A Shared Museum CMS Case Study: Under the umbrella of the Utah Department of Cultural & Community Engagement (UTCCE), the Utah Division of Arts & Museums (UA&M) and the Utah Historical Society (UHS) have united to modernize their digital stewardship. Together, they embarked on a procurement process for a shared Collections Management System (CMS) that could meet the needs of both institutions and be expanded to include future partners. To achieve this, they selected Lucidea’s Argus and ArchivEra platforms to manage their diverse art, artifact, and archival collections.
You can explore the collections of the Utah Division of Arts & Museums and the Utah Historical Society via their public portal.
A shared vocabulary is a powerful tool because it unlocks the collective stories of individual institutions for a wider audience. When multiple museums are within a shared CMS, a common vocabulary is crucial for making meaningful, data-driven connections. In addition to standardized data, vocabulary and vocabulary-supporting tools like Argus’ aggregates can highlight cross-collection connections while still maintaining data accuracy at the individual museum level.
This post will outline how UA&M and UHS navigated vocabulary implementation, the technical functionality available with Argus aggregates, and how UA&M and UHS leveraged aggregates to serve up cross-collection results from complementary sources of data.
To read more about sharing a single database and an overview of the benefits and challenges, please check out our previous post on Lucidea’s Think Clearly Blog: Power in Partnerships: The Unified Hub.
Bridging Art and History: The Path to Alignment
UA&M and UHS steward fundamentally different materials—art versus historical artifacts—each with its own established descriptive traditions. The challenge was not to erase these differences, but to find the common threads where these distinct collections overlap. Moving from two separate sets of terminology to a unified language isn’t just a technical configuration; it’s a collaborative practice of alignment that allows Utah’s data to be searched and understood as a single, cohesive collection.
Common museum vocabularies center on:
- Object Name or Title
- Creator or Artist/Maker
- Medium or Material
- Geography
- Nationality
- Cultural Groups
- Categories and Classifications
- Subject
While their collections are different types, UA&M and UHS share a large overlap of people, places, and things. The above listed vocabularies can help connect their collections through the adoption of the same standards or through the use of aligned aggregates. Now that the sister divisions are in their new Argus system, the teams are working their way toward shared vocabularies in appropriate areas. In the meantime, Utah is leveraging aggregates to serve as collection connectors.
Aggregates Offer Individualism with Flexible Connections
Aggregates assist with cross-pollination discovery by identifying two or more fields that are alike and should be searched together (as an aggregate). In short, aggregates enable machine readability, allowing the CMS to interconnect records based on shared nodes. The use of aggregates helps to reconcile the different ways museum partners might describe a similar item, creating a seamless experience for the end user.
An Argus aggregate can include any field type and is often deployed as a keyword search. For example, an aggregate can be composed of object title, object name, description, and subjects. Or, across two similar but separate vocab fields that host a controlled lexicon, like Medium and Material. UA&M and UHS elected to use aggregates in a number of ways with an emphasis on supporting their separate but related approach to vocabularies. For example, UA&M uses the Medium field while UHS uses Materials. These can be searched together as a keyword search and pull all relevant items regardless of whether the data was in UA&M’s Medium field or UHS’s Materials field.
Removing Barriers and Connecting Collections
By prioritizing shared vocabularies and smart data aggregation, we ensure that the database search engine doesn’t just look for matching characters, but instead reveals interconnected concepts at the heart of the collective collections. This best practice meets technical infrastructure approach removes the “correct field” barrier imposed upon the end user. By shifting the complexity from the user to the underlying technology we create a more inclusive, accessible, and powerful tool for meaningful collection discovery.
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