The value and complexity of collection arrangement for evidentiary work

Abstract

Archives are invaluable resources for those interested in understanding past activities and events. What makes archival collections valuable as evidence is that they are organized in a way that connects the materials to their creator(s), their associated activities, and recordkeeping systems. In order to create this organization archivists engage in a complex process that involves arranging materials physically and intellectually. This arrangement focuses on documenting the original order of the materials and making them evident to secondary users. The time-consuming nature of this process has resulted in a massive backlog of unprocessed (and thus unavailable) collections, which represents an impediment to the investigative activities of scholars and researchers. To help alleviate such a situation, this article presents a novel approach to archival arrangement, using tabletop computers and digitized images. The article explains the project design and implementation and discusses the evaluation results. This work provides several major contributions to the field, including: a new system that allows archival collections to be arranged digitally, new methods and metrics for evaluating archival arrangements, a detailed analysis of the steps involved in archival arrangement and how they correlate with the final outcomes of the process, and a method for analyzing arrangements based on the topologies created by processing archivists.

Archival infrastructure and the information backlog

“…Since the turn of the twenty-first century, methods and tools from digital forensics (software, programs, and scripts) have been used in tandem with human analysis to complete select digital processing tasks: extracting metadata, creating file catalogs and access copies, as well as the deduplication and bulk ingesting of files into digital repositories at scale (Kim et al 2006 ). Interactive technologies, including the multitouch tabletop computer, have also been used in tandem with human analysis to prototype a digitize first, process second approach to improve the effectiveness of archival processing (Crow et al 2012 ; Francisco-Revilla and Trace 2014 ; Trace and Francisco-Revilla 2015 ). In addition, the increasing size of digital collections and the scale of processing tasks have brought AI techniques from computer science and computational linguistics to the fore with machine learning, natural language processing, and data mining forming the new archival toolkit.…”

Acting up, Talking Back: TITA, TIARA, and the Value of Gossip

“…Gossip, such as that printed in TITA and TIARA, presents a challenge to traditional archival conceptions of reliability. At their core definitions of reliability revolve around the concept that the record is a consistent (Pearce-Moses, 2005c), a full, and an accurate representation of the activities to which it attests (Trace and Francisco-Revilla, 2015). As archival scholar Heather MacNeil writes, the "reliable record is one that is capable of standing for the facts to which it attests.…”

The quantified-self archive: documenting lives through self-tracking data

“…Contacts between the quantified self and archival communities have already been established, as evidenced by Gary Wolf’s 2017 talk on archiving QS data at the National Archives of the Netherlands (Nationaal Archief). Connections between archival science and HCI are also in a promising if nascent phase (Crow et al , 2012; Abreu and Acker, 2012; Stanton et al , 2013; Bunn, 2015; Schofield et al , 2015, 2017; Trace and Francisco-Revilla, 2015; Nilsson and Ottsen Hansen, 2018).…”