Publications and Presentations

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Publications and Presentations of the Linked Data Research Group at the University of Alabama SLIS.

  1. Liu, Ho., Aderon, C., Wagon, N., Bamba, A. L., Li, X., Liu, Hu., MacCall, S. & Gan, Y. (2023). Automated player identification and indexing using two-stage deep learning network. Scientific Reports, 13, article number: 10036 (available open access: https://doi.org/10.1038/s41598-023-36657-5).
  2. Liu, H., & MacCall, S.L. (2022). Historical Text Datafication and Loss: Computational Recovery of Typographical Layout Logic on an RDF Graph Featuring ML Methods. Conference paper presented at the 2022 ASIS&T Annual Meeting Pre-conference AI Workshop: AI in the Real World: Strengthening Connections Between LIS Research and Practice (presentation slides and speaker notes).
  3. Liu, H., MacCall, S.L., & Lewis, N.A. (2021). Knowledge Graph as Navigational Paratext: Returning Structural Semantics to a Closed System Index through the Computational Recovery of the Typographical Logic of Digitized Historical Book Indexes. Conference paper presented at Wissensorganisation 2021, biennial conferences of the German chapter of the International Society of Knowledge Organization (presentation slides).
  4. Liu, H., MacCall, S.L., & Lewis, N.A. (2021). Exploring the computational recovery of the typographical logic of book indexes as paratext for improving navigation within digitized historical texts using semantic methods. Poster presented at the 2021 annual meeting of the American Society for Information Science and Technology. (Poster PDF).
  5. Nguyen Nguyen, Jeff Reidy, and Noah Wagnon (2021). "Final Presentation: Automated Jersey Number Recognition". Senior design team presentation for EECE 494.407 for 2020-21 academic year at The University of Alabama. PDF slidedeck.
  6. MacCall, S.L., & Liu, H. (2020). Data-driven semantic indexing of digital assets documenting American football game action. Poster presented at the 2020 annual meeting of the American Society for Information Science and Technology. https://doi.org/10.1002/pra2.414
  7. MacCall, S.L., Bott, G., Anderson, C.M., & Liu, H. (2020). Investigation of a data-driven indexing method for multimedia asset collections in sports: Phase I: How much data can be recovered from Alabama football history? Presented at the University of Alabama 2020 Faculty Research Day, Tuscaloosa, AL. Virtual session due to COVID19
  8. MacCall, S.L. (2020). Systems and methods for digital asset organization. U.S . Patent number 10,534,812.
  9. MacCall, S.L., Liu, H., & Anderson, C.M. (2020). Statistical data recovery from historical documentation of Alabama football games using Wikibase as a repository. Interactive demonstration accepted for Connecting Collections as Data: Transforming Communities, Sharing Knowledge, and Building Networks with International GLAM Labs, Washington, DC. (Conference canceled due to COVID-19)
  10. MacCall, S.L. (2020). Data-driven semantic DAM indexing incorporating statistical play-by-play game logs: A linked data application using Wikibase from the 2017 football season of the Alabama Crimson Tide. Conference paper presented at the 2020 LD4 Conference on Linked Data in Libraries, College Station, TX. (Video of presentation)
  11. Anderson, C.M., Liu, H., & MacCall, S.L. (2020). Crowdsourcing in a semantic indexing workflow for efficiently organizing historical multimedia sports collections. Poster accepted for the 2020 Annual Meeting of the Alabama Library Association, Birmingham, AL. (Conference canceled due to COVID-19)
  12. MacCall, S.L., Liu, H., & Anderson, C.M. (2019). How much statistical data can be recovered from Alabama football history? Piloting a crowdsourced approach using Wikibase as data repository. Conference paper presented at 2019 Digitorium Digital Humanities Conference, Tuscaloosa, AL. [UA Institutional Repository deposit: https://ir.ua.edu/handle/123456789/6574]
  13. MacCall, S.L. (2018). Investigation of a data-driven indexing method for multimedia asset collections in sports: Phase 2: Developing SLIS research capacity for key linked open data technologies. University of Alabama School of Library and Information Studies Research Fund -$1,000. Funded.
  14. MacCall, S.L., & Bott, G. (2018). Investigation of a data-driven indexing method for multimedia asset collections in sports: Phase 1: How much data can be recovered from Alabama football history? University of Alabama Office of Research and Development Research Grants Committee Level 1 Program - $6,000. Funded
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