9th COMPUTATIONAL ARCHIVAL SCIENCE (CAS) WORKSHOP
Dec. X, 2024 (exact date TBD)

Part of: 2024 IEEE Big Data Conference (IEEE BigData 2024) — https://www3.cs.stonybrook.edu/~ieeebigdata2024 (Washington DC, USA) – Dec. 15-18, 2024

  • IMPORTANT DEADLINES:

    • Monday, Nov. 4, 2024 (final): Due date for full workshop papers submission
    • Friday, Nov 15, 2024: Notification of paper acceptance to authors
    • Wednesday, Nov 20, 2024 (hard deadline): Camera-ready of accepted papers
    • Dec 15 to 18, 2024: Day-long CAS workshop (in person) in Washington DC, USA (exact day TBD)
      • If you are planning on attending the workshop, please contact organizers for registration details!

    PAPER SUBMISSION:

    COMPUTATIONAL ARCHIVAL SCIENCE: digital records in the age of big data

    INTRODUCTION TO WORKSHOP [also see our CAS Portal]:

    The large-scale digitization of analogue archives, the emerging diverse forms of born-digital archive, and the new ways in which researchers across disciplines (as well as the public)wish to engage with archival material, are resulting in disruptions to transitional archival theories and practices. Increasing quantities of ‘big archival data’ present challenges for the practitioners and researchers who work with archival material, but also offer enhanced possibilities for scholarship, through the application both of computational methods and tools to the archival problem space and of archival methods and tools to computational problems such as trusted computing, as well as, more fundamentally, through the integration of computational thinking with archival thinking.

    Our working definition of Archival Computational Science (CAS) is:

      • A transdisciplinary field that integrates computational and archival theories, methods and resources, both to support the creation and preservation of reliable and authentic records/archives and to address large-scale records/archives processing, analysis, storage, and access, with aim of improving efficiency, productivity and precision, in support of recordkeeping, appraisal, arrangement and description, preservation and access decisions, and engaging and undertaking research with archival material.

    OBJECTIVES

    This workshop will explore the conjunction (and its consequences) of emerging methods and technologies around big data with archival practice (including record keeping) and new forms of analysis and historical, social, scientific, and cultural research engagement with archives.We aim to identify and evaluate current trends, requirements, and potential in these areas, to examine the new questions that they can provoke, and to help determine possible research agendas for the evolution of computational archival science in the coming years. At the same time, we will address the questions and concerns scholarship is raising about the interpretation of ‘big data’ and the uses to which it is put, in particular appraising the challenges of producing quality–meaning, knowledge and value–from quantity, tracing data and analytic provenance across complex ‘big data’ platforms and knowledge production ecosystems, and addressing data privacy issues.

    This will be the 8th workshop at IEEE Big Data addressing Computational Archival Science (CAS), following on from workshops in 2016, 2017, 2018, 2019, 2020, 2021, 2022 and 2023. It also builds on three earlier workshops on ‘Big Humanities Data’ organized by the same chairs at the 2013-2015 conferences, and more directly on a 2016 symposium held in April 2016 at the University of Maryland.

    All papers accepted for the workshop will be included in the Conference Proceedings published by the IEEE Computer Society Press. In addition to standard papers, the workshop (and the call for papers) will incorporate a student poster session for PhD and Master’s level students.

    RESEARCH TOPICS COVERED:
    Topics covered by the workshop include, but are not restricted to, the following:

      • Application of analytics to archival material, including AI, ML, text-mining, data-mining, sentiment analysis, network analysis.
      • Analytics in support of archival processing, including e-discovery, identification of personal information, appraisal, arrangement and description.
      • Scalable services for archives, including identification, preservation, metadata generation, integrity checking, normalization, reconciliation, linked data, entity extraction, anonymization and reduction.
      • New forms of archives, including Web, social media, audiovisual archives, and blockchain.
      • Cyber-infrastructures for archive-based research and for development and hosting of collections
      • Big data and archival theory and practice
      • Digital curation and preservation
      • Crowd-sourcing and archives
      • Big data and the construction of memory and identity
      • Specific big data technologies (e.g. NoSQL databases) and their applications
      • Corpora and reference collections of big archival data
      • Linked data and archives
      • Big data and provenance
      • Constructing big data research objects from archives
      • Legal and ethical issues in big data archives

    PROGRAM CHAIRS:
    Dr. Mark Hedges
    Department of Digital Humanities (DDH)
    King’s College London, UK

    Prof. Victoria Lemieux
    School of Information
    University of British Columbia, CANADA

    Prof. Richard Marciano
    Advanced Information Collaboratory (AIC)
    College of Information Studies
    University of Maryland, USA

    PROGRAM COMMITTEE MEMBERS:
    Dr. Sarah Buchanan
    Library and Information Science
    iSchool
    University of Missouri, USA

    Mark Conrad
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    Dr. Anne J. Gilliland
    Center for Information as Evidence (CIE)
    School of Education and Information Science
    UCLA, USA

    Dr. Jane Greenberg
    Alice B. Kroeger Professor and Director, Metadata Research Center
    College of Computing & Informatics
    Drexel University, USA

    Dr. Lise Jaillant
    Communication and Media
    School of Social Sciences and Humanities
    Loughborough University, UK

    Gregory Jansen
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    Rajesh Kumar Gnanasekaran
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    Dr. Nathaniel Payne
    Advanced Information Collaboratory (AIC)
    Dygital9 and NOQii & Contivos
    University of British Columbia, CANADA

    Lori Perine
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    Jennifer Proctor
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    Dr. Bill Underwood
    Advanced Information Collaboratory (AIC)
    College of Information
    University of Maryland, USA

    • In Memoriam one year ago… our friend and CAS collaborator Michael Kurtz:
      “One of the pulls to the bright side is our CAS initiative. Not only is it intellectually compelling to me, but I feel I am part of an endeavor that will help others in the archival space and beyond. To be even more blunt, I am so curious to see what happens next as it makes me want to push the boundaries of the time that I have left!”
    Photo taken on Friday, Dec. 16, 2022.
      • Michael launched the CAS initiative in 2016, with Victoria Lemieux, Mark Hedges, Maria Esteva, William Underwood, Mark Conrad, and Richard Marciano [LINK].