At some point in your career, you will likely find yourself in a museum where nothing in the collection is cataloged.

Starting from the beginning can have its benefits—such as establishing and maintaining consistent best practices. But it can also be incredibly overwhelming. This mini-series will outline how to take a “ground zero” approach including a discussion of how to prioritize and how batch processing can help.

What do we mean by “cataloged”?

For our purposes we define “cataloged” to mean that information about the collection items is captured, whether on paper, a spreadsheet, or in a Collections Management System (CMS). For many small or under-resourced museums—especially those that rely on volunteer help—there’s typically little to no data captured for the items in the collection. This is not to disparage these institutions; they are doing the best they can with the resources they have.

Where do you begin?

Once resources are available, it can be difficult to know where to start! Gathering more information about the situation you are in is step number one.

The first things to figure out are:

• What information exists
• What resources are available
• What practices you wish to implement

The next three sections will provide additional detail for each of these areas.

What information exists, if any?

Before you begin, attempt to gather all known documentation on the collection. It’s important to perform a survey of the information captured thus far so that you don’t inadvertently duplicate work and lose precious time in the project.

Documentation types could include the following:

• Donor files
• Purchase invoices
• Donation forms
• Preliminary or past inventories
• Past catalog records whether hand written or from a previous, now defunct database
• Exhibit catalogs, pull lists, and labels
• Anything that may capture some item-level information

We’re looking for information on:

• When the objects may have been donated and/or accessioned
• Who donated the object and other provenance
• Any accession or otherwise unique identifier
• Any descriptions on the objects, where they came from, who made them, when they were created, etc.
• A sense of the material types
• Any notes on the condition of the item or past conservation work
• Any exhibits or loans the items may have been a part of
• Indication of any rights or access restrictions

While it may not seem obvious at first glance, the information found across these documents can help you to fill-in missing information gaps for the collection. Or, at least give you a starting point of information to further investigate.

What resources do you have access to?

The next item for consideration is the resources you have available to you. Knowing what your resources are will aid in right-sizing the project you take on. For example, the amount of work you can take on for this project will vary depending on whether you’re a solo collection manager, versus part of a moderate-sized team. You’ll also need access to certain tools for the project. Cataloging a collection requires a spreadsheet as a minimum. And, if you’re intending to digitize objects as part of the project then you’ll have additional tool needs.

Consider the quantity and quality of your resources. Such as:

• People
• Database
• Digitization Equipment and Software (as appropriate)

What best practices are most applicable for your museum and collection?

Since you are starting “at zero” you’ll want to select and establish best practices for cataloging collection objects. Best practices are informed by the industry standards you adopt and adapt to you work.

Consider establishing best practices for the following areas:

• Information capture (what fields to use)
• Descriptive standards (how to use the fields)
• Controlled vocabulary

Conclusion

Now that we’ve covered the essentials you need to consider before you embark on cataloging an undocumented collection, it’s time to consider strategies for approach and determining priorities. Both elements will be critical to your project’s success. We’ll cover both aspects in the following weeks. We will then end with advice on how to construct batch-processing methods to aid in projects where mass data capture is necessary and staff time is finite.