This presentation was made at the Public Sector Data Management Forum held in Melbourne in 2nd April 2019. In this presentation, Richard provided insights into the challenges he has observed regarding the theme of "scoping integrated data management" - taking an inter-disciplinary perspective where data management is conceived as a function that forms part of a wider broadly based knowledge ecology.

1. Scoping Integrated Data
Management
A case study from Agriculture
Richard Vines

2. An brief introductory story
Story theme
Data management
is messy –
It involves subject matter
expert’s personal knowledge
and committed action with
multiple stakeholders
potentially over long periods of
time
The forest fires of Dwellingup in Western Australia - 1961
The aftermath– The Royal Commission.
Response was to first invest in better equipment, radio communications and weather
forecasting. Secondly, to invest in a fire behaviour research program

3. Over 45 year later in 2017
Australian fire innovation wins international (US) award
Mid 1960’s to early 1970’s
Pioneering of aerial prescribed burning in
Western Australia drawing upon research science
… with the emergence of the Very Early Smoke Detector Apparatus (VESDA)
An introductory story about ……..
Involving science, scientific instrumentation,
data, commercialisation and innovation

4. 1960s-70s CSIRO Scientists in 2010
1961 Western Australian forestry
workers in 2010
… and then the emergence of contemporary data management capabilities
Jim Williamson, Frank Campbell and George Peet
David Packham, Bob Vines and David McCarthur
An introductory story about ……..
2018 announcement

5. Data management is not an end it itself
From a knowledge management perspective, data management forms part of a networked knowledge ecology
• The opportunities of “big data” and “big data
systems” are real and rapidly evolving but need to
be treated with a great deal of pragmatic
cautiousness
• The design of data management infrastructure
follows the design of science based solutions to
problems
• Scientists and particularly numerical modelers need to
drive process of “designing and doing data
management”. Equally everyone needs to
acknowledge the need for new “socio-technical”
capabilities
• This requires a creative response - principles of inter-
disciplinary research, trust building and co-design are
imperative
Data
Key messages

6. Agriculture Victoria Research operating context

7. What is meant by “scoping” integrated data management?
The function of data management needs to be linked to
a demand for “problems to be solved”
Problems need to be identified, negotiated
and prioritised. Data management supports
this process of developing solutions to
problems
An example
Victoria’s is experiencing a significant reduction
in the amount of water available to dryland and
irrigated agriculture. Predictions of future
climates being more variable but often hotter
and drier is further increasing the pressure on
farmers to grow more from less water
Requiring
social
governance

8. The function of data management is integrated into the
design for a response to an identified problem
Demand for science
based solutions
Supply of science
based solutions
What is meant by “integrated data management”?

9. Example of
new modes of
procuring data
management
services
Grains industry

10. The complexity, sources and format of data sources are increasing
and require greater levels of technical governance and specialised
forms of investment
Technical
governance
What is meant by “integrated data management”?
Social
governance
Drones
Satellites
Data monitoring informing decision making

11. Integrated data management means we are moving towards real time,
data informed, modelling based decision support services
What is meant by “scoping” “integrated data management”?

12. Data management has a program management context
Resource use innovation strategic action plan
Program
Program
Program
Program
What is meant by “scoping” “integrated data management”?

13. A program management
framework involves headline
indicators
Underpinned by real world
monitoring, space-based data
and a flexible spatial grid
What is meant by “scoping” “integrated data management”?

14. Reflective conclusions
Scoping Integrated Data Management - A case study from Agriculture
• The opportunities of “big data” and “big data
systems” are real but need to be treated with a
great deal of pragmatic cautiousness
• The design of data management infrastructure
follows the design of science based solutions to
problems
• Scientists and particularly numerical modelers
need to drive the process of “designing and doing
data management”. Equally everyone needs to
acknowledge the need for new “socio-technical”
capabilities
• This requires a creative response - principles of
inter-disciplinary research, trust building and co-
design are imperative
Thank you – for further questions contact – richard.vines@ecodev.vic.gov.au