Thanks to the GLAM Incubator, the Archives of Ontario has been able to move full speed ahead with a pilot project that will make archival material both easier to discover and more accessible
Constrained by tradition and technology, archival descriptions have historically focused on two things: the records themselves and the people and organizations that create these records. But because the reality of record creation is far more complex, often with multiple people and organizations making their own unique contributions, this method has left a lot of information unexplored and undocumented.
For more than a decade, the International Council on Archives has been looking to develop a new standard for archival description, leading to the release last fall of its new Records in Contexts model. When Aaron Hope, senior archivist at the Archives of Ontario, who has followed the issue closely, read about it, he was excited by the possibilities of the proposed graph-based data model for archival description.
In a nutshell, the new standard is designed to do three things. It links out to external data sources. It’s more expressive and allows archivists to document more of the complexity. And it makes archives more discoverable.
The new model, says Hope, provides “whole new avenues for our users to explore. For example, we are testing out various data visualizations. Instead of just text or code, we’re actually plotting the data in a visual graph that users can then explore, clicking through from one entity, following that chain to another entity and exploring wherever their interests take them.”
To build and test the new model, the Archives of Ontario needed technical expertise in coding and programming. Looking for this support, Hope successfully applied last fall to the Faculty of Information’s GLAM incubator which allowed the Archives to hire research assistants, Peiwen Zhang, a Master of Information student in human-centred data science, and Pavel Zhelnov, a PhD student in medicine. (In another Faculty of Information connection, alumni Jill Ruby and Amir Lavie work on this project with Hope.)
“The research assistants have been really vital to the success of the project, taking our ideas and making them possible,” says Hope. “They take care of coding and the technical aspects of the data format of linked open data.” Their work is guided by Faculty of Information professors Anastasia Kuzminykh and Shion Guha, who also offer insights on the project more generally.
By this August, the Archives had run tests on small sample groups and was ready to do a proof of concept test, batch converting thousands of its existing data records into the new enriched format. If successful, the plan is to convert all Archives of Ontario descriptions, which number almost three million.
Separately, the Archives has been working to improve its existing descriptions by uncovering more of the stories buried in traditional archival descriptions. Digging into dry government records can turn up “really interesting stories about people and communities who are not otherwise documented, at least not in major archives in Ontario,” says Hope. “We’re interested in surfacing some of those narratives. We need to take better advantage of this new data model, by going back and redescribing things and making those links out to external resources.”
With the current stage of the project wrapping up, the Archives has hired a grant writer to help it prepare a SSHRC Partnership Engage Grant application, which would procure a second year of funding for its research assistants to continue the project. As a leader in Canada in this field, the Archives of Ontario also wants to develop prototype interfaces for data input and data exploration including visualization. Another goal is to have members of the public and researchers test the new model to see if it succeeds in its goal of helping people find information in new and unique ways.
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