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7 advanced uses of rdfs

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7 advanced uses of rdfs

  1. 1. + Advanced use RDFS Mariano Rodriguez-Muro, Free University of Bozen-Bolzano
  2. 2. + Disclaimer  License   A few examples from these slides has been taken from   This work is licensed under a Creative Commons Attribution-Share Alike 3.0 License (http://creativecommons.org/licenses/by-sa/3.0/) Semantic Web for the working Ontologist. Chapter 6. Some of the slides on the use of taxonomies are based on:  http://info.earley.com/webinar-replay-business-value-taxonomy-aug2012
  3. 3. + Reading material  Semantic Web for the working Ontologist. Chapter 6 http://proquest.safaribooksonline.com/book/-/9780123859655
  4. 4. + Uses of RDFS (and ontology)  Application oriented uses     Application behavior without coding Data integration through vocabulary alignment, integration Controlled vocabularies Formal ontology:  Definition of taxonomies, e.g., parent/broader, child/narrower, etc. Taxonomy/Ontology can be used to create business/data value Taxonomy can open the door for new kinds of data management
  5. 5. + Enterprise
  6. 6. + Content Management  Increase the control/productivity that the enterprise has over their data to increase internal productivity, customer satisfaction, etc.  Why not “just Google” your sites? These do not work in the enterprise    Back links and Statistics In the enterprise, granularity is small
  7. 7. + Search enhancement  Search enhancement    Examples:     Finding content (DB., entries, document collections, etc) relevant to a query, but tagged with an alternative name Key is search by metadata and organized metadata Add synonyms to a query Language/translation Include more general terms Precision vs Recall. The focus here is recall, get all “relevant” content.
  8. 8. + Browsing and Navigation: Search overload User doesn’t know what he wants precisely
  9. 9. + Browsing and Navigation: Search overload Facets Give control to the user
  10. 10. + Browsing and Navigation: Search overload Note: Taxonomy is not navigation
  11. 11. + Browsing and navigation, results  Faceted navigation in e-commerce:  Findability  Conversions  Sales  Market size  Customer satisfaction  etc.  Studies show that faceted navigation in enterprise content easily increases all these aspects in hard benchmarks.  See presentation by Earley & Associates
  12. 12. + Content Reuse – Taxonomy in Content Management  Many use cases   Examples, knowledge management, content finding, etc.   Look at business processes, group at targeted users Useful when knowledge is large, and it needs to be accessible fast A Taxonomy can be used to  Define content and document types (e.g., “Article”)  Define the fields that will describe attributes (e.g., tag a document with “Industry”)  Define the actual values of certain fields (e.g., the list of values for the attribute “Industry” might include “Construction”, “Information Technology”, “Utilities”, etc.)
  13. 13. + Example: Knowledge management  Portal development  Service a functional organization, e.g., call centers, technical field services  Key: Changing content  Requires: Access to the latest's and best value always Call centers representatives required 50% less time to solve a problem with correctly organized information. Earley & Associates, 2012 Average reactive time per incident: 10.35hrs Knowledge Helpful Average Reactive TPI: 5.45hrs Knowledge Helpful Time Saved Per Incident: 43%
  14. 14. + Content reuse: Improved Management of Marketing Assets  Type: Magazine Ads  Channel: Print  Target Demographic: Parents  Country: US  Language: English  Concept: Rebellion  Brand: Settletra  Do your kids:  Have discipline problems?  Trouble paying attention?  Trouble getting along? Maybe It’s time to findout how Settletra can help
  15. 15. + Content reuse
  16. 16. + Content reuse: result  Requirement   Question   Do we have material for this campaign No?   Images for campaigns Produce new material Use taxonomies to improve search  $1.25M /yr through digital asset management and increased image reuse (Earley & Associates)
  17. 17. + Public Entities
  18. 18. + The power of large, curated taxonomies  Many large taxonomies developed in the context of large national and international projects  Large amount of knowledge  Clean knowledge (manually curated)  General knowledge (cover domains rather than applications)  Reusable to provide valuable services
  19. 19. + Taxonomies resources  Taxonomy resources:  http://www.taxonomywarehouse.com/  http://www.taxobank.org/  http://www.taxotips.com/resources/sources/  http://id.loc.gov/  http://id.loc.gov/authorities/subjects/sh85112348.html  http://bioportal.bioontology.org/  http://www.w3.org/2001/sw/wiki/SKOS/Datasets Some of these are actually ONTOLOGY repositories
  20. 20. + Taxonomies in Biology  Taxonomies in Biology have been developed for a long time    Large investment world wide Deployed in applications today Include wide range of Biology subjects   Medical terminologies   Macro and Micro biology (Genes, Human Anatomy) Etc. Started as knowledge management/sharing, now applications are being built.
  21. 21. • • • • Download Traverse Search Comment Mapping Services • • • Create Download Upload Widgets • • • Tree-view Auto-complete Graph-view Ontology Services http://rest.bioontology.org Views Annotation Term recognition Data Access Fetch “data” annotated with a given term http://bioportal.bioontology.org
  22. 22. Annotation service Process textual metadata to automatically tag text with as many ontology terms as possible. 90 million calls, ~700 GB of data
  23. 23. Annotating Clinical Text
  24. 24. Resource index Pubmed Abstracts Adverse Events (AERS) GEO : Clinical Trials Drug Bank
  25. 25. + Semantic Annotation services  Semantic Annotations services are very wide spread  Topics include:  General purpose (based on DBPedia URI’s for example)  Specialized  Music  Movies  Libraries  Biology  http://lmgtfy.com/?q=semantic+annotator  http://dbpedia-spotlight.github.com/demo/index.html
  26. 26. + Summary
  27. 27. + Summary: RDFS  Ontology languages, Ontologies  RDFS language and inferences  Common use patterns of RDFS inferences  Taxonomies  Their value and use in the enterprise  Collections and applications

Notas do Editor

  • Example, the library of congress. Largest librarian resource, large taxonomies in the form of subject headings. Subject headings are: There is taxonomy in the form of…Note broader/narrower terms/related terms etc.
  • Another example of large taxonomy resources is biology. Biologist have been building taxonomies from… They use them for agreement, controlled vocabularies in medical applications, document tagging. Very useful applications, for example text mining and taxonomies We create and maintain a library of biomedical ontologies.We buildtools and Web services to enable the use of ontologies and their derivatives.We collaborate with scientific communities that develop and use ontologies.
  • text mining, explain resource index workflow

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