reasoning the fma ontologies with trowl jeff z. pan, yuan ren, nophadol jekjantuk, and jhonatan...
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![Page 1: Reasoning the FMA Ontologies with TrOWL Jeff Z. Pan, Yuan Ren, Nophadol Jekjantuk, and Jhonatan Garcia University of Aberdeen, UK ORE2013](https://reader035.vdocuments.site/reader035/viewer/2022072011/56649e365503460f94b26750/html5/thumbnails/1.jpg)
Reasoning the FMA Ontologies with TrOWL
Jeff Z. Pan, Yuan Ren, Nophadol Jekjantuk, and Jhonatan Garcia
University of Aberdeen, UKORE2013
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The FMA ontology• The Foundational Model of Anatomy ontology is “an evolving computer-based
knowledge source for biomedical informatics”– Developed with Protégé as a FRAME-BASED system– Consists of several components such as Metaknowledge– Evolves (latest version released in 2010)– Highly expressive
• Several OWL translations– DLR and FullR: OWL DL/FULL versions without/with metamodelling– Constitutional: alternative OWL DL translation with metamodelling– OWL2G_noMTC: OWL2 translation from FAM 3.0 without metamodelling– DLR_M1/M2: portion of DLR enriched with the class-based approach (Glimm et al., 2010)
to accommodate metaclasses
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TrOWL: Tractable reasoning infrastructure for OWL 2
• Semantic Approximation (AAAI2007)– Pre-compute and compile the materialisation of OWL 2 ontologies in OWL 2
QL– Sound and complete for conjunctive queries without non-distinguished
variables– Tractable in run-time
• Syntactic Approximation (AAAI2010)– Normalise OWL 2 axioms into nominal-safe EL++ with additional data
structures to maintain non-EL semantics– Approximate deduction on the normalisation results– Sound, incomplete but practically high recall for many ontologies– Tractable TBox classification and ABox materialisation
• Oracle 11g support, SPARQL 1.1 query answering (leveraging OWL-BGP), local closed world reasoning, Jena API, etc.
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Syntactic Approximation• Normalisation
– Representing non-EL expressions with fresh names
– Maintain complementary relations
• Deduction– CEL rules– Additional rules
• E.g. A subClassOf B => not B subClassOf not A
• Example ontology:– A subClassOf forall r B– forall r C subClassOf D– B subClassOf C– =>– A subClassOf D
ALL
r B
A
C
ALLD
Some
r nB
A
nC
Some D
B C
X1 X2
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Metamodelling in FMA Ontology• FMA frame-based ontology contains metamodelling
– E.g. Physical_anatomical_entity instanceOf Anatomical_entity_template– Physical_anatomical_entity subClassOf Anatomical_entity
• Different implementations in OWL ontologies– FMA FullR uses OWL Full;– FMA Consititutional encodes metaclass assertions with class
subsumptions, metaproperty assertions with existential and universal restrictions;
– OWL 2 DL with punning semantics• A class and an individual with same IRI will still be treated as different entities,
leading to incomplete results
– OWL 2 DL with class-based approach• Introducing representative individual of each concept• Encoding subsumptions/class assertions with object property relations
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Evaluation Results
• FMA ontologies are in general very difficult to reason with– Especially with Metamodelling involved
• TrOWL performs generally well on FMA ontologies– Generally faster than fully-fledged, universal, intractable
reasoners;– The only one to classify FMA-OWL2G_noMTC TBox in 1 hour;– Practically high recall
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Dealing with Unsatisfiable Concepts
• Translated versions of FMA contain many unsatisfiabilities– FMA Constitutional: 33,433 / 41,648– FMA OWL2G_noMTC: 67,771 / 85,005
• Investigating such unsatisfiabilities is difficult– Hard to compute justifications
• Requires a lot of entailment checkings
– Too many unsatisfiability to look into• We want to get into the core of the problem
efficiently
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Just. (A subClassOf Bot)
Finding the Core Unsatisfiabilities• Kalyanpur et al.’s root and derived unsatisfiable concepts
– B is parent of A– A is derived– Non-derived unsatisfiable concept is root
• A derived concept can have alternative justification that contains no parent– Eliminating all root concepts do not necessarily eliminate all unsatisfiability
• Still need to compute justifications and entailment checkings
Just. (B subClassOf Bot)
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Finding the Core Unsatisfiabilities• Type I and Type II unsatisfiable concepts
– Purely based on the derivation relations between axioms– Suitable with a forward-chaining completion-based algorithm
• Type I concepts are full-unsatisfiable in reasoning• Type II concepts are semi-unsatisfiable in reasoning
– not immediately subsumed by all concepts– propagates Type II– Can become Type I if appropriate inference occurs
axiom1
axiom2
axiom3
A subClassOf Bot
B subClassOf Bot
Type I
Type IIType I and
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Application on FMAs
• Repairing the Type I concepts will resolve all existing unsatisfiabilities– From TrOWL’s perspective
• Fewer enough Type I makes debugging much easier– E.g. 145 Type I in FMA Constitutional, only 0.43%
of all the unsatisfiable concepts; 6 axioms directly involved, out of the 122,136 logical axioms
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Summary and Future Work• TrOWL and its syntactic approximation facility is well suited for the reasoning,
metamodelling and debugging of the FMA ontologies– Striking a balance among expressiveness, performance and quality
• Future works– A completeness-guarantee?
• Why does TrOWL have high recalls on certain ontologies?• A potential tractable DL that covers FMA family?
– A fully-fledged completion-based reasoner for OWL2 DL?• Will be intractable
– Parallelisation?• Changing CEL rules to ELK rules?• Parallelising the additional approximate deduction rules
– Improved entailment checking• Currently using the dual-ontology classification algorithm from CEL• Changing to a goal-driven algorithm?