A Collaborative Museum Discovery Portal: Blending Best Practices

Each museum has its own cataloging DNA, shaped and developed over decades by generations of staff, and often across multiple systems. When collections come together in a shared discovery portal, these cataloging differences can create friction for the search engine and impact the quality of the results for users.

In our first post of this series, we defined shared collection discovery as the inherently collaborative practice of making digital records from multiple institutions searchable and accessible through a single, unified interface. But once two or more museums commit to a joint portal, they immediately face a practical hurdle: how to make data from different institutions cross-searchable. In other words, how can we format our data to speak the same language?

To create a successful cross-searchable environment, partnering museums must adopt a blended approach to best practices where they reconcile their individual cataloging styles into a unified standard that works for the collective.

What Does it Mean to Blend Best Practices?

In the context of this series, blending best practices is the process where two or more partner institutions reconcile their internal cataloging traditions to create a unified data standard for a shared portal.

This doesn’t mean every aspect of cataloging needs to change. Instead, the focus is on data that is most valuable for connecting collections across multiple institutions. The goal is to align these key data areas with those of our peers and partner organizations. Key aspects include:

• Shared Catalog Record Template: This is the technical agreement on where data lives. This practice helps ensure that data is uniformly entered in the agreed-upon field.
• Shared Data Format: Institutions may have different ways of recording dates or materials. Blending best practices requires partners to standardize data formatting (e.g., using a YYYY format for dates) so the portal’s filters, facets, and timelines function correctly across the entire collective collection.
• Shared Vocabulary: Partners agree to use the same external vocabulary standards—such as ULAN for artist names or AAT for subjects—to ensure that a search for a single creator or topic pulls results from all participating institutions simultaneously.

All three of these areas impact (for good or for ill) the ability to cross-search collections and meaningfully filter results.

The Art of Cross-Institutional Data Mapping

When contributing to a shared portal, each institution’s data must be mapped to a central template. This is where the blending truly happens.

For example, your Materials field might need to map to the portal’s Medium field. This process requires communication between registrars and collections managers across the partnership. If one museum records “oil on canvas” in their Medium field while another puts it in Description, the portal’s search filters may not work as intended.

By agreeing on these mapping rules up front, partners help ensure that the central search engine can treat all contributed data as part of a single, coherent collection.

The Power of Blended Best Practices

To create a seamless user experience, partner institutions must move beyond their individual cataloging traditions and align their data with the collective’s needs. This collaborative effort, known as blending best practices, transforms fragmented data sets into a unified, high-performing discovery environment.

By reconciling these internal styles, partners ensure that their shared portal provides more reliable, relevant, and interconnected search results for their audience. The benefits include:

• Improved Search Results: It reduces friction for the search engine, which directly improves the quality and accuracy of results for the user.
• Cross-Searchability: By reconciling individual cataloging styles into a unified standard, data from different institutions can speak the same language, allowing them to be searched simultaneously.
• Synchronized Filtering and Timelines: Normalizing data formats ensures that portal-wide filters, facets, and timelines function correctly across the collective collection.
• Greater Data Consistency: Using a shared catalog record template helps ensure information is uniformly placed in agreed-upon fields, reducing the risk of search issues that may occur when data is misplaced.
• Unified Collection Experience: Successful data mapping allows the central search engine to treat data from multiple institutions as a single, coherent collection.

Collaboration as a Standard

Blending best practices across institutions is a significant commitment, but it’s the only way to move from a collection of separate parts to a truly shared discovery experience.

By aligning our data, we aren’t losing our institutional identity. Instead, we’re amplifying it through the power of the collective.