Notes

Slide Show

Outline

1	Integrating Knowledge Representation into GIS: An Example from Minerals Exploration
2	Representations of Human Knowledge as Networks: Geneology Example (Smith-Jones, 1890)
3	Computer Representations of Human Knowledge As Networks: Biology (Yodzis, 1995)
4	Computer Representations of Mineral Deposits Knowledge as “Semantic Networks”: (Smyth (2001) from Cox and Singer (1986))
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7	Tabular (Relational) Computer Data can be converted to Semantic Networks for Representation of Sophisticated “Knowledge”
8	The Knowledge Engineering (KE) Approach
9	CLASSES (No Relational Equivalent)
10	The BGS RCS is a Taxonomy
11	Hetero-Hierarchy (~ Partonomy)
12	Standards: Ontology development requires concept models, which often include taxonomies and partonomies.
13	Study Area
14	Bedrock Geology:
15	Geochemistry:
16	Lithology-specific Anomaly Thresholds
17	Analysis-specific Anomaly Thresholds
18	Mineral Deposit Models: Porphyry Co ± Mo ± Au
19	Workflow #1
20	Workflow #2
21	Workflow #3
22	Workflow #4
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36	In conclusion ….. “Geologists owe it to themselves and to workers in other sciences to use standard nomenclature.” R. B. Travis Preface to “Classification of Rocks”, Quarterly of the Colorado School of Mines, Volume 50, Number 1, (1955)
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38	Successful Standards For standards to succeed, their adoption has to be a rewarding experience for their users.
39	"“Geologists owe it to..." “Geologists owe it to themselves and to workers in other sciences to use standard nomenclature.” R. B. Travis Preface to “Classification of Rocks”, Quarterly of the Colorado School of Mines, Volume 50, Number 1, (1955)