This presentation focuses on the quotation: "Can we better integrate policy, research science, modelling and ICT engineering solutions". It draws on principles of the marketing concept of "relationship proximity" and whether this idea has relevance to the successful development of "socio-technical systems" associated with the future of Agriculture and agricultural resource use management.

1. Linkages between ICT engineering
challenges and policy frameworks
A knowledge based perspective of agriculture and technology development
Richard Vines
Presentation made to the Information, Telecommunications, and Electronics Engineering (ITEE) College as part of a IT transforming Agriculture Forum. April 9 2019. Melbourne Australia

2. A brief introductory story
Story theme
Engineering
challenges are
messy –
They involve 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, engineering and innovation

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

5. Can we better integrate policy, research science, modelling
and ICT engineering solutions
Background context for presentation

6. Core idea
• Within the realm of social psychology, the proximity principle accounts for the tendency for individuals to
form interpersonal relations with those who are close by.
Core observations
• In the realm of scientific research and digital disruption, there is greater relationship proximity between
numerical modellers and scientists than there is between “data managers” and “enterprise architects”
and scientists.
• Are there are lower levels of relationship proximity between ICT engineers and those involved in research
science and modelling and those involved in the design of user orientated decision support platforms
• And the same may apply for policy representatives and scientists, engineers and software engineers
Does this really matter?
Can we better integrate policy, research science, modelling
and ICT engineering solutions
Drawing upon the principle of relationship proximity
Background context for presentation

7. Research science, ICT engineering and modelling go together
From a knowledge management perspective, innovations in the use of ICT solutions necessarily form part of a networked knowledge ecology
• The opportunities of “big data” and “big data systems”
and ICT design and engineering solutions are real and
rapidly evolving but need to be treated with a great deal
of pragmatic cautiousness
• The design of engineering solutions infrastructure follows
the design of science based solutions to problems
• Scientists, particularly numerical modelers and software engineers
need to drive process of “designing and doing data management”.
Equally everyone needs to acknowledge the need for new “socio-
technical” capabilities
Key messages
• This requires a creative response - principles of inter-
disciplinary research, trust building and co-design are
imperative
A knowledge-based perspective of linking policy, ICT technologies and agriculture
Problem
context

8. Agriculture Victoria Research operating context
My operating context

9. A knowledge-based perspective of linking policy, ICT technologies and agriculture
ICT engineering, science and modelling need 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 identifying and 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

10. The functions of ICT engineering, research science and
modelling are integrated into the design for a response
to an identified problem
Demand for science
based solutions
Supply of science
based solutions
A knowledge-based perspective of linking policy, ICT technologies and agriculture

11. Example of new
modes of
procuring ICT
engineering
research science
and modelling
services
Grains industry

12. The complexity, sources and format of data sources are increasing and require
greater levels of technical governance and specialised forms of investment to
support ICT engineering solutions
Technical
governance
Social
governance
Drones
Satellites
Data monitoring informing decision making
Policy perspective on technology and agriculture

13. Evidence informed policy implies we are moving towards real time, data centric
and modelling based decision support services
Policy perspective on technology and agriculture

14. Deploying policy interventions has a program management context
Example: Resource use innovation strategic action plan
Program
Program
Program
Program
Policy perspective on technology and agriculture

15. A program management framework now
necessarily involves integrating ICT
engineering, modelling and research
science solutions by monitoring headline
indicators
Underpinned by real world monitoring,
space-based data and a flexible spatial
grid
Policy perspective on technology and agriculture

16. Reflective conclusions
Linkages between ICT engineering challenges and policy frameworks
• The opportunities of “big data” and “big data systems”
and ICT design and engineering solutions are real and
rapidly evolving but need to be treated
• The design of engineering solutions infrastructure
follows the design of science based solutions to
problems
• Scientists, particularly numerical modelers and
software engineers 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
Thank you – for further questions contact – richard.vines@ecodev.vic.gov.au
Relationship proximity matters