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Preparing the Way : Creating Future Compatible Cataloguing Data in a Transitional Environment Dean Seeman & Lisa Goddard Memorial University of Newfoundland.

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Presentation on theme: "Preparing the Way : Creating Future Compatible Cataloguing Data in a Transitional Environment Dean Seeman & Lisa Goddard Memorial University of Newfoundland."— Presentation transcript:

1 Preparing the Way : Creating Future Compatible Cataloguing Data in a Transitional Environment Dean Seeman & Lisa Goddard Memorial University of Newfoundland Faster, Smarter, Richer Conference Rome, Italy February 27 th, 2014

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4 Aspects of our Linked Data Future Decentralization Collaboration Localization Richness Structure

5 Indexes eJournals eBooks Digital Archives Research Repositories Data Sets 1. Decentralization

6 Extract, Transform, Load

7 Disparate data sources and incompatible data structures are among the biggest obstacles for 21 st century humanities researchers. (RIN, 2011)

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9 Decentralization Subject -> Predicate -> Object Statements not records.

10 #creator#Shakespeare#Macbeth Decentralization Most data stored remotely.

11 2. Collaboration

12 Collaboration

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15 Enhancing Shared Records

16 Ontology Development Library Related Ontologies RDA Ontology Dublin Core Ontology Bibliographic Ontology (BIBO) Citation (CITO) Provenance Ontology (PROV-O) MODS/MADS FRBR Holding Ontology

17 3. Localization [I]t is their accumulated special collections that increasingly define the uniqueness and character of individual research libraries. - ARL, 2009

18 Expose Entity URIs Annotation

19 4. Richness

20 Define Relationships subjectOf bornIn employs employedBy adaptedFrom published creator setIn annotates subjectOf hostedBy Annotation

21 5. Structure Collaboration Richness Decentralization Localization Structure

22 Structured Data

23 Clothing Apparel Clothes Dress Garments Beauty, Personal Manners & customs Fashion Undressing Aprons Armbands Belt toggles Belts (Clothing) Bodices Breechcloths Burial clothing Buttonholes Buttons Caftans Cloaks Collars Color in clothing Costume Coveralls Darts (Clothing) Dirndls Doll clothes Dresses Footwear Fur garments Garters Headgear Hosiery Jackets Jumpsuits Kilts Kimonos Knitwear Lapels Latex garments Leggings Neckwear Same AsRelated Broader Narrower Semantic Structure

24 Machine-Actionable Data

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26 4 Cataloguer Tasks in Relation to Linked Data WorryPanicWeepResign

27 Trust Standard Development?

28 Collaboration Richness Decentralization Localization Structure

29 The greatest consumer of our data is going to be the machine. We have to make our data machine understandable.

30 Automatic Data Normalization MARC Linked Data Formats

31 Collaboration Richness Decentralization Localization Structure Automatic Data Normalization

32 In computer terms, we have a data normalization problem. Ross Singer

33 Collaboration Richness Decentralization Localization Structure Automatic Data Normalization Manual Data Creation (Cataloguing) Good Data

34 Ochoa, X., & Duval, E. (2009). Automatic Evaluation of Metadata Quality in Digital Repositories, 10(2), 67–91. doi: /s What is Good Data?

35 A Few Markers of Good Data for Data Normalization Discrete Each element asserts a single thing Semantically Unambiguous Data should be clear in its meaning and minimize multiple interpretations Consistent Predictable values

36 Helps us in our current environment Helps the process of data normalization Helps the future … even if it isnt Linked Data This kind of data …

37 Looking at the future what can cataloguers practically do to plug into it?

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39 Authorities & Controlled Access Points

40 Authorities Contain mostly differentiated values Better for machine processing

41 Authorities

42 lc/ es/authorWork /rdf.xml Tom StoppardAuthor of WorkParades End Controlled Access Points (MARC 1xx, 6xx, 7xx) Automatically Normalized / Translated into URIs

43 Better to have this compacted in one statement As opposed to spread throughout the record Controlled Access Points

44 AUTHORIZED UNAUTHORIZED

45 But in our Current Cataloguing Environment, It May Be the Best We Can Do

46 Vocabularies & Differentiated Values

47 Vocabularies Provide Consistent Values for Normalization

48 Already Equipped with URIs

49 Differentiable Values Example: Exercise the option at RDA for place of publication … make the implicit explicit

50 Local

51 Local Catalogue

52 Unique Assertions > Ubiquitous Assertions Future Value

53 Richness Smart Fields and Values Authorities Controlled access points Vocabularies Differentiable values Local Authorities Local & Unique Resources Local Aspects of Ubiquitous Localization

54 Some practices DO NOT prepare us for the future.

55 Trapping Data in Free Text Fields Spread Throughout the Record

56 Addicted to Keystrokes

57 Principle of Common Usage or Practice (RDA ) illustrations instead of ill. pages instead of p. publisher not identified instead of s.n.

58 Addicted to Keystrokes Principle of Representation (RDA ) Increased transcription of text

59 Problems with Keystrokes More Time and Effort Greater Amount of Error (Bad for Normalization) (in case of RDA) Of Unproven User Value

60 I think a good rule of thumb is that if youre having to type data, and you havent been transported back in time, then youre doing it wrong. Richard Cotton, Bad Data Handbook

61 Punctuation We Need To Focus on Values, Not Display

62 LC-PCC PS No 490, no period to end present, 300 field ends in a. Punctuation

63 Local Practice Genre/Form terms in Topical Heading fields (MARC 650) Semantic Ambiguity About Musical Films OR Is a Musical Film?

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65 Focus on... Structure Statements Differentiable Values Vocabularies Authorities Controlled Access Points Local Data Good Data

66 ... and start to focus less on Punctuation Free Text Fields The Data we Cant Easily Normalize The Data Machines Cant Use

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68 Thank you.

69 References Allemang, Dean and James A. Hendler Semantic Web for the Working: Modeling in RDF, RDFS and OWL, 2nd ed. Amsterdam; Boston: Elsevier/Morgan Kaufmann American Research Libraries (ARL). March Special Collections in ARL Libraries: A Discussion Report from the ARL Working Group on Special Collections. Washington, DC:ARL. Bowen, Jennifer B Moving Library Metadata Toward Linked Data: Opportunities Provided by the eXtensible Catalog. International Conference on Dublin Core and Metadata Applications 0 (0) (September 20): 44–59. Cole, Timothy W., Myung-Ja Han, William Fletcher Weathers, and Eric Joyner Library Marc Records Into Linked Open Data: Challenges and Opportunities. Journal of Library Metadata 13 (2-3): 163–96. doi: / Coyle, Karen Library Linked Data, Part I: Introduction to the Semantic Web (Mar. 8, 2011) March 8. Hilliker, Robert J., Melanie Wacker, and Amy L. Nurnberger Improving Discovery of and Access to Digital Repository Contents Using Semantic Web Standards: Columbia Universitys Academic Commons. Journal of Library Metadata 13 (2-3): 80–94. doi: / Kincy, Chamya P., and Michael A. Wood Rethinking Access with RDA (Resource Description and Access). Journal of Electronic Resources in Medical Libraries 9 (1): 13–34. doi: / Lahanas, Stephen. March 9, Understanding The Semantic Value Proposition. Semanticweb.com, semantic-value-proposition_b11492?red=su Lawson, Mark. August 9, Berners-Lee on the read/write web, BBC News. Online Computer Library Centre (OCLC) Perceptions of Libraries, 2010: Context and Community. Dublin,OH:OCLC. Research Information Network. April Reinventing Research? Information Practices in the Humanities. accessing-information-resources/information-use-case-studies-humanities Schreur, Philip Evan The Academy Unbound: Linked Data as Revolution. Library Resources & Technical Services 56 (4) (October 1): 227. Singer, Ross Linked Library Data Now! Journal of Electronic Resources Librarianship 21 (2): 114–126. doi: / Tillett, Barbara B Keeping Libraries Relevant in the Semantic Web with Resource Description and Access (RDA). Serials: The Journal for the Serials Community 24 (3) (November 1): 266–272. doi: / W3C Library Linked Data Incubator Group (W3C) Library Linked Data Incubator Group Final Report. October 5. Welsh, Anne, and Sue Batley Practical Cataloging. AACR, RDA and MARC21. American Library Association. Zeng, Marcia Lei, Karen F. Gracy, and Laurence Skirvin Navigating the Intersection of Library Bibliographic Data and Linked Music Information Sources: A Study of the Identification of Useful Metadata Elements for Interlinking. Journal of Library Metadata 13 (2-3): 254–278. doi: /

70 Image Credits RDA Toolkit RDA Metadata Registry RDA Toolkit ilderness_oil_on_oak_panel_by_Pieter_Brueghel_the_Younger.jpg


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