Empirical Knowledge Representation
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DESCRIPTIONEmpirical Knowledge Representation. Enrico Motta Knowledge Media Institute The Open University, UK. Introduction. KR/ Ont.Eng . research traditionally follows a top-down approach - PowerPoint PPT Presentation
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Empirical Knowledge RepresentationEnrico MottaKnowledge Media InstituteThe Open University, UK1As the title says what I want to discuss today is the relationship between the field of knowledge engineering and the semantic web, in particular discussing the extent to which the emergence of a large scale semantic web is changing the way we do knowledge engineeringI will start by reminding everybody about what knowledge engineering is about and then we will take it from there.IntroductionKR/Ont.Eng. research traditionally follows a top-down approachformalisms are designed on the basis of modelling needs and computational considerations; tools and applications based on these formalisms are realizedlittle history of paying attention to usersContrast, e.g., with software engineering, where empirical studies have a long and fine traditionHowever, emergence of large scale web semantics means that engaging with formal representation of knowledge is no longer the preserve of a few samuraisa far larger group of users now publishes, consumes and in general tries to make sense of formal semantic structures.
2A research programmeNeed for a research programme centred on empirical studies of KR and OO, which should foster the construction of an empirical body of evidence about the usability of alternative modelling solutionsmore ambitiously, it should help the discipline to start moving away from a purely top-down paradigm, to include a user-centric research element, consistently with most other engineering disciplines. This goes hand in hand with an emerging recognition in the Ont. Eng. community that from an epistemological point of view there isnt necessarily a unique way of doing things. For instance, alternative design patterns exist for representing time, alternative upper level ontologies exist, etc. Our work is also motivated by the fact that it is not uncommon for authors to make statements about the intuitiveness of different solutions. Hence, there is awareness that user acceptance is indeed valuableHowever, such statements tend to reflect an authors epistemological standpoint, rather than any concrete user experience.
3An empirical study on time representation13 subjects took part in an empirical study, comprising nine different elements, including modelling task(SE1) William Shakespeare was born and baptised in Stratford-upon-Avon in 1564, which at the time had a population of 5000 people. (SE2) In 1582, William Shakespeare, aged 18, married Anne Hathaway, aged 26. (SE3) William Shakespeare bought the Lord Chamberlains Men playing company in London in 1585 paying in cash. (SE4) Richard Burbage was an actor. (SE5) In 1592, William Shakespeare was a family man in Stratford-upon-Avon and an actor in London. (SE6) In 1595, he wrote the plays Richard II, Romeo and Juliet, and A Midsummer Nights Dream. (SE7) In 1597, William Shakespeare decided that he will retire at New Place in 1613. And, by the way: (SE8) in 2007, Michael Phelps surpassed Ian Thorpes world record from 2001. Subjects were given a KR formalism to solve the task with meta-level features but restricted to binary relationsFour patterns for time representation
43D and 3D+13D Pattern (time stamping statements)holdsAt (rel (arg1, arg2), t)
3D ExampleholdsAt (population (France, 55M), 1985)
3D+1 Pattern (slicing relations)rel@t (arg1, arg2)temporalSubpartOf (rel@t, rel)atTime (rel@t, t)
3D+1 Examplepopulation@1985 (France, 55M)temporalSubpartOf (population@1985, population)atTime (population@1985, 1985) 54D slicing individualsPatternrel (arg1@t1, arg2@t2)temporalSubpartOf (arg1@t1, arg1)temporalSubpartOf (arg2@t2, arg2)atTime (arg1@t1, t1)atTime (arg2@t2, t2)
Example: Henry, in 2009, was taller than Boris in 2010, taller (henry@2009, boris@2010)temporalSubpartOf (henry@2009, henry)temporalSubpartOf (boris@2010, boris)atTime (henry@2009, 2009)atTime (boris@2010, 2010)6N-ary patternGeneric solution to represent n-ary relations in formalisms that only support binary relations. The transformation consists of decomposing the n-ary statement in n+1 binary statements, by creating an instance of the relation and then linking this instance to the n arguments of the original statement.
Example: Michael Phelps was born in Towson in 1985
typeOf (birthEvent1, BirthEvent)location (birthEvent1, Towson)atTime (birthEvent1, 1985)subject (birthEvent1, MichaelPhelps)
7Results3D pattern considered as the most user-friendly, in particular by the least experienced users. Hence, it seems unfortunate that, in contrast with other standards, such as KIF and Common Logic Web-KR languages for the Semantic Web only provide rather cumbersome mechanisms for representing statements about statements 3D+1 is more readily used by subjects that have lower levels of skill in KR. Subjects that use the 3D+1 pattern tend to perform less well and take a greater amount of time to complete the modelling tasks.3D+1 and n-ary pattern appear to provide some kind of alternative dominant solutions for representing temporal informationexperts opted for the n-ary pattern possibly on the basis of its superior representational power and degree of flexibility novices opted for 3D+1 possibly on the basis of surface syntactic features (problem solving by imitation)
8Results4D PatternThe 4D pattern is rated as the least intuitive. This confirms the observations about this pattern found in the literature. however, users with a higher level of expertise in KR were in favor of using it for the modelling task, probably as a result of its representational power and flexibility.N-ary PatternMost widely used pattern throughout the modelling task and, particularly, the choice of users with a higher level of expertise. As in the case of 4D, this is likely to be the case because of its generality and flexibility. positive correlation between using this pattern and getting a high score in the modelling task. 9