1 Introduction to (Geo)Ontology Barry Smith
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3 natural language labels to make the data cognitively accessible to human beings and algorithmically tractable to computers
4 compare: legends for maps
5 common legends allow (cross-border) integration
6 ontologies are legends for data
7 compare: legends for diagrams
8 legends help human beings use and understand complex representations of reality help human beings create useful complex representations of reality help computers process complex representations of reality
9 computationally tractable legends help human beings find things in very large complex representations of reality
10 maps may be correct by reflecting topology, rather than geometry
11 two kinds of annotations
12 names of types
13 names of instances
14 First basic distinction type vs. instance (science text vs. diary) (human being vs. Tom Cruise)
15 Ontology types Instances
16 Ontology = A Representation of Types
17 An ontology is a representation of types We learn about types in reality from looking at the results of scientific experiments in the form of scientific theories experiments relate to what is particular science describes what is general
18 where in the body ? where in the cell ? what kind of organism ? what kind of disease process ?
19 to yield: distributed accessibility of the data to humans reasoning with the data cumulation for purposes of research incrementality and evolvability integration with clinical data Creating broad-coverage semantic annotation systems for biomedicine
20 The Gene Ontology
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23 The Idea of Common Controlled Vocabularies MouseEcotope GlyProt DiabetInGene GluChem sphingolipid transporter activity
24 The Idea of Common Controlled Vocabularies MouseEcotope GlyProt DiabetInGene GluChem Holliday junction helicase complex
25 what cellular component? what molecular function? what biological process?
26 Michael Ashburner
GEO.OBO biological samples populations, epidemics speciation, evolutionary processes in space and time museum artifacts 27