, Mapserver, Mapcache and a spatially enabled database to dynamically generate choropleth maps. In excess of 190,000 possible map combinations by use of the following data aspects: Year ( ) Age Group (5 yr, 10 yr, 15 yr, 20 year, Custom) Gender (Male, Female) Participant Club (5000+) Participant Program (40+) Coach Level Umpire level Region type (Postcode, LGA and SA4) Data Metric (Total participants/coaches/umpires, Participation Rate (Percentage of region population, Change from Previous year)

Features

Participation numbers- Postcode Demographic breakdowns

Participation filters

Number of participants

Yearly participation rate- LGA

Changes in participation

Exporting data

Age profiles of sport

Health

Facilities

Provision of facilities

Details of facilities

Provision of facilities

Population projections

Socio-Economic Status

Contact Details Associate Professor Rochelle Eime VicHealth Research Practice Fellow Federation University, Victoria University (03)