Key success factor

The Nectar project brings huge benefits to the society, in order to achieve the final result and gain actual project benefit from the project success, a series factors is used to measure project progress. The project success is based on all project deliverables are completed and accepted by all stakeholders. The project stakeholders includes Prof Mandred Lenzen, University of Sydney, developer team from intersect, project management team from ICT, the University of Sydney, Dr Thomas Weidman, Prof Richard Stuetz – UNSW and Dr Arne Geschke, the University of Sydney.

Evidence of project success includes:

1. Deployment of raw data repository structure in NecTar cloud. 

2. Initial integration of automated data feed for state level IO tables.

3. Initial integration of automated data feed for sub-state level IO tables.

4.  Initial integration of automated data feed from disaggregated waste sector data.

5.  Initial integration of automated data feed for ABS water & energy accounts.

6. Initial integration of automated data feed for Materials Flow Accounts data.

7. Construction of standalone ‘Peripherals Repository’ for miscellaneous environmental - extensions data

8.  Integration of automated data feed from ‘Peripherals Repository.
9. Deployment of the MRIO optimiser and integration of automated data feeds for inter-regional commodity trade.
10.  Initial deployment of analysis toolbox.
11.  Deployment of Share Interface.
12. Completed integration of automated data feed for state level IO tables.
13. Completed integration of automated data feed for sub-state level IO tables.
14. Completed integration of automated data feed from dis aggregated waste sector data.
15. Completed integration of automated data feed for ABS water & energy accounts.
16. Completed integration of automated data feed for Materials Flow Accounts data.
17. Completed integration of automated data feed from ‘Peripherals Repository.
18. Finalisation of optimiser integration.
19. Completion and deployment of entire Mother MRIO table time series in cloud.
20.  Final deployment of analysis toolbox and visualisation tools.