3. CAS Publications:

2018:

• “A Case Study in Creating Transparency in Using Cultural Big Data: The Legacy of Slavery Project”, R. Cox et al. (2018) Proceedings of IEEE Big Data Conference 2018, CAS Workshop, Seattle, Washington. Link: http://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2018/11/los_paper.pdf

• “Automating the Detection of Personally Identifiable Information (PII) in Japanese-American WWII Incarceration Camp Records.”, R. Marciano, W. Underwood, M. Hannaee, C. Mullane, A. Singh and Z. Tethong. (2018) Proceedings of IEEE Big Data Conference 2018, CAS Workshop, Seattle, Washington. Link: http://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2018/10/pii_paper.pdf
• “Digital Curation of a World War II Japanese-American Incarceration Camp Collection: Implications for Sociotechnical Archival Systems”, R. Marciano, M. Lee, W. Underwood, S. Laib, Z. Diker, and A. Singh (2018). DigitalHeritage2018, San Francisco, Oct. 27, 2018 (part of the Digital Solutions for Heritage Archives & Collections session). Link: http://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2019/04/DigitalHERITAGE_2018_paper_220.pdf

• Foundational Paper: Apr. 2018
  • “Archival records and training in the Age of Big Data”, Marciano, R., Lemieux, V., Hedges, M., Esteva, M., Underwood, W., Kurtz, M. & Conrad, M. (2018). In J. Percell , L. C. Sarin , P. T. Jaeger , J. C. Bertot (Eds.), Re-Envisioning the MLS: Perspectives on the Future of Library and Information Science Education (Advances in Librarianship, Volume 44B, pp.179-199). Emerald Publishing Limited. Link: http://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2017/06/Marciano-et-al-Archival-Records-and-Training-in-the-Age-of-Big-Data-final.pdf.

• “The Enhanced ‘International Research Portal for Records Related to Nazi-Era Cultural Property” Project (IRP2): A Continuing Case Study by Michael Kurtz, Greg Jansen, and Richard Marciano.

• “Mapping Inequality: ‘Big Data’ Meets Social History in the Story of Redlining,” in The Routledge Companion to Spatial History, Richard Marciano et al. Eds: Ian Gregory, Don Debats, Don Lafreniere.

2017:

• Chapter in Future Archives, Victoria Lemieux

•  Towards Automated Quality Curation of Video Collections from a Realistic Perspective, University of Texas at Austin,Todd Goodall, Maria Esteva, Sandra Sweat, Alan C. Bovik

•  “Evaluating the Use of Blockchain in Land Transactions: An Archival Science Perspective,” in European Property Law Journal, Victoria Lemieux (forthcoming)

• Association of Canadian Archivists 2017 Annual Meeting: Jun. 9, 2017
  • “Disrupting Archival Education [making a case for Computational Science]”, Victoria Lemieux, Ottawa CA.

• “Modeling archival problems in Computational Archival Science (CAS)”, May 16, 2017 – Maria Esteva
  Link: https://saaers.wordpress.com/2017/05/16/modeling-archival-problems-in-computational-archival-science-cas/

• SAA Electronic Records Section (ERS) Blog: July 27, 2016 & May 16, 2017
  • “Building a ‘Computational Archival Science’ Community”, Jul. 27, 2016, Richard Marciano
    Link: https://saaers.wordpress.com/2016/07/27/building-a-computational-archival-science-community/

• The Signal, Library of Congress: April 14, 2017
  • “The Reality of Preparing MLS Students for a Competitive and Increasingly Digital World”, Guest blog post by MLIS graduate, Mary Kendig
  • Link: https://blogs.loc.gov/thesignal/2017/04/identity-crisis-the-reality-of-preparing-mls-students-for-a-competitive-and-increasingly-digital-world/
  • Main points:
    1. Need to encourage students to enroll into technology intensive courses and programs.
    2. Need to develop projects for students to gain digital skills and hands-on experience.
    3. Need to develop collaborations with institutions to provide beneficial learning environments for students.

• National Forum Position Paper: Mar. 3, 2017
  • “On the Computational Turn in Archives & Libraries and the Notions of Levels of Computational Services”, Invited talk and position paper
  • Link: http://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2016/05/AlwaysAlreadyComputationalPositionStatement.pdf
    At the UC Santa Barbara IMLS workshop on “Always Already Computational: Library Collections as Data”, the goals of which are to: (1) articulate computationally amenable library collection use cases, (2) initiate a collection of best practices that support developing, describing, and providing access to computationally amenable library collections.