by Richard Marciano, Victoria Lemieux, and Mark Hedges
The 3rd workshop on Computational Archival Science (CAS) was held on December 12, 2018, in Seattle, following two earlier CAS workshops in 2016 in Washington DC and in 2017 in Boston. It also built on three earlier workshops on ‘Big Humanities Data’ organized by the same chairs at the 2013-2015 conferences, and more directly on a symposium held in April 2016 at the University of Maryland. The current working definition of 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 .
The workshop featured five sessions and thirteen papers with international presenters and authors from the US, Canada, Germany, the Netherlands, the UK, Bulgaria, South Africa, and Portugal. All details (photos, abstracts, slides, and papers) are available at: http://dcicblog.umd.edu/cas/ieee-big-data-2018-3rd-cas-workshop/. The keynote focused on using digital archives to preserve the history of WWII Japanese-American incarceration and featured Geoff Froh, Deputy Director at Densho.org in Seattle.
This workshop explored the conjunction (and its consequences) of emerging methods and technologies around big data with archival practice and new forms of analysis and historical, social, scientific, and cultural research engagement with archives. The aim was 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 addressed 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.
- Computational Thinking and Computational Archival Science
- #1:Introducing Computational Thinking into Archival Science Education [William Underwood et al]
- #2:Automating the Detection of Personally Identifiable Information (PII) in Japanese-American WWII Incarceration Camp Records [Richard Marciano, et al.]
- #3:Computational Archival Practice: Towards a Theory for Archival Engineering [Kenneth Thibodeau]
- #4:Stirring The Cauldron: Redefining Computational Archival Science (CAS) for The Big Data Domain [Nathaniel Payne]
- Machine Learning in Support of Archival Functions
- #5:Protecting Privacy in the Archives: Supervised Machine Learning and Born-Digital Records [Tim Hutchinson]
- #6:Computer-Assisted Appraisal and Selection of Archival Materials [Cal Lee]
- Metadata and Enterprise Architecture
- #7:Measuring Completeness as Metadata Quality Metric in Europeana [Péter Királyet al.]
- #8:In-place Synchronisation of Hierarchical Archival Descriptions [Mike Bryant et al.]
- #9:The Utility Enterprise Architecture for Records Professionals [Shadrack Katuu]
- Data Management
- #10:Framing the scope of the common data model for machine-actionable Data Management Plans [João Cardoso et al.]
- #11:The Blockchain Litmus Test [Tyler Smith]
- Social and Cultural Institution Archives
- #12:A Case Study in Creating Transparency in Using Cultural Big Data: The Legacy of Slavery Project [Ryan Cox, Sohan Shah et al]
- #13:Jupyter Notebooks for Generous Archive Interfaces [Mari Wigham et al.]
Several related events are scheduled in April 2019: (1) a 1 ½ day workshop on “Developing a Computational Framework for Library and Archival Education” will take place on April 3 & 4, 2019, at the iConference 2019 event (See: https://iconference2019.umd.edu/external-events-and-excursions/ for details), and (2) a “Blue Sky” paper session on “Establishing an International Computational Network for Librarians and Archivists” (See: https://www.conftool.com/iConference2019/index.php?page=browseSessions&form_session=356).
Finally, we are planning a 4th CAS Workshop in December 2019 at the 2019 IEEE International Conference on Big Data (IEEE BigData 2019) in Los Angeles, CA. Stay tuned for an upcoming CAS#4 workshop call for proposals, where we would welcome SAA member contributions!
 “Archival records and training in the Age of Big Data”, Marciano, R., Lemieux, V., Hedges, M., Esteva, M., Underwood, W., Kurtz, M. & Conrad, M.. See: LINK. 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. May 17, 2018. See: 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
Richard Marciano is a professor at the University of Maryland iSchool where he directs the Digital Curation Innovation Center (DCIC). He previously conducted research at the San Diego Supercomputer Center at the University of California San Diego for over a decade. His research interests center on digital preservation, sustainable archives, cyberinfrastructure, and big data. He is also the 2017 recipient of Emmett Leahy Award for achievements in records and information management. Marciano holds degrees in Avionics and Electrical Engineering, a Master’s and Ph.D. in Computer Science from the University of Iowa. In addition, he conducted postdoctoral research in Computational Geography.
Victoria Lemieux is an associate professor of archival science at the iSchool and lead of the Blockchain research cluster, Blockchain@UBC at the University of British Columbia – Canada’s largest and most diverse research cluster devoted to blockchain technology. Her current research is focused on risk to the availability of trustworthy records, in particular in blockchain record keeping systems, and how these risks impact upon transparency, financial stability, public accountability and human rights. She has organized two summer institutes for Blockchain@UBC to provide training in blockchain and distributed ledgers, and her next summer institute is scheduled for May 27-June 7, 2019. She has received many awards for her professional work and research, including the 2015 Emmett Leahy Award for outstanding contributions to the field of records management, a 2015 World Bank Big Data Innovation Award, a 2016 Emerald Literati Award and a 2018 Britt Literary Award for her research on blockchain technology. She is also a faculty associate at multiple units within UBC, including the Peter Wall Institute for Advanced Studies, Sauder School of Business, and the Institute for Computers, Information and Cognitive Systems.
Mark Hedges is a Senior Lecturer in the Department of Digital Humanities at King’s College London, where he teaches on the MA in Digital Asset and Media Management, and is also Departmental Research Lead. His original academic background was in mathematics and philosophy, and he gained a PhD in mathematics at University College London, before starting a 17-year career in the software industry, before joining King’s in 2005. His research is concerned primarily with digital archives, research infrastructures, and computational methods, and he has led a range of projects in these areas over the last decade. Most recently has been working in Rwanda on initiatives relating to digital archives and the transformative impact of digital technologies.