SDI Convergence - Nederlandse Commissie voor Geodesie - KNAW

As the research progresses more feedback will be sought from key stakeholders and
additional evaluation workshops will be programmed. The focus will not be on what has
been done so far, but to garner ideas and concepts to assist in progressing the development
of the tool.
6. CONCLUSIONS AND
SUMMARY
The MIKE metadata tool shows promise
in assisting the use of Natural Resource Man-
agement
(NRM) models within Victoria, Australia and in providing details of modelling
activities throughout the state. Users have found it easy and efficient as a tool to register
their modelling projects. The entry of the model metadata content describing the
models is proving more cumbersome and future ways to streamline or improve this activity
need to be sought. Although some other groups have demonstrated success in
automating storage of model runs and model run metadata (Steenman-Clark, 2004)
this is usually in the context of more tightly focused modelling at few locations or more
isolated laboratory based modelling and processing systems. In our case the modelling
activity is widely dispersed geographically and is undertaken using a multitude of continually
evolving models. This makes automated approaches difficult to achieve at this
time. With the growing number of digital datasets and models being developed and deployed
it is critical that metadata not just around fundamental datasets, but also around
models such as land use change and impact models be properly developed. Across
the board the development and maturation of standards for models and model metadata
is required, similar to those that have been developed and continue to evolve for
data and data metadata. This will be a crucial step in the evolution of an e-science
framework for supporting knowledge management and collaboration.
Further areas of research will include improving the model metadata schema and col-
laboration
to assist further standardisation of the model metadata content (for improved
search and query). Exploration of the potential to more automatically extract and capture
model metadata and store parameters and data associated with a model instance
is also a next step. However progressing this is a real challenge due to model dispersion,
complexity and variety. More immediate next tasks will be to further improve the
entry and display of the model metadata. In particular there will be a focus on ways to
geographically visualise multiple modelling efforts and temporal views of modelling activity
within landscapes.
ACKNOWLEDGEMENTS
The authors wish to thank the Victorian Department of Industry, Innovation and Re-
gional
Development and the Victorian Department of Primary Industries for funding this
research. Additionally we wish to acknowledge the assistance and support of the Our
Rural Landscapes research program and all our colleagues there-in that have given of
their time and provided such useful and constructive feedback.
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Boughton, W. (2005).
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and Water management, 71: 91-116.
Bridewell, W., Sanchez, J., Langley, P. and Billman, D. (2006). An interactive environment
for the modeling and discovery of scientific
knowledge, International Journal
of Human-Computer Studies, 64(11): 1099-1114.
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