Recent Posts

This month, we completed our project to create an ArchivesSpace Helpers Package. While the end product looked slightly differently than initially scoped–we’re about to embark on a project to add some of the code we’ve created to the ArchivesSnake library–we created a library of functions and tests that builds on ArchivesSnake to support common use cases. This is the first of two blog posts, where project team members reflect on the project. First up are the code helpers, who were paired with code owners on a rotating basis, and were responsible for understanding and presenting the work of their partner at the scrum meetings.

Earlier this year, the RAC undertook a project to research the General Data Protection Regulation (GDPR), the European Commission’s data protection legislation that took effect in May 2018, and produce a report on its implications for the RAC. In general, there’s a dearth of information and lack of clear legal interpretation related to archival collections data and the GDPR, particularly for U.S. archives, so we’ve made that report available on the RAC’s Documentation Site so that it might be useful for other institutions. In this post, I’ll introduce some concepts from the GDPR and share a few key resources on the topic of how it applies to archives.

In preparation for our new discovery system, processing archivists at the RAC have been working on cleaning up some of our data in ArchivesSpace in order to facilitate improved searching. A large chunk of data that has been problematic for some time is our collection of agent records in ArchivesSpace. We simply had too many agents, none of which are standardized, and most which were duplicates of agents that were already in our system, misspelled, or contained incorrect data. Some of our finding aids had too many agents at the file-level, and other findings aids didn’t have any linked agents at all. The state of our agent records makes it difficult for researchers to use the “Filter by Creator” feature, since there is no consistency as to how many agents are assigned, or the level in which they are assigned to a finding aid. In this post, we’ll discuss how we evaluated and cleaned up the agents in our repository.

As you might have read in previous blog entries (here and here), processing archivists Amy Berish, Darren Young, and myself have been cleaning up and improving ArchivesSpace data in preparation for the Rockefeller Archive Center’s new access system. As part of this initiative, I have removed thousands of legacy access restriction notes from our collections.

As you may already know, the Digital Strategies Team is working on developing and integrating a new discovery system for the RAC. In preparation for this new system, we have been working on cleaning up data in ArchivesSpace so that the new system can more effectively point researchers to relevant material. My involvement in the data cleanup phase included adding structured (begin/end) dates to all archival objects in our ArchivesSpace repository. In this post, I’ll be talking about how we developed a semi-automated plan to clean up date expressions and add structured dates to our repository by parsing date expressions.