1 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Stuart Aitken Artificial Intelligence Applications Institute A Process Ontology for Cell Biology

2 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Outline Rapid Knowledge Formation (RKF) Project –RKF Project goals and domain –The Cyc knowledge based-system –RKF Tools Process Ontology –General approach –Formalisation –Example

3 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Rapid Knowledge Formation The RKF project aims to develop tools which will allow domain experts to enter knowledge directly into the KBS. DARPA-funded, two teams: –CYCORP –SRI Organised around ‘Challenge Problems’ – Cell Biology

4 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications RKF Aim: To enable biologists to construct an ontology/KB from a textbook source formalise Ontology Alberts et al, Essential Cell Biology, 1998

5 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Rapid Knowledge Formation Key techniques: The KBS has knowledge of the KA process –Knowledge of salience –Knowledge of the requirements of an adequate formalisation There is a dialogue between expert and system, which clarifies the concept being defined.

6 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Rapid Knowledge Formation Evaluation: After a period of tool development, trials are organised, both expert performance, and KE performance is measured, and assessed independently. The evaluation is extensive – over a period of 2 weeks

7 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications The Cyc KBS Cyc (Doug Lenat) is a knowledge- based system, under development since ~1984, aiming to represent common sense knowledge. Cyc uses a large upper-level ontology Uses a logical language based on first-order logic

8 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications The Cyc KBS Concepts in the Upper Ontology: –Thing, Agent, Event –TangibleThing, InformationBearingObject –…. Dog, Book –subclass(genls), instance-of(isa) –parts, subevent, role predicates –1600 concepts in total in the public release (1998) - small% of Cyc Classification: –Stuff-like vs Object-like –Individual vs Set

9 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications The Cyc KBS The upper-ontology supports application development: Upper-level Intermediate-level Application-level Thing

10 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications The Cyc KBS Cyc includes: An inference engine, GUI, tools for ontology development. Until the RKF project, ontology development was by trained knowledge engineers, working with domain experts.

11 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications RKF New tools in Cyc: Define a new concept, and place it correctly in the ontology Refine a concept definition Define a new predicate Assert a new fact Define a new rule State an analogy Construct a new process

12 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications RKF User interaction: Selection of items in the interface –Choice determined ‘intelligently’, KBS has knowledge of salience, and the KA process, this knowledge must be authored Browsing of the ontology Search Natural language dialogue

13 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Process Models BindsTogetherMove RNA Transcription

14 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Process Descriptor Q: Name the process A: [ RNA Transcription ] Q:Select the type of Process that describes the category best event localised creation or destruction event… ‘say this:’[ _ _ _ _ _ _ ] Q: Define: affected object: [ _ _ _ _ _ ] location: [ _ _ _ _ _ ] actor: [ _ _ _ _ _ ]

15 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Process Models Describing Processes: Complex expressions at the instance level Simpler to describe in terms of types Upper-level Intermediate-level subevent(Event,Event) doneBy(Event,Agent) ForAll ?E ?F ?G implies (subevent(?E,?G) and isa(?E,BindsTogether) subevent(?F,?G) and isa(?F,Move)) before(startOf(?E),startOf(?F)) Application-level ?

16 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Script Vocabulary The Script theory defines the semantics of Type-Level assertions (typePlaysRoleInScene RNATranscription DNAMolecule BindsTogether objectActedOn) Requires rules for identity –Can require complex reasoning Good for user input Can be extended to cover pre and postconditions of actions

17 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Scripts subevents BindsTogether e Move f RNA Transcription Forall subevents f of t, of type Move, and all subevents e of t, of type BindsTogether, (startsAfterStartingof f e) where t is of type RNATranscription t startsAfterStartingOfInScript

18 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Scripts Type playing role N BindsTogether Nucleotide e Types: objectActedOn Instance: For some n in N, (objectActedOn e n)

19 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications New Script Vocabulary Pre and Post conditions BindsTogether N R N R not touchingDirectly connectedTo (preconditionOfScene-negated BindsTogether touchingDirectly ) (postconditionOfScene BindsTogether connectedTo )

20 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications New Script Vocabulary N R Some ?n in N, some ?r in R (not (touchingDirectly ?n ?r)) Some ?n in N, some ?r in R (connectedTo ?n ?r) BindsTogether Nucleotide Ribonucleotide e Types: role Set of Instances: Precondition: Postcondition: identity

21 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Script Vocabulary The Script vocabulary forms an ‘intermediate level’, which lies behind the Process descriptor GUI (i.e. the textboxes) Not, in itself, a taxonomy of processes, but allows processes to be described in detail. Defining the subclass relation is just one task.

22 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Vaccinia Virus Life Cycle The vaccinia virus life cycle was selected as an example of a complex model to formalise as a set of Scripts. The model includes actions, decomposition, ordering, objects- playing-roles and pre/postconditions It is a good test for the Script vocabulary

23 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Vaccinia Virus Life Cycle mRNATranscription-Early ViralGeneTranslation-Early MovementOfProtein Temporal: mRNATranscription-Early ViralGeneTranslation-Early MovementOfProtein mRNATranscription-Early ViralGeneTranslation-Early MovementOfProtein Participants Conditions: Outputs:messengerRNA Inputs:messengerRNA Pre:spatiallySubsumes Cell VirusCore Post:spatiallySubsumes CellCytoplasm Vitf2

24 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Evaluation 8 biologists were selected, and trained in the tools, 4 per team The knowledge to be formalised was selected (chapter 7 in Alberts) The knowledge base was allowed to contain ‘pump-priming’ knowledge The biologists entered knowledge, using the tools, then tested it against a set of questions, Ontology/KB was revised

25 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Evaluation Results (outline) A huge amount of data was collected, but analysis is complex (IET Inc) Domain experts were able to develop ontologies after ‘light’ training Knowledge engineers out-perform domain experts in ontology construction

26 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications Summary ‘Power Tools’ for ontology development are being implemented and tested in the RKF project. A Script/Process vocabulary has been developed and applied to processes in cell biology, covering: –Temporal order –Participants –Pre/postconditions –Repetition