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Linked data MLA 2015

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Linked data MLA 2015

  1. 1. Linked Data, the Semantic Web, and You Maine Library Association 2015
  2. 2. Linked Data
  3. 3. What is Linked Data Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. URIs - Uniform Resource Identifiers HTTP - Hypertext Transfer Protocol RDF - Resource Description Framework Source: http://linkeddata.org/faq
  4. 4. URIs Uniform Resource Identifier (URI) is a string of characters used to identify the name of a resource. Such identification enables interaction with representations of the resource over a network, typically the World Wide Web, using specific protocols. Uniform Resource Locator (URL) (commonly informally referred to as a web address, although the term is not defined identically) URL (uniform resource locator) is a subset of the URIs that include a network location. Uniform Resource Name (URN) is a subset of URIs that include a name within a given space, but no location. Image Source: http://www.slideshare.net/rodsenra/rest-representational-state-transfer-emc-brdc-internal-tech-talk
  5. 5. HTTP HyperText Transfer Protocol, HTTP is the underlying protocol used by the World Wide Web. HTTP defines how messages are formatted and transmitted, and what actions Web servers and browsers should take in response to various commands.
  6. 6. RDF The Resource Description Framework (RDF) data model represents information as node-and-arc-labeled directed graphs. The data model is designed for the integrated representation of information that originates from multiple sources, is heterogeneously structured, and is represented using different schemata. RDF aims at being employed as a lingua franca, capable of moderating between other data models that are used on the Web. Source: http://linkeddatabook.com/editions/1.0/#htoc16
  7. 7. Graph Database Steven Roman foaf: knows foaf: publications foaf: publications Dragons in the Stacks Cason Snow
  8. 8. RDF - Triples RDF uses triples to describe resources. Triples consist of a Subject, Predicate, and Object. Cason Snow knows Steven Roman. http://www.library.umaine.edu/staff/snow.htm http://xmlns.com/foaf/0.1/knows https://dkpl.org/teens-tweens/
  9. 9. Serialization Remember RDF is not a data format. It is a data model for describing resources. To display RDF data on the Web it must be serialized though some kind of syntax. RDF/XML and RDFa are standardized by the W3C but many other serializations are out there.
  10. 10. RDF/XML example 1 <?xml version="1.0" encoding="UTF-8"?> 2 <rdf:RDF> 3 xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" 4 mlns:foaf="http://xmlns.com/foaf/0.1/"> 5 <foaf:Person> 6 <foaf:name>Cason Snow</foaf:name> 7 <foaf:workplaceHomepage rdf:resource=”http://www.library.umaine.edu/staff/snow.htm”/> 8 <foaf:knows> 9 <foaf:Person> 10 <foaf:name>Steven Roman</foaf:name> 11 <foaf:workplaceHomepage rdf:resource=”https://dkpl.org/teens-tweens/”/> 12 </foaf:Person> 13 </foaf:knows> 14 </foaf:Person> 15 </rdf:RDF>
  11. 11. Turtle (Terse RDF Triple Language) example @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . a foaf:Person ; foaf:name "Cason Snow" ; foaf:workplaceHomepage <http://www.library.umaine.edu/staff/snow.htm> ; foaf:knows [ a foaf:Person ; foaf:name "Steven Roman" ] .
  12. 12. Benefits of RDF in Linked Data 1. By using HTTP URIs as globally unique identifiers for data items as well as for vocabulary terms, the RDF data model is inherently designed for being used at global scale and enables anybody to refer to anything. 2. Clients can look up any URI in an RDF graph over the Web to retrieve additional information. Thus each RDF triple is part of the global Web of Data and each RDF triple can be used as a starting point to explore this data space. 3. The data model enables you to set RDF links between data from different sources. 4. Information from different sources can easily be combined by merging the two sets of triples into a single graph. 5. RDF allows you to represent information that is expressed using different schemata in a single graph, meaning that you can mix terms for different vocabularies to represent data. 6. Combined with schema languages such as RDF-Schema and OWL, the data model allows the use of as much or as little structure as desired, meaning that tightly structured data as well as semi-structured data can be represented. Source: http://linkeddatabook.com/editions/1.0/#htoc16
  13. 13. Why Linked Data Linked Data provides a more generic, more flexible publishing paradigm which makes it easier for data consumers to discover and integrate data from large numbers of data sources. In particular, Linked Data provides: • A unifying data model • A standardized data access mechanism • Hyperlink-based data discovery • Self-descriptive data Source: http://linkeddatabook.com/editions/1.0/#htoc22
  14. 14. Semantic Web Bringing Data to the Web
  15. 15. What is the Semantic Web The ultimate goal of the Web of data is to enable computers to do more useful work and to develop systems that can support trusted interactions over the network. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. Linked data are empowered by technologies such as RDF, SPARQL, OWL, and SKOS. Source: http://www.w3.org/standards/semanticweb/
  16. 16. Linked Data The Semantic Web is a Web of data — of dates and titles and part numbers and chemical properties and any other data one might conceive of. RDF provides the foundation for publishing and linking your data. Source: http://www.w3.org/standards/semanticweb/
  17. 17. Vocabularies At times it may be important or valuable to organize data. Using OWL (to build vocabularies, or “ontologies”) and SKOS (for designing knowledge organization systems) it is possible to enrich data with additional meaning, which allows more people (and more machines) to do more with the data. Vocabularies are the contextless list of terms used Ontologies provide the relationships and grammar to express relations between vocabulary terms Source: http://www.w3.org/standards/semanticweb/
  18. 18. Ontology Examples Dublin Core FOAF WOT Basic Geo Vocabulary
  19. 19. Query Query languages go hand-in-hand with databases. If the Semantic Web is viewed as a global database, then it is easy to understand why one would need a query language for that data. SPARQL is the query language for the Semantic Web. Source: http://www.w3.org/standards/semanticweb/
  20. 20. Inference Near the top of the Semantic Web stack one finds inference — reasoning over data through rules. W3C work on rules, primarily through RIF and OWL, is focused on translating between rule languages and exchanging rules among different systems. Source: http://www.w3.org/standards/semanticweb/
  21. 21. And You BIBFRAME and Linked Data Library Projects
  22. 22. BIBFRAME BIBFRAME (Bibliographic Framework Initiative) is a project by LC to provide a foundation of bibliographic description for integration in the Web of Data. Uses RDF serialization.
  23. 23. BIBFRAME The BIBFRAME Model consists of the following main classes: Creative Work - a resource reflecting a conceptual essence of the cataloging item. Instance - a resource reflecting an individual, material embodiment of the Work. Authority - a resource reflecting key authority concepts that have defined relationships reflected in the Work and Instance. Examples of Authority Resources include People, Places, Topics, Organizations, etc. Annotation - a resource that decorates other BIBFRAME resources with additional information. Examples of such annotations include Library Holdings information, cover art and reviews.
  24. 24. Core BIBFRAME
  25. 25. Creative Work The Work exists as a Web based control point that reflects both commonality of content between and among the various Instances associated with the Work as well as a reference point for other Works. Common properties of Works include contextual relationships to BIBFRAME Authorities related to the “subjectness” (Topic, Person, Place, Geographical, etc.) of the resource as well as the entities (Person, Organization, Meeting, etc.) associated with its creation. Works can relate to other Works reflecting, for example, part / whole relationships.
  26. 26. Instance BIBFRAME Instances reflect an individual, material embodiment of a BIBFRAME Work that can be physical or digital in nature. A BIBFRAME Instance exists as a Web based control point that includes properties specific to the materialization as well as contextual relationships to appropriate BIBFRAME Authorities related to the publication, production, distribution of the material resource. Each BIBFRAME Instance is an instance of one and only one BIBFRAME Work.
  27. 27. Authorities BIBFRAME Authorities are key authority concepts that are the target of defined relationships reflected in the Work and Instance. Example of BIBFRAME Authority Resources include People, Places, Topics, Organizations, etc. From a cataloging perspective Authorities provide a means for supporting disambiguation and synchronization around authoritative information. From a users perspective, BIBFRAME Authorities provide effective and efficient control points that can be used to help navigate and contextualize related BIBFRAME Works and Instances. BIBFRAME Authorities are not designed to compete or replace existing authority efforts but rather provide a common, light weight abstraction layer over various different Web based authority efforts to make them even more effective.
  28. 28. Annotation Libraries generate, maintain and improve an enormous amount of high-quality data that is valuable well beyond traditional library boundaries. The Bibliographic Framework Initiative recognizes this by including as a goal the ability to “accommodate and distinguish expert-, automated-, and self- generated metadata, including annotations (reviews, comments) and usage data.” Rather than pre-define and limit our potential uses of this data, the BIBFRAME model provides the necessary scaffolding to allows this data to easily be annotated by libraries as well as third party users of this information.
  29. 29. Annotated BIBFRAME
  30. 30. BIBFRAME and MARC BIBFRAME is not ready yet, and it will be a mixed environment for the near future. Currently there is a tool to convert MARC to BIBFRAME. It changes fairly often as BIBFRAME develops. Currently designed to be rules agnostic, but RDA is a major component.
  31. 31. Digital Public Library of America The Digital Public Library of America (DPLA) is an all-digital library that aggregates metadata — or information describing an item — and thumbnails for millions of photographs, manuscripts, books, sounds, moving images, and more from libraries, archives, and museums around the United States. DPLA brings together the riches of America’s libraries, archives, and museums, and makes them freely available to the world.
  32. 32. European Library The European Library is an independent not-for-profit library services organisation supported by CENL, LIBER and CERL. The European Library importantly works to strengthen and support libraries across the continent. Member libraries benefit from a powerful, low-cost aggregation structure enabling a greater exposure of digital resources and bibliographic records. We collect, enrich and innovate with libraries' data and content for the widest possible dissemination. The European Library's mission is to be THE open data hub for library data in Europe. Additionally, The European Library partakes in projects to create useful tools and a pan-European infrastructure for librarians and researchers.
  33. 33. Linked Data for Libraries LD4L The goal of the project is to create a Scholarly Resource Semantic Information Store (SRSIS) model that works both within individual institutions and through a coordinated, extensible network of Linked Open Data to capture the intellectual value that librarians and other domain experts and scholars add to information resources when they describe, annotate, organize, select, and use those resources, together with the social value evident from patterns of usage.
  34. 34. Further resources Reading BIBFRAME Primer XML RDF Education Certificate in XML and RDF-based Systems W3Schools XML Tutorial
  35. 35. Contact information Cason Snow Metadata Librarian/Cataloger University of Maine 207-581-1670

Hinweis der Redaktion

  • A unifying data model. By providing for the globally unique identification of entities and by allowing different schemata to be used in parallel to represent data, the RDF data model has been especially designed for the use case of global data sharing. In contrast, the other methods for publishing data on the Web rely on a wide variety of different data models, and the resulting heterogeneity needs to be bridged in the integration process.
    A standardized data access mechanism. Linked Data commits itself to a specific pattern of using the HTTP protocol. This agreement allows data sources to be accessed using generic data browsers and enables the complete data space to be crawled by search engines. In contrast, Web APIs are accessed using different proprietary interfaces.
    Hyperlink-based data discovery. By using URIs as global identifiers for entities, Linked Data allows hyperlinks to be set between entities in different data sources. These data links connect all Linked Data into a single global data space and enable Linked Data applications to discover new data sources at run-time. In contrast, Web APIs as well as data dumps in proprietary formats remain isolated data islands.
    Self-descriptive data. Linked Data eases the integration of data from different sources by relying on shared vocabularies, making the definitions of these vocabularies retrievable, and by allowing terms from different vocabularies to be connected to each other by vocabulary links.

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