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Western Name Authority File: Creating a Collaborative Regional Vocabulary
- 1. Western Name Authority File: Creating a Collaborative Regional Vocabulary Anna Neatrour (@annaneat) Jeremy Myntti (@jmyntti) DPLA Fest, April 2017
- 2. Why?
- 3. Why? Metadata problems when collections are aggregated: • Savage, C. R. (Charles Roscoe), 1832-1909 • Savage, C. R.(Charles Roscoe),1832-1909 • Savage, C.R. (Charles Roscoe) • Savage, Charles R. • C. R. Savage (Charles Roscoe Savage and George Ottinger), Pioneer Art Gallery, East Temple Street, Salt Lake City, Utah • Charles R. Savage • Savage, Charles Roscoe • C. R. (Charles Roscoe) Savage, photographer • Savage, C. R. • Charles R. Charles R. Savage BYU Digital Collections http://contentdm.lib.byu.edu/cdm/ref/collection/Savage2/id/1749 Charles R. Savage, perplexed by his many name variants.
- 4. More metadata, more metadata problems...
- 5. IMLS Grant for regional authority control 4 phases: 1) investigating data models to express local/regional name authority data using linked data standards 2) evaluation of tools used for creating, maintaining, and making this data available 3) pilot implementation using the tools investigated in the second phase 4) assessment of how this type of authority data can improve digital collection metadata on a local, regional, and national level. Thompson, Mickey; Salt Flats – Shot 24 https://collections.lib.utah.edu/details?id=694074
- 6. What will save us?
- 7. Libraries Working Together Metadata Review Received data from 8 institutions • Brigham Young University • Oregon Digital (Univ. of Oregon and Oregon State Univ.) • University of Nevada, Reno • University of Utah • University of Denver • Utah Department of Heritage and Arts • Utah State Archives • Utah State University Data gathered • Name (including associated dates) • Institution • Collection • Field(s) • Type (personal name or corporate body) • Cross references Mormon Meteor -Shot 6 https://collections.lib.utah.edu/details?id=608551
- 8. How Will It Happen?
- 9. Phase 1: metadata wrangling (data metrics) • Started with ~500,000 names • Deduplicated to 76,360 • 7357 -- 2+ collections (9.6%) • 1484 -- 2+ institutions (1.9%) • 271 -- 2+ states (0.35%) • 62,381 personal names • 10,706 corporate bodies • 3,273 unknown • 1091 are single words • 2400+ cross references • 500+ PN are First Last Total names submitted • Brigham Young University - 30,535 • University of Utah - 7533 • Utah State University - 2067 • Utah State Historical Society - 12,138 • Utah State Archives - 3657 • University of Nevada, Reno - 1277 • Oregon Digital - 4170 • University of Denver - 16,608
- 10. Phase 2: investigating tools (evaluation matrix) https://goo.gl/wMQRbY
- 11. Phase 2: investigating tools/frameworks Vitro Opaque Namespace Controlled Vocabulary Manager ThManager redis
- 12. DATA MODELS!!!!!
- 13. Data Models: Collaborative Investigation Data to capture • Preferred form of name • Alternate forms of name • Local authority source • Institution holdings • Relationship information Data Models Explored • SKOS • OWL • BIBFRAME Authorities/Agent/Role • EAC-CPF – look to SNAC as a model http://socialarchive.iath.virginia.edu/ Campbell, Donald; Salt Flats – Shot 2 https://collections.lib.utah.edu/details?id=691549
- 15. Stats script leveraging DPLA API Search results in December 2016 Creator Subject Name MWDL DPLA MWDL DPLA Savage, C. R. 2022 2226 44 50 Savage, C. R. (Charles Roscoe) 1830 2023 43 44 Savage, C. R. (Charles Roscoe), 1832- 1909 1708 1901 43 43 Savage, C. R., 1832-1909 1708 1901 43 43 Savage, Charles 1936 2165 60 126 Savage, Charles R. 1932 2128 58 65 Savage, Charles R., 1832-1909 1708 1902 43 43 Savage, Charles Roscoe 1833 2034 44 53 Savage, Charles Roscoe, 1832-1909 1708 1904 43 43 Savage, Charles, 1832-1909 1708 1905 43 43 Savage, Chas. R. 1 1 0 1 Savage, Chas. R., 1832-1909 0 0 0 0 SQLlite database, use python Requests library to query DPLA API - get stats on coverage for name variants in MWDL and DPLA.
- 16. Workflow considerations - 2nd year • Managing vocabulary • Reconciliation issues • Many partners on CONTENTdm • Need external system not tied to specific digital library software/infrastructure • Explore impact of WNAF on metadata creators and users Thompson, Mickey; Salt Flats -Shot 11 Utah Department of Heritage and Arts, Salt Lake Tribune Negative Collection https://collections.lib.utah.edu/details?id=694077
- 17. Further reading and acknowledgements Full Grant Narrative https://www.imls.gov/grants/awarded/LG-72-16-0002-16 Project Webpage https://sites.google.com/site/westernnameauthorityfile/home This project was made possible in part by the Institute of Museum and Library Services LG-72- 16-0002-16.
Notes de l'éditeur
- Today I’m going to present on our pilot project to establish a regional vocabulary for names and corporate bodies. Along the way too, I’m going to highlight a new collection of Salt Lake Tribune negatives from the Utah Department of Heritage and Arts – one of the partners of the University of Utah.
- Phases for project – reviewing data models, evaluate tools, pilot implementation for tools and/or framework developed and assessment
- Partners we received data from – note it is very Utah centric although we also have Nevada, Colorado, and Oregon represented.
- JM Started with over 500,000 names Deduplicated to 76,360 (deduplicated based off of full name entered, institution, collection, field) Lots more deduplication still needs to take place (some manual work that will wait for our graduate student assistant) I expect the following stats to improve after more deduplication is done 7357 used in more than one collection/field (9.6%) 13 used in more than 20 collections/fields 80 used in more than 10 collections/fields 6795 used in 2-5 collections/fields 1484 used in more than one institution (1.9%) 1360 in two institutions 110 in three institutions 11 in four institutions 3 in five institutions 271 used in more than one state (.35%) 267 in two states 4 in three states 62,381 personal names 10,706 corporate bodies 3,273 unknown 1091 are single words (could be PN or CB or only family name) 1922 cross references (this will go up as the list is further refined and deduplicated) ~70 variations on C.R. Savage 424 variations on Shipler Commercial Photographers 500+ personal names are First Last (rather than Last, First) many generic names shared between Colorado and Oregon other common names include United States, US Army Corps of Engineers, Ronald Reagan, John Fremont, William Shakespeare, George Washington, Harry S. Truman, William Howard Taft (and other similar names that would be in LCNAF) Total names submitted BYU - 30,535 UU - 7533 USU - 2067 USHS - 12,138 UtSA - 3657 UNR - 1277 Oregon - 4170 DU - 16,608
- AN - Using tools broadly, but we are evaluating solutions with the awareness that we are likely to end up with a solution that will be likely to be more of a framework. For example we might store names and related information with one particular software solution, but then need to export and transform the data for a public display.
- AN - when we started we were trying to go very wide in terms of opening up all possibilities for testing. Some tools we were initially considering have been ruled out already, with comments in the evaluation matrix.
- Reviewed lots of documentation about several data models Due to scope of project and our goals (along with our partners goals), decided on EAC-CPF (Encoded Archival Context for Corporate Bodies, Personal Names, and Families) Reviewing EAC fields we want to include now and fields to implement in the future How to express this as RDF linked data Creating cheat sheet for entering data we want to capture Using document Gina Strack @ Utah State Archives prepared as starting point Fields include: Identity Alternate Names Multiple identities Official Name Authorized form Parallel names Relationships (in future) Context (in future) Resources
- Baseline statistics on current names representation, will gather stats again at the end of the project
- Will likely be building a prototype framework rather than finding one tool out there that will do everything we want it to, from managing names collaboratively, to expressing the data in EAC-CPF, to developing some workflows for metadata remediation for partners.