
We describe computational treatments of archival collections through a case study involving World War II Japanese-American Incarceration Camps. We focus on automating the detection of personally identifiable information or PII. The paper also discusses the emergence of computational archival science (CAS) and the development of a computational framework for library and archival education. Computational Thinking practices are applied to Archival Science practices. These include: (1) data creation, manipulation, analysis, and visualization (2) designing and constructing computational models, and (3) computer programming, developing modular computational solutions, and troubleshooting and debugging. We conclude with PII algorithm accuracy, transparency, and performance considerations and future developments.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
