Lost Without Context: Representing Relationships between Archival Materials in the Digital Environment

The Lighting the Way Handbook

Written by Jodi Allison-Bunnell, Maureen Cresci Callahan, Gretchen Gueguen, John Kunze, Krystyna K. Matusiak, and Gregory Wiedeman · 2021 November

This is the group contribution I facilitated for the Lighting the Way Working Meeting, published in Matienzo, M.A. & Handel, Dinah, eds. The Lighting the Way Handbook: Case Studies, Guidelines, and Emergent Futures for Archival Discovery and Delivery (November 2021).

The rest of the authors deserve credit for this article. I organized and facilitated our working meeting sessions and did some editing and small contributions to the piece.


The problem of representing context for archival materials in digital asset management systems (DAMS) has been noted - and lamented - for as long as digital representations of archives have been online. This white paper discusses the nature of this challenge, explores why it remains so thorny, and provides examples of where archival access systems have been successful in representing context. With hopes of moving the conversation forward, we provide a set of principles for representing archives in context that can be implemented regardless of the particular systems employed. These principles are based on archival standards and software best practices, and can be summarized as six ideas:

  1. Create space for deep conversations with all stakeholders and so that everyone understands foundational requirements.
  2. Value archival context and design systems so that contextual relationships between records are explicit and clear.
  3. Leverage the power (and cost savings) of aggregate digitization and description when appropriate.
  4. Be consistent about modelling relationships between an analog object (if relevant), a digital object, and the description of the archival record.
  5. Use persistent identifiers.
  6. Lean on widely-used standards, systems, and solutions.

Finally, we call on standards-making bodies to introduce a more robust data model for archival representation that includes both the description of archival contents and contexts.