OWL 2 Examples Franz J Kurfess Computer Science

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OWL 2 Examples Franz J. Kurfess Computer Science Department California Polytechnic State University San

OWL 2 Examples Franz J. Kurfess Computer Science Department California Polytechnic State University San Luis Obispo, CA, U. S. A. Franz Kurfess: Knowledge Retrieval

Overview Methodology ❖ domain ❖critical aspects ❖OWL 2 vs. OWL 1 ❖ Case Studies

Overview Methodology ❖ domain ❖critical aspects ❖OWL 2 vs. OWL 1 ❖ Case Studies ❖ Family History Knowledge Base ❖ Franz Kurfess: Knowledge Retrieval 2

Domains 1 biology ❖ biomedicine ❖bioinformatics ❖ chemistry ❖ molecular interaction ❖ genealogy ❖geography

Domains 1 biology ❖ biomedicine ❖bioinformatics ❖ chemistry ❖ molecular interaction ❖ genealogy ❖geography ❖ GIS ❖ Franz Kurfess: Knowledge Retrieval 3

Domains 2 laws ❖product design ❖reasoning ❖ argumentation ❖case-based reasoning ❖ services ❖ Web

Domains 2 laws ❖product design ❖reasoning ❖ argumentation ❖case-based reasoning ❖ services ❖ Web services ❖ software engineering ❖ Franz Kurfess: Knowledge Retrieval 4

Critical Aspects open world vs closed world ❖ OWL has an open world semantics

Critical Aspects open world vs closed world ❖ OWL has an open world semantics ❖logic programming typically uses closed world semantics ❖ performance ❖ Lehigh University Benchmark (LUBM) ❖ Franz Kurfess: Knowledge Retrieval 5

Family History interesting relationships ❖ complex ❖deterministic ❖ excellent opportunities for inferencing ❖ most

Family History interesting relationships ❖ complex ❖deterministic ❖ excellent opportunities for inferencing ❖ most relationships can be inferred from asserted facts ❖ e. g. motherhood, fatherhood, gender as a basic set ❖ widely known domain ❖ everybody has family relationships ❖ Franz Kurfess: Knowledge Retrieval 6

Specification of Family Relationships two extremes ❖ fact-centric ❖relationship-centric ❖ specified in a Family

Specification of Family Relationships two extremes ❖ fact-centric ❖relationship-centric ❖ specified in a Family History Knowledge Base (FHKB) ❖ Franz Kurfess: Knowledge Retrieval 7

Fact-Centric most knowledge is represented via facts ❖limited set of basic relationships ❖ motherhood,

Fact-Centric most knowledge is represented via facts ❖limited set of basic relationships ❖ motherhood, fatherhood, gender ❖ all other relationships are inferred ❖minimalistic design ❖lower memory requirements ❖higher computational requirements ❖ can be reduced by pre-computing frequently used relationships ❖ increases space requirements ❖ easy maintenance ❖ Franz Kurfess: Knowledge Retrieval 8

Relationship-Centric knowledge about relationships is made explicit ❖ sister (jane, John) ❖ often more

Relationship-Centric knowledge about relationships is made explicit ❖ sister (jane, John) ❖ often more convenient to capture knowledge ❖more difficult to maintain ❖ addition or modification of knowledge may lead to inconsistencies ❖ higher space requirements ❖often lower computational requirements ❖ may require complex rules to infer new relationships from existing ones ❖ Franz Kurfess: Knowledge Retrieval 9

Family Relationships and OWL 2 interesting OWL 2 features ❖ sub-property chains ❖ “an

Family Relationships and OWL 2 interesting OWL 2 features ❖ sub-property chains ❖ “an uncle is the brother of one of my parents” ❖well suited for fact-centric design ❖ ❖ most family relationships can be inferred via chains of properties Franz Kurfess: Knowledge Retrieval 10

FHKB TBox primitive classes ❖defined classes ❖asserted relationships ❖inferred relationships ❖property hierarchy ❖ Franz

FHKB TBox primitive classes ❖defined classes ❖asserted relationships ❖inferred relationships ❖property hierarchy ❖ Franz Kurfess: Knowledge Retrieval 11

Primitive Classes Domain. Entity ❖ Person ❖Sex ❖ Male ❖Female ❖has. Sex relationship is

Primitive Classes Domain. Entity ❖ Person ❖Sex ❖ Male ❖Female ❖has. Sex relationship is functional ❖ ❖ the result of applying it to a person is a single value Franz Kurfess: Knowledge Retrieval 12

Defined Classes Man ❖ Person Has. Sex SOME Male ❖ Woman ❖ Person Has.

Defined Classes Man ❖ Person Has. Sex SOME Male ❖ Woman ❖ Person Has. Sex Female ❖ both Man and Woman classes are used as domain and range constraints in the property hierarchy ❖other classes are also defined, but these are the most important ones ❖ Franz Kurfess: Knowledge Retrieval 13

Asserted Relationships parentage ❖ parent. Of subsumes ❖ father. Of ❖mather. Of ❖both relations

Asserted Relationships parentage ❖ parent. Of subsumes ❖ father. Of ❖mather. Of ❖both relations are functional ❖ a person can have only one mother and only one father ❖does not include stepfather/stepmother and similar relationships ❖ gender can be inferred from domain and range constraints of Man and Woman ❖ Franz Kurfess: Knowledge Retrieval 14

Inferred Relationships all other kin relationships are inferred via properties ❖ emphasis on “core”

Inferred Relationships all other kin relationships are inferred via properties ❖ emphasis on “core” relationships ❖ sibling, sister brother ❖half-sibling ❖uncle, aunt ❖cousin ❖ ❖ first, second, third niece, nephew ❖grandparent, grandmother, grandfather ❖ancestor ❖ can be extended to other relationships ❖ those based on marriage ❖ ❖ possibly including multiple marriages, divorce, step-parents Franz Kurfess: Knowledge Retrieval 15

Property Hierarchy hasrelation ❖ ancestor. Of ❖ parent. Of ❖ father. Of ❖mother. Of

Property Hierarchy hasrelation ❖ ancestor. Of ❖ parent. Of ❖ father. Of ❖mother. Of ❖ sibling. Of ❖ brother. Of ❖sister. Of ❖ Franz Kurfess: Knowledge Retrieval 16

Interesting Relations - Ancestors ancestor. Of ❖ subsumes parent. Of ❖transitive property ❖can be

Interesting Relations - Ancestors ancestor. Of ❖ subsumes parent. Of ❖transitive property ❖can be derived from parent. Of ❖ descendant. Of ❖ inverse of ancestor. Of ❖ parent. Of ❖ subsumes father. Of, mother. Of ❖not transitive ❖implies ancestor. Of ❖domain and range constraints for Man and Woman allow the gender to be inferred ❖ Franz Kurfess: Knowledge Retrieval 17

Interesting Relations - Siblings sibling. Of ❖ transitive ❖symmetric ❖irreflexive ❖ prevents a person

Interesting Relations - Siblings sibling. Of ❖ transitive ❖symmetric ❖irreflexive ❖ prevents a person from being their own brother/sister ❖unclear if this is possible in OWL 2 ❖ subsumes brother. Of, sister. Of ❖ not transitive, symmetric due to gender specificity ❖ brother. Of(Jack, Jane) and brother. Of (Jack, Jill) does not infer brother. Of(Jane, Jill) ❖brother. Of(Jack, Jane) does not infer brother. Of(Jane, Jack) ❖ Franz Kurfess: Knowledge Retrieval 18

Interesting Relations Uncles and Aunts inferred via sub-property chains ❖ uncle. Of ❖ brother.

Interesting Relations Uncles and Aunts inferred via sub-property chains ❖ uncle. Of ❖ brother. Of º parent. Of ❖distinction between blood relations and marriage relations ❖ aunt. Of ❖ sister. Of º parent. Of ❖ great. Uncle. Of, great. Aunt. Of ❖ has. Parent º has. Uncle, has. Parent º has. Aunt ❖ Franz Kurfess: Knowledge Retrieval 19

Interesting Relations - Cousins first. Cousin. Of ❖ has. Parent º sibling. Of º

Interesting Relations - Cousins first. Cousin. Of ❖ has. Parent º sibling. Of º parent. Of ❖ children of my parents siblings ❖share a grandparent, but not parents: siblings are not cousins ❖ higher-degree cousins can be built in a similar manner ❖ second cousins share a great-grandparent, but not grandparents ❖third cousins share a great-grandparent, but not great-grandparents ❖ “removed” cousins ❖ refers to generational gaps ❖ Franz Kurfess: Knowledge Retrieval first. Cousin. Of º parent. Of implies first. Cousin. Once. Removed. Of ❖ 20

Interesting Relations - Grandparents has. Grandparent subsumes ❖ has. Grandfather, has. Grandmother ❖allows gender-neutral

Interesting Relations - Grandparents has. Grandparent subsumes ❖ has. Grandfather, has. Grandmother ❖allows gender-neutral grand- and great- relationships ❖ has. Grandfather ❖ has. Parent º has. Father ❖ has. Grandmother ❖ has. Parent º has. Mother ❖ has. Great. Grandfather ❖ has. Parent º has. Grand. Father ❖ has. Great. Grandmother ❖ has. Parent º has. Grand. Mother ❖ Franz Kurfess: Knowledge Retrieval 21

OWLViz View Franz Kurfess: Knowledge Retrieval 22

OWLViz View Franz Kurfess: Knowledge Retrieval 22

Problems and Limitations irreflexive property ❖gender issues ❖half-siblings ❖ Franz Kurfess: Knowledge Retrieval 23

Problems and Limitations irreflexive property ❖gender issues ❖half-siblings ❖ Franz Kurfess: Knowledge Retrieval 23

Irreflexive Property required for some relationships ❖ sibling. Of needs to be irreflexive to

Irreflexive Property required for some relationships ❖ sibling. Of needs to be irreflexive to prevent a person from being their own sibling ❖ lack of it ❖ may yield incorrect entailments ❖leads to additional inferences ❖ Franz Kurfess: Knowledge Retrieval 24

Gender Issues more complex inferences about gender ❖ sibling. Of(John, David) and Man(David) ❖should

Gender Issues more complex inferences about gender ❖ sibling. Of(John, David) and Man(David) ❖should imply brother. Of(John, David) ❖has. Brother(John, David) can be inferred, but not brother. Of(John, David) ❖a workaround may exist, but may require OWL 2 full ❖ Franz Kurfess: Knowledge Retrieval 25

Half-Siblings two parents in common between two male individuals allows brother. Of to be

Half-Siblings two parents in common between two male individuals allows brother. Of to be inferred ❖if only one parent is in common, half. Brother. Of should be inferred ❖ Franz Kurfess: Knowledge Retrieval 26

Marriage the current version of the FHKB does not contain information about marriage ❖

Marriage the current version of the FHKB does not contain information about marriage ❖ no in-law relationships ❖ Franz Kurfess: Knowledge Retrieval 27

Rules and OWL all the above relationships are defined without rules ❖rules allow further

Rules and OWL all the above relationships are defined without rules ❖rules allow further inferences ❖ may also simplify dealing with some that can currently be made, but are computationally expensive, or difficult to specify ❖ Franz Kurfess: Knowledge Retrieval 28

OWL 2 in Biomedicine Biomedical Knowledge Base Extracted from the GENIA Corpus ❖ 2000

OWL 2 in Biomedicine Biomedical Knowledge Base Extracted from the GENIA Corpus ❖ 2000 annotated abstracts from the MEDLINE database ❖query “transcription factors in human blood cells” ❖ knowledge base (KB) that includes ❖ a more comprehensive taxonomy of categories, ❖relationships between biological entities, ❖hierarchy of relationships ❖ Franz Kurfess: Knowledge Retrieval 29

Bibliography • • • • • [Bechhofer et al. , 2008] Bechhofer, S. ,

Bibliography • • • • • [Bechhofer et al. , 2008] Bechhofer, S. , Hauswirth, M. , Ho�mann, J. , and Koubarakis, M. , editors (2008). The Semantic Web: Research and Applications, 5 th European Semantic Web Conference, ESWC 2008, Tenerife, Canary Islands, Spain, June 1 -5, 2008, Proceedings, volume 5021 of Lecture Notes in Computer Science. Springer. [Besnard et al. , 2008] Besnard, P. , Doutre, S. , and Hunter, A. , editors (2008). Computational Models of Argument: Proceedings of COMMA 2008, Toulouse, France, May 28 -30, 2008, volume 172 of Frontiers in Artificial Intel ligence and Applications. IOS Press. [de Freitas et al. , 2008] de Freitas, F. L. G. , Stuckenschmidt, H. , Pinto, H. S. , Malucelli, A. , and Corcho, ´ O. , editors (2008). Proceedings of the 3 rd Workshop on Ontologies and their Applications, Salvador, Bahia, Brazil, October 26, 2008, volume 427 of CEUR Workshop Proceedings. CEUR-WS. org. [Dolbear et al. , 2009] Dolbear, C. , Ruttenberg, A. , and Sattler, U. , editors (2009). Proceedings of the Fifth OWLED Workshop on OWL: Experiences and Directions, col located with the 7 th International Semantic Web Conference (ISWC-2008), Karlsruhe, Germany, October 26 -27, 2008, volume 432 of CEUR Workshop Proceedings. CEUR-WS. org. [Ganascia and Gan¸ carski, 2009] Ganascia, J. -G. and Gan¸carski, P. , editors (2009). Extraction et gestion des connaissances (EGC’ 2009), Actes, Strasbourg, 27 au 30 janvier 2009, volume RNTI-E-15 of Revue des Nouvel les Technologies de l’Information. C´epadu`es- ´ Editions. [Garcia-Castro et al. , 2008] Garcia-Castro, R. , G´omez-P´erez, A. , Petrie, C. J. , Valle, E. D. , K¨ uster, U. , Zaremba, M. , and Shafiq, M. O. , editors (2008). Proceedings of the 6 th International Workshop on Evaluation of Ontology-based Tools and the Semantic Web Service Chal lenge (EON-SWSC-2008), Tenerife, Spain, June 1 -2, 2008, volume 359 of CEUR Workshop Proceedings. CEUR-WS. org. [Grau et al. , 2008] Grau, B. , Horrocks, I. , Motik, B. , Parsia, B. , Patel-Schneider, P. , and Sattler, U. (2008). Owl 2: The next step for owl. Web Semantics: Science, Services and Agents on the World Wide Web. [Graves, 2008] Graves, H. (2008). Representing product designs using a description graph extension to owl 2. In [Dolbear et al. , 2009]. [Hoekstra and Breuker, 2008] Hoekstra, R. and Breuker, J. (2008). Polishing diamonds in owl 2. In Gangemi, A. and Euzenat, J. , editors, EKAW, volume 5268 of Lecture Notes in Computer Science, pages 64– 73. Springer. [Horrocks, 2008] Horrocks, I. (2008). Ontologies and the semantic web. Commun. ACM, 51(12): 58– 67. [Lacy et al. , 2005] Lacy, L. , Aviles, G. , Fraser, K. , Gerber, W. , Mulvehill, A. M. , and Gaskill, R. (2005). Experiences using owl in military applications. In Grau, B. C. , Horrocks, I. , Parsia, B. , and Patel- Schneider, P. F. , editors, OWLED, volume 188 of CEUR Workshop Proceedings. CEUR-WS. org. [Moreira and Musen, 2007] Moreira, D. A. and Musen, M. A. (2007). Obo to owl: a protege owl tab to read/save obo ontologies. Bioinformatics, 23(14): 1868– 1870. [Rak et al. , 2008] Rak, R. , Kurgan, L. A. , and Reformat, M. (2008). Use of owl 2 to facilitate a biomedical knowledge base extracted from the genia corpus. In [Dolbear et al. , 2009]. [Rector et al. , 2004] Rector, A. , Drummond, N. , Horridge, M. , Rogers, J. , Knublauch, H. , Stevens, R. , Wang, H. , and Wroe, C. (2004). Owl pizzas: Practical experience of teaching owl-dl: Common errors & common patterns. pages 63– 81. [Sheth et al. , 2008] Sheth, A. P. , Staab, S. , Dean, M. , Paolucci, M. , Maynard, D. , Finin, T. W. , and Thirunarayan, K. , editors (2008). The Semantic Web - ISWC 2008, 7 th International Semantic Web Conference, ISWC 2008, Karlsruhe, Germany, October 26 -30, 2008. Proceedings, volume 5318 of Lecture Notes in Computer Science. Springer. [Shvaiko et al. , 2008] Shvaiko, P. , Euzenat, J. , Giunchiglia, F. , and Stuckenschmidt, H. , editors (2008). Proceedings of the 3 rd International Workshop on Ontology Matching (OM-2008) Col located with the 7 th International Semantic Web Conference (ISWC-2008), Karlsruhe, Germany, October 26, 2008, volume 431 of CEUR Workshop Proceedings. CEUR-WS. org. [Stevens and Stevens, 2008] Stevens, R. and Stevens, M. (2008). A family history knowledge base using owl 2. In [Dolbear et al. , 2009]. [van de Ven et al. , 2008] van de Ven, S. , Hoekstra, R. , Breuker, J. , Wortel, L. , and El-Ali, A. (2008). Judging amy: Automated legal assessment using owl 2. In [Dolbear et al. , 2009]. Franz Kurfess: Knowledge Retrieval 30

Resources The Open Biomedical Ontologies ❖ http: //obofoundry. org/ ❖ OBO Download Matrix ❖

Resources The Open Biomedical Ontologies ❖ http: //obofoundry. org/ ❖ OBO Download Matrix ❖ http: //www. berkeleybop. org/ontologies/ ❖OWL ontologies ❖ http: //www. berkeleybop. org/ontologies/owl/ ❖ Franz Kurfess: Knowledge Retrieval 31