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Introduction to the Special Issue on Computational Archival Science

Published: 22 January 2022 Publication History
This special issue of JOCCH aims to present a wide-ranging review over the current state-of-the-art of research in computational archival science. The large-scale digitisation 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 disrupting to traditional archival theories and practices and are presenting challenges for practitioners and researchers who work with archival material. They also offer enhanced possibilities for scholarship, through the application of computational methods and tools to the archival problem space, and, more fundamentally, through the integration of “computational thinking” with “archival thinking.” This potential led the collaborators in this special issue to identify Computational Archival Science (CAS) as a new field of study, and our working definition 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 the 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. [1]
The CAS Initiative (https://ai-collaboratory.net/cas/) was launched in 2016 at an inaugural KCL-UMD Symposium and since then has held an annual workshop at the IEEE Big Data Conference. In December 2021, we expect to host the sixth CAS event. This sustained activity has produced nearly 60 research works and countless events along the way.
This special issue is one of the outcomes of a one-year international research networking grant for UK-US collaborations on digital scholarship in cultural heritage institutions, funded by the Arts and Humanities Research Council (AHRC) of the UK in 2019. [2] The Department of Digital Humanities at King's College London (UK), together with the National Archives (UK), the Digital Curation Innovation Center at the University of Maryland iSchool (USA), and the Maryland State Archives in the USA, were awarded an AHRC network grant to address the field of CAS. The CAS research network's particular focus was the application of computational methods to the contextualisation of records within archival collections at a time when the archive is becoming an increasingly digital space.

Content of the Special Issue

The aim of the special issue on Computational Archival Science is to explore the conjunction of emerging computational and analytical methods and technologies with archival practice (including record keeping) and their consequences for historical, social, scientific, and cultural research engagement with archives. With the collection of articles in this Special Issue, we envisage to identify potential in these areas and examine the new questions that they can provoke. At the same time, we aim to address the questions and concerns scholarship is raising about issues of interpretation raised by such methods, and in particular the challenges of producing quality—meaning, knowledge, and value—from quantity, tracing data, and analytic provenance across complex knowledge production ecosystems and addressing data privacy and other ethical issues.
Given the very positive response to the call for papers, this special issue is split into two parts, the first of which makes up the current issue of the journal (Vol. 15, Issue 1), the second will make up Vol. 15, Issue 3. Part 1 includes the following 11 contributions:
E. Daga et al., Integrating Citizen Experiences in Cultural Heritage Archives: Requirements, State of the Art, and Challenges
Mark Hedges
King's College London (KCL)
Richard Marciano
University of Maryland (UMD)
Eirini Goudarouli
The National Archives
Guest Editors

Acknowledgments

The guest editors would like to congratulate the authors who made this special issue possible and offer their sincere thanks to the reviewers for their important role in ensuring the quality of submissions. We are grateful to the Editor-in-Chief of the ACM Journal on Computing and Cultural Heritage, Prof. Franco Niccolucci, for approving and seeing this special issue through, as well as to the Associate Editor and Information Director of the journal, Dr. Karina Rodriguez Echavarria, for her valuable support and contribution to the successful organisation of this special issue.

References

[1]
Marciano et al. 2018. Archival records and training in the Age of Big Data. In Re-Envisioning the MLS: Perspectives on the Future of Library and Information Science Education. For more information, see: ai-collaboratory.net/cas/.
[2]
For more information about the Computational Archival Science (CAS) research network have a look at the project's webpage at https://computationalarchives.net/.

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  • (2024)Training in Computational Archival Science: Do CAS Educational Frameworks meet Professional Expectations?2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825962(2440-2448)Online publication date: 15-Dec-2024
  • (2024)Demystifying oral history with natural language processing and data analytics: a case study of the Densho digital collectionThe Electronic Library10.1108/EL-12-2023-030342:4(643-663)Online publication date: 28-Jun-2024
  • (2024)Exploring the Application of Artificial Intelligence and Machine Learning in GLAM CollectionsProceedings of the Association for Information Science and Technology10.1002/pra2.110161:1(782-785)Online publication date: 15-Oct-2024
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Published In

cover image Journal on Computing and Cultural Heritage
Journal on Computing and Cultural Heritage   Volume 15, Issue 1
February 2022
348 pages
ISSN:1556-4673
EISSN:1556-4711
DOI:10.1145/3505194
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 January 2022
Published in JOCCH Volume 15, Issue 1

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  • (2024)Training in Computational Archival Science: Do CAS Educational Frameworks meet Professional Expectations?2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825962(2440-2448)Online publication date: 15-Dec-2024
  • (2024)Demystifying oral history with natural language processing and data analytics: a case study of the Densho digital collectionThe Electronic Library10.1108/EL-12-2023-030342:4(643-663)Online publication date: 28-Jun-2024
  • (2024)Exploring the Application of Artificial Intelligence and Machine Learning in GLAM CollectionsProceedings of the Association for Information Science and Technology10.1002/pra2.110161:1(782-785)Online publication date: 15-Oct-2024
  • (2023)AI-Generated Images as an Emergent Record Format2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386946(2020-2031)Online publication date: 15-Dec-2023
  • (2023)Record DNA: reconceptualising digital records as the future evidence baseArchival Science10.1007/s10502-023-09414-w23:3(411-446)Online publication date: 12-Apr-2023
  • (2023) The “Collections as ML Data” checklist for machine learning and cultural heritage Journal of the Association for Information Science and Technology10.1002/asi.24765Online publication date: 2-May-2023
  • (2022)Digital History and the Politics of DigitizationDigital Scholarship in the Humanities10.1093/llc/fqac05038:2(830-851)Online publication date: 16-Sep-2022

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