TermGenie and Shoge

Ontology Generation
Tools
Chris Mungall

Tuesday, May 8, 2012

Exploiting modularity
for ontology generation
• Biology is modular
• Same ‘innovation’ repeated in multiple contexts,
with variation
• E.g. phalanx, arthropod segments
• Repetition = RSI for poor ontology creators
• Logical deﬁnitions and reasoning help automate
classiﬁcation
• Reasoners will not generate terms for you


Some tools
• OBI QuickTerm Templates
• Populous and OPPL
• POPL
• TermGenie
• instant compositional terms for curators
• Shoge
• generate an entire ontology from core rules

TermGenie
• Web based wrapper onto an ontology managed
in a VCS
• Administrator deﬁnes templates
• User (curator or ontology editor) ﬁlls in templates
• TG generates a stable ID and logical axioms plus
textual metadata according to template pattern
• Reasoner checks and places term
• Gatekeeper approves or obsoletes terms


History and
implementation
• TermGenie prototype: released 2010
• prolog implementation
• working prototype: used 2010-2011 for GO
• now retired
• TermGenie v1: released Q4 2011
• Programmer: Heiko Dietze
• java OWLAPI based
• any reasoner (Elk is default)
• jQuery on front-end
• Currently used heavily in GO


TermGenie walk-
through
• This example uses the GO TermGenie config
• http://go.termgenie.org
• GO pre-coordinates a lot of process terms
• e.g. epithelial cell differentiation in kidney development
• TermGenie can be configured for any compositional pattern; e.g
• EQ
• Repeated anatomical structures
• {mucosa,submucosa,...} x {jejunem, iluem,..}
• spatial qualifiers


(we recommend Elk here)

(this inference is fairly trivial, more complex
cases are easily accommodated)

(you can get this far without
even logging in)


(only authorized GO users can get this far)

The term is not committed to cvs/svn
yet, but the ID is reserved


(only authorized GO gatekeepers can access this)


Another example: what happens when
we try to add a term that exists already?


Bulk entry


Discussion
• TermGenie currently only allows terms conforming to rigid pre-deﬁned templates
• In our experience this is a good thing
• Ontology engineering roles and phases
• High level design
• relations
• core repeated terms
• patterns
• small number of domain experts and ontologists
• Implementing the design
• ﬁlling in templates
• curators
• lots of users, need not be trained in ontologies


• TermGenie allows you to selectively “ﬂesh
out” an ontology
• What if you want to seed an ontology from
some basic rules?


Shoge
• Serial Homology Ontology Generation
Engine
• Uses anatomy grammars to
generate
• labels
• logical axioms


Repetition in anatomy
• Simple example:
• limb segments:
• stylopod, zeugopod, autopod
• Each is repeated 4 times
• anterior/posterior
• fore/hind

limbs.shg
grammar(limbs_simple).

limb_segment *--> stylopod | zeugopod | autopod.

stylopod *--> in_limb, @stylopod.
zeugopod *--> in_limb, @zeugopod.
autopod *--> in_limb, @autopod.

in_limb *--> part_of some limb.
limb *--> laterality, anterioposterior, @limb.

laterality *--> @left.
laterality *--> @right.
anterioposterior *--> @anterior.
anterioposterior *--> @posterior.


Generated ontology


Naming rules

'hand' is_name_of anterior limb autopod.
'foot' is_name_of posterior limb autopod.


Digits (human)

:- include(ordinal_series).
anatomical_digit *-->
part_of some limb, @anatomical_digit, in_ordinal_series(1-5).

Together with previous grammar,
this generates 20 digits, such as:
Class: ‘left forelimb digit 1’
EquivalentTo:
digit and part_of some ‘left forelimb’ and has_order value 1


Phalanges and
repetition with
variation
phalanx *--> ?proximality,@phalanx,[of],part_of some anatomical_digit.
proximality *--> @proximal.
proximality *--> @distal.
proximality *--> @medial.

exclude(phalanx and medial and part_of some (anatomical_digit and
has_order value 1)).

Generates 52 leaf node classes


a more EHDAA2
complex
example


:- if(in_context('Homo sapiens')).

somite_number *-->
in_ordinal_series(1-39).

:- endif.
:- if(in_context('Mus')).

Somites
somite_number *-->

:- endif.
:- if(in_context('chick')).

somite_number *-->

:- endif.
:- if(in_context('snake')).

somite_number *-->

:- endif.


somitic_element *--> somite.
somitic_element *--> sclerotome.
somitic_element *--> myotome.
somitic_element *--> dermatome.
somitic_element *--> dermomyotome.

somite *--> @somite,somite_number.
sclerotome *--> @sclerotome,somite_number.
dermatome *--> @dermatome,somite_number.
myotome *--> @myotome,somite_number.
dermomyotome *--> @dermomyotome,somite_number.

about *-->
{develops_from(S1,S2)}, % RULE
somitic_element(S1 and X),[develops,from],somitic_element(S2 and X) % PHRASE
::
S1 and X < develops_from some S2 and X. % AXIOM

% GENERIC RULES
develops_from(dermatome,dermomyotome).
develops_from(myotome,dermomyotome).
develops_from(dermomyotome,somite).
develops_from(sclerotome,somite).


Pre vs post
coordination
• Some people are uncomfortable with
excessive pre-coordination
• Shoge can be used to create a ‘background’
super-pre-coordinated ontology
• align with existing ontologies to check
• curators can mireot in the subsets they

Conclusions
• TermGenie
• extending an ontology and ﬁlling in gaps
• in production use for GO
• easy to make your own templates
• Shoge
• generating an entire ontology module
• powerful but difﬁcult to use (prolog helps)
• in development


TermGenie and Shoge

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