The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real world instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. We present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.

1. A P ractical O ntology for the L arge- S cale M odeling of S cholarly A rtifacts and their U sage Marko A. Rodriguez (1) Johan Bollen Herbert Van de Sompel Digital Library Research & Prototyping Team Los Alamos National Laboratory - Research Library (1) [email_address] Acknowledgements: Lyudmila L. Balakireva (LANL), Wenzhong Zhao (LANL) , Aric Hagberg (LANL) MESUR is supported by the Andrew W. Mellon Foundation.

2. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

3. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

9. What is the Purpose of an Ontology?

10. The MESUR Data Flow

11. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

13. RDF, RDFS ex:marko ex:cookie ex:Human ex:Food ex:isEating rdf:type rdf:type ex:isEating rdfs:domain rdfs:range ontology instance

14. RDF, RDFS, OWL ex:fluffy ex:marko ex:Pet ex:Human ex:hasOwner rdf:type rdf:type ex:hasOwner rdfs:domain rdfs:range ontology instance _:0123 rdfs:subClassOf owl:onProperty “ 1” owl:maxCardinality ex:bob ex:hasOwner owl:Restriction rdf:type

16. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

18. Relational Database & Triple Store

19. The MESUR Class Hierarchy

20. The Context Classes Inspired by OntologyX: http://www.ontologyx.com

21. The Publishes Context

22. The Uses Context

23. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

25. Journal Citation and Usage

26. Calculating the 2007 Impact Factor SELECT ?x WHERE ( ?x rdf:type mesur:Citation ) ( ?x mesur:hasSource ?a) ( ?x mesur:hasSink urn:issn:0028-0836 ) ( ?x mesur:hasSourceTime ?u) AND (?u == 2007) ( ?x mesur:hasSinkTime ?t) AND (?t > 2004 AND ?t < 2007) SELECT ?y WHERE ( ?y rdf:type mesur:Publishes ) ( ?y mesur:hasGroup urn:issn:0028-0836 ) ( ?y mesur:hasTime ?t ) AND (?t > 2004 AND ?t < 2007) INSERT < _123 rdf:type mesur:ImpactFactor > INSERT < _123 mesur:hasObject urn:issn:0028-0836 > INSERT < _123 mesur:hasStartTime 2007 > INSERT < _123 mesur:hasEndTime 2007 > INSERT < _123 mesur:hasNumbericValue (COUNT(?x) / COUNT(?y)) > The 2007 impact factor of journal A is the total number of citations to articles published in A in 2005 and 2006 from articles published in 2007 in journal B divided by the total number of articles published by journal A in 2005 and 2006.

27. Calculating the 2007 Usage Impact Factor SELECT ?x WHERE ( ?x rdf:type mesur:Uses ) ( ?x mesur:hasUnit ?a ) ( ?x mesur:hasGroup ?b ) ( ?b mesur:partOf urn:issn:1082-9873 ) ( ?x mesur:hasTime ?t ) AND (?t == 2007) ( ?y rdf:type mesur:Publishes ) ( ?y mesur:hasUnit ?a ) ( ?y mesur:hasTime ?u ) AND (?u > 2004 AND ?u < 2007) SELECT ?y WHERE ( ?y rdf:type mesur:Publishes ) ( ?y mesur:hasGroup ?a ) ( ?a mesur:partOf urn:issn:1082-9873 ) ( ?y mesur:hasTime ?t ) AND (?t > 2004 AND ?t < 2007) INSERT < _123 rdf:type mesur:UsageImpactFactor > INSERT < _123 mesur:hasObject urn:issn:1082-9873 > INSERT < _123 mesur:hasStartTime 2007 > INSERT < _123 mesur:hasEndTime 2007 > INSERT < _123 mesur:hasNumbericValue (COUNT(?x) / COUNT(?y)) > The 2007 usage impact factor of journal A is the total number of 2007 usage events of articles published in A in 2005 and 2006 divided by the total number of articles published by journal A in 2005 and 2006.

28. Overview The MESUR project A quick RDF/RDFS/OWL tutorial Modeling the scholarly community Practical applications of the model Conclusion

31. Questions MESUR is at http://www.mesur.org MESUR ontology is at http://www.mesur.org/schemas/2007-01/mesur/ Many thanks to the Andrew W. Mellon Foundation for their support