Difference between revisions of "KB build process"
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SubClassOf: <col_10> and (inheres_in some (<col_4> and (<col_6> some <col_8>))) and (towards some (<col_13> and (<col_15> some <col_17>)))
SubClassOf: <col_10> and
(inheres_in some (<col_4> and (<col_6> some <col_8>))) and
(towards some (<col_13> and (<col_15> some <col_17>)))
Revision as of 19:46, 13 March 2014
Still being fleshed out
The Phenoscape KB build process goes through several steps in converting input data sources to a queryable knowledgebase. This page provides some description for each of the steps, most or all of which are implemented in the phenoscape-owl-tools project.
- 1 OWL conversion
- 2 Identifier cleanup
- 3 Axiom generation
- 4 Materialization of inferred axioms
- 5 Assertion of absence hierarchy
The Phenoscape Knowledgebase works as a single unified OWL model. While some inputs (e.g. the shared ontologies such as Uberon and PATO) are natively distributed as OWL documents, others are converted to OWL from some other representation. In doing so the inputs are, as far as possible, converted to a shared data model. EQ annotations are converted to a specific semantic representation.
- ZFIN phenotype annotations are provided at their data download site. We translate each row into a phenotype instance: an individual instance of some PATO quality. Here are the column headers from the ZFIN website, followed by representative OWL syntax (referencing column numbers where actual URI values would be, and somewhat casual with other identifiers):
|ID||Gene Symbol||Gene ID||Affected Structure or Process 1 subterm ID||Affected Structure or Process 1 subterm Name||Post-composed Relationship ID||Post-composed Relationship Name||Affected Structure or Process 1 superterm ID||Affected Structure or Process 1 superterm Name||Phenotype Keyword ID||Phenotype Keyword Name||Phenotype Tag||Affected Structure or Process 2 subterm ID||Affected Structure or Process 2 subterm name||Post-composed Relationship (rel) ID||Post-composed Relationship (rel) Name||Affected Structure or Process 2 superterm ID||Affected Structure or Process 2 superterm name||Genotype ID||Genotype Display Name||Knockdown Reagent ID||Start Stage ID||End Stage ID||Genotype Environment ID||Publication ID||Figure ID|
Individual: <uuid_1> Types: ps:AnnotatedPhenotype, <uuid_2> Facts: ps:associated_with_gene <col_3>, ps:associated_with_taxon NCBITaxon:zebrafish, dc:source <col_26> Class: <uuid_2> SubClassOf: <col_10> and (inheres_in some (<col_4> and (<col_6> some <col_8>))) and (towards some (<col_13> and (<col_15> some <col_17>)))
- Annotations from other MODs are similarly structured; however some such as MGI use precoordinated phenotype classes instead of an EQ template. In that case, the phenotype instance is simply an instance of the stated MP phenotype term.
Several common OWL properties (part_of, has_part, develops_from, etc.) are conceptually shared across ontology and annotation resources, facilitating data integration. However, unlike class identifiers, identifiers for properties are often not standardized and they may not properly reference shared terms (usually because of poor tool support rather than user intent). We maintain a table of "alternative" URIs for common properties as we observe them in our data inputs. We could create equivalence axioms between these, but instead we just standardize all incoming content. This saves the reasoner some work and also makes it much easier to query across data using standard URIs, especially when not using a reasoner.
"Absence" classes for OWL EL negation classification workaround
We model absence phenotypes as an instance of the quality lacks all parts of type which inheres_in the whole organism and is towards a type, the class of structure that is absent, i.e.
towards value X. This approach allows us to have a phenotype class for the condition, but directly using a class as a property value in this way is outside of DL reasoning. So to classify our absence phenotypes, we also add an equivalence to
not (has_part some X). TODO—this should probably be
inheres_in some (not (has_part some X)). Because we are confined to using the ELK reasoner (for scalability reasons) class expressions using
not, which is excluded from OWL EL, will still not be classified. For this reason we must pregenerate an "absence" phenotype for each known anatomical structure. These generated classes are named in a standardized way so that they can be arranged into a hierarchy by the "Negation Hierarchy Asserter" (below).
For more on modeling of absence phenotypes, see Absence Phenotypes in OWL.
SPARQL facilitation (e.g. materialized existential hierarchies such as part_of)
"EQ character" classes: combinations of anatomical entities and PATO attribute terms
Materialization of inferred axioms
ELK reasoner using extracted tbox axioms only (not feasible with individuals included).
Assertion of absence hierarchy
Based on inverse of hierarchy of negated classes computed by ELK.