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Linked Data Aggregation, Integration and Mashups in the Performing Arts

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This presentation describes the process of data integration from multiple sources to create rich descriptions of people entities and design cross-domain access services for cultural heritage resources. This work is part of an ongoing project centered on applying LOD technologies to archival performing arts content developed by the Semantic Lab at Pratt Institute.

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Linked Data Aggregation, Integration and Mashups in the Performing Arts

  1. 1. Linked Data Aggregation, Integration and Mashups in the Performing Arts: A Project Report M. Cristina Pattuelli & Hannah Sistrunk NKOS Workshop at DC-2017 Washington, D.C., October 28, 2017
  2. 2. Open Data Linking Aggregation Integration Mashups
  3. 3. Background & Context
  4. 4. Relationships as a tool for aggregation Linked data generation via text mining and entity extraction: 1. Named-entity Recognition 2. Entity Reconciliation 3. Entity Association
  5. 5. Mona Hinton interviewed by Milt Fillius & Michael Woods, Scottsdale, Arizona, March 4, 1995.The Fillius Jazz Archive, Hamilton College.
  6. 6. Mona Hinton interviewed by Milt Fillius & Michael Woods, Scottsdale, Arizona, March 4, 1995.The Fillius Jazz Archive, Hamilton College. <http://linkedjazz/resource/Mona_Hinton>
  7. 7. Mona Hinton interviewed by Milt Fillius & Michael Woods, Scottsdale, Arizona, March 4, 1995.The Fillius Jazz Archive, Hamilton College. http://linkedjazz/resource/Mona_Hinton <http://dbpedia.org/resource/Ella_Fitzgerald>
  8. 8. rel:knows_of
  9. 9. Mona Hinton interviewed by Milt Fillius & Michael Woods, Scottsdale, Arizona, March 4, 1995.The Fillius Jazz Archive, Hamilton College. <http://linkedjazz/resource/Mona_Hinton> http://purl.org/vocab/relationship/knowsOf> <http://dbpedia.org/resource/Ella_Fitzgerald>
  10. 10. LJ TRANSCRIPT ANALYZER
  11. 11. Network Graph TYPED RELATIONSHIPS DRIVING THE NETWORKS <PersonA> <rel:knowsOf> <PersonB>
  12. 12. Entity Reconciliation In order to link data effectively and correctly, data needs to be unambiguously identified.
  13. 13. Identity Management owl:sameAs
  14. 14. <http://data.carnegiehall.org/names/47408> <http://xmlns.com/foaf/0.1/name> "Ella Fitzgerald" <http://dbpedia.org/resource/Ella_Fitzgerald> <http://dbpedia.org/ontology/name> "Ella Fitzgerald" <http://linkedjazz.org/resource/Ella_Fitzgerald> <http://xmlns.com/foaf/0.1/name> "Ella Fitzgerald"@en <https://musicbrainz.org/artist/54799c0e-eb45- 4eea-996d-c4d71a63c499> <http://xmlns.com/foaf/0.1/name> “Ella Fitzgerald” <https://viaf.org/viaf/6148211> < http://schema.org/familyName > “Fitzgerald” <https://www.wikidata.org/wiki/Q1768> <https://www.w3.org/2000/01/ rdf-schema#label> "Ella Fitzgerald" sameAs Co-referencing
  15. 15. Integration through interlinking
  16. 16. Enrich your data by consuming data from other LOD-enabled datasets. More complex queries Trigger new questions Ignite discovery Benefits
  17. 17. Carnegie Hall Performance History Data
  18. 18. JAZZ TRANSCRIPT DATA INTERVIEW PASSAGE PASSAGE PASSAGE INTERVIEWEE MUSICIAN MENTIONED MUSICIAN MENTIONED PERFORMANCE HISTORY DATA EVENT CONDUCTOR PERFORMER PERFORMER DATE VENUE WORK sameAs
  19. 19. Static view of the Carnegie Hall and Linked Jazz relationship visualization
  20. 20. The results were made available for exploration through an interactive Gephi visualization.
  21. 21. JAZZ TRANSCRIPT DATA INTERVIEW PASSAGE PASSAGE PASSAGE INTERVIEWEE MUSICIAN MENTIONED MUSICIAN MENTIONED PERFORMANCE HISTORY DATA EVENT CONDUCTOR PERFORMER PERFORMER DATE VENUE WORK sameAs NAME BIRTH DATE DEATH DATE BIRTH PLACE ROLE ENSEMBL E INSTRUM ENT Mashup
  22. 22. MUSICIAN MENTIONED PERFORMER NAME BIRTH DATE DEATH DATE BIRTH PLACE ROLE ENSEMBL E INSTRUM ENT sameAs NAME DEPICTIO N SAME AS KNOWS OF COLLABORA TED WITH MENTOR OF FRIEND OF PLAYED TOGETHER IN BAND TOGETHER BAND MEMBER ACQUAINTA NCE OF TOURED WITH sameAs
  23. 23. JAZZ TRANSCRIPT DATA INTERVIEW PASSAGE PASSAGE PASSAGE INTERVIEWEE MUSICIAN MENTIONED MUSICIAN MENTIONED PERFORMANCE HISTORY DATA EVENT CONDUCTOR PERFORMER PERFORMER DATE VENUE WORK sameAs NAME BIRTH DATE DEATH DATE BIRTH PLACE ROLE ENSEMBL E INSTRUM ENT Mashup
  24. 24. Interview with Mary Lou Williams conducted by John S.Wilson June 26, 1973 Smithsonian Institution Jazz Oral History Project Mary LouWilliams
  25. 25. Little Bursts in the Wild “The best use of your data will be thought by somebody else in likely unanticipated ways.”
  26. 26. The JAZZCATS (Jazz Collection of Aggregated Triples) Project “A collection of aggregated RDF triples tracing performance history through musicological data…bridge previously unconnected but complementary information about jazz music.” Daniel Bangert,Alfie Abdul-Rahman, and Terhi Nurmikko-Fuller (UNSW, Oxford University,Australia National University) http://jazzcats.oerc.ox.ac.uk/
  27. 27. Discography of over 200 recordings
  28. 28. Solos within performances, including pitch, key, and chord changes
  29. 29. JazzTube Annotations of jazz solos from the Weimar Jazz Database (WJD) + discographies A joint project between the Hochschule für Musik Franz Liszt Weimar (University of Music Franz Liszt Weimar) and the International Audio Laboratories Erlangen. http://mir.audiolabs.uni-erlangen.de/jazztube/about
  30. 30. http://mir.audiolabs.uni-erlangen.de/jazztube/soloists/
  31. 31. Challenges Data Cooking: 80% work involved is in data preparation and transformation – web scraping, wrangling, cleaning, assuring quality and consistency
  32. 32. Challenges Skill-sets needed for information professionals Not established methodologies Organizational limitations (e.g., lack of resources) and unequal opportunities for communities to participate Need to low-barrier tools for linked data engineering tasks
  33. 33. Thank you! Questions? Linked Jazz https://linkedjazz.org @semlabteam Thanks to: Karen Hwang; Matt Miller; Rachel Egan; Bill Levay Cristina Pattuelli mpattuel@pratt.edu @cristinapattuel Hannah Sistrunk hsistrunk@rockarch.org @HaSistrunk SEMANTIC LAB @PRATTCREDITS: Icons from the Noun Project collection Photos from Wikimedia Commons

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