Students complete a Data Modeling assignment in Data & Records Management 9492, part of the Archival Studies MLIS emphasis at Missouri’s iSchool. Working in groups of three, students are provided with a data dictionary and dataset from an archival agency, and they engage in manipulation and visualization of the data to show patterns, identify or reconstruct decisions, and construct future uses of the records. Classmates often take and share notes in a Google Doc. A Guest Lecture was generously given by PN member Geoff Froh, Deputy Director at Denshō, a month out from the assignment due date. Titled “Punchcard Stories,” Froh’s presentation discussed the Japanese-American incarceration history and contextualized our three datasets. We also noted the Library of Congress’s collection of camp newspapers as mentioned in a recent virtual presentation by the Missouri S&T Archives and SHSMO-Rolla Research Center, “Japanese-American Student Success at the Missouri School of Mines in World War II.” The student submissions are structured as a Computational Story in CASES – including the objectives, visualizations, and ethical considerations enumerated in each Notebook. The below sections relate to the Data Modeling assignment itself, first in the context of CT Piloting Network (project website) educator (EN) and practitioner (PN) network collaborations, and more broadly that of graduate archival education and archival science pedagogy. Some material was first presented as “Solving Incarceration Camp Cases with Computational Storytelling” at the October Mini-Summit on CAS Educational Possibilities. The Notebooks include instructor contributions and student initials for some combined items.
Learn more about Archival Studies at Missouri’s iSchool at https://education.missouri.edu/degree/archival-studies-mlis/
The main objective of the Data Modeling assignment, which is one of the course goals in IS_LT 9492, is to: “Develop skills to mediate among stakeholders (records creators, users, and IT staff) over the records lifecycle to ensure perpetual (tiered) access to analog and digital formats.” The objective also aligns with the 2016 SAA GPAS curriculum components, including but not limited to: (1) Knowledge of archival material and functions, (c) Arrangement and Description, and (e) Reference and Access; and (2) Knowledge of the profession, (c) Ethics and values.
Students are asked to download one tool – OpenRefine – and use it to import the provided dataset (portion). Doing so will meet the goal of DP 3, Manipulation.
Student groups are encouraged to use additional resources to meet the goal of DP 5, Visualization, some examples of which include Dataviz.tools, Data Biographies, Visualization Tools presented at ARLIS/NA 2021, Dr. Melanie Walsh’s Introduction to Cultural Analytics & Python (2021), and the Usage case studies in Teaching and Learning with Jupyter (2019)
For OpenRefine:
The members of the CT-LASER+ Educator Network (EN) this semester received complementary portions of a dataset being studied by Denshō: Intake Registry, Camp cards (Dr. Buchanan’s course), and Exit Registry. The data, digitized in 2015, were treated as non-public information until they reached 75 years of age. Accordingly the EN coordinates their students’ secure access to the data during the course semester, after which students should delete their local copies.