---
title: Making Digital Collections Discoverable (Clemency Wright & PastView Webinar)
description: PastView partner Clemency Wright joins us for a webinar to discuss making digital collections discoverable, with Metadata, Taxonomy & AI.
image: https://blog.townswebarchiving.com/hubfs/Blog%20Header%20%26%20Images%20-%202026-09-17T111217.594.jpg
---

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# PastView Blog

Find out more about Digital Access & Discovery

 

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# Making Digital Collections Discoverable (Clemency Wright & PastView Webinar)

Written by [Paul Marks](https://blog.townswebarchiving.com/pastview/author/paul-marks)  
October 5, 2026 at 9:29 AM

![Blog Header & Images - 2026-09-17T111217.594](https://blog.townswebarchiving.com/hs-fs/hubfs/Blog%20Header%20%26%20Images%20-%202026-09-17T111217.594.jpg?width=2000&name=Blog%20Header%20%26%20Images%20-%202026-09-17T111217.594.jpg "Blog Header & Images - 2026-09-17T111217.594")

## Making Digital Collections Discoverable, with Metadata, Taxonomy and the Role of AI

Digitizing a collection is a major undertaking. But creating digital copies of physical material is only part of the challenge.

Once a collection is online, people need to be able to find what they are looking for, understand what they are seeing, and discover material they might not have known existed.

That is where metadata, taxonomy, and good search design become essential.

In our latest webinar, <http://pastview.com>[PastView](http://pastview.com)’s COO, [Casper Smithson](https://www.linkedin.com/in/caspergsmithson/), joined keywording and search consultant <https://www.linkedin.com/in/clemencywright/>[Clemency Wright](https://www.linkedin.com/in/clemencywright/), Founder and Director of [Clemency Wright Consulting](http://clemency.co.uk) and a specialist partner supporting PastView, to explore how organizations can make their digital collections more discoverable, accessible, and useful.

Hosted by <https://www.linkedin.com/in/martin-drewe-22a38434/>[Martin Drewe](https://www.linkedin.com/in/martin-drewe-22a38434/), Head of Partnerships & Growth at PastView, the conversation covered everything from controlled vocabularies and metadata migration to AI-assisted tagging, facial recognition, and the continuing importance of human expertise.

***Watch the full webinar recording below, or read on for some of the key themes from the discussion.***

 

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### What makes a digital collection discoverable?

A discoverable digital collection combines well-structured metadata, clear taxonomy, consistent keywords, and search tools designed around the needs of its users.

Good metadata helps people understand what an item is, while taxonomy and controlled vocabularies create consistency across a collection. Together, they make it easier for users to search, filter, and explore digital content.

AI can support this process by helping to classify and tag large volumes of material, but human oversight remains essential to ensure metadata is accurate, relevant, sensitive to context, and appropriate for the people using the collection.

For organizations digitizing or migrating archive collections, the key is not simply to create more metadata, but to create the **right metadata for the people who need to find and use the content**.

 

### Metadata is about more than describing an asset

Metadata is often described simply as ‘data about data’. In an archive, that might include information about an object, image, document, or other asset: what it is, where it came from, when it was created, who created it, or what it contains.

Within that metadata sit other elements such as taxonomies and keywords.

A taxonomy provides structure. It can organize terms hierarchically, establish relationships between information, and create a consistent vocabulary for describing a collection.

Keywords, meanwhile, can describe what an asset contains as well as administrative information associated with it, such as a collection, time period, or department.

The terminology itself is less important than understanding what that information needs to achieve.

Ultimately, metadata should help users find the content they need.

### Start with your users, not your system

One of the strongest themes to emerge from the webinar was the importance of putting the user at the center of metadata and search design.

Different audiences may search a collection in very different ways.

An archivist or subject specialist may understand internal terminology, abbreviations, and established cataloging conventions. A member of the public encountering the collection for the first time may use completely different language.

Likewise, internal staff, researchers, external partners, and members of the public may all have different reasons for accessing the same collection.

As Clemency explained:

> *“The value comes from understanding the user journey, and what their needs are.”*

Rather than simply asking what fields a system is capable of supporting, organizations should consider:

- Who will search the collection?
- What are they trying to find?
- What language are they likely to use?
- Which information genuinely helps them narrow their search?
- Are specialist terms supported by more commonly understood synonyms?

Observing how real users search can be particularly revealing. Some people may rely almost entirely on a simple search box, while others prefer filters and more advanced ways of exploring a collection.

Good digital collection design needs to accommodate both.

### Don’t overcomplicate discovery

More metadata fields and more search options do not automatically create a better experience.

In fact, too much complexity can make a collection harder to navigate.

During the webinar, Casper highlighted that some of the most effective systems take a relatively simple approach to search, supported behind the scenes by well-structured metadata.

The goal should not be to expose every piece of information simply because the technology allows it. Instead, organizations should concentrate on the information that genuinely helps people find and explore content.

That can include creating different pathways into a collection and surfacing related material once a user begins exploring.

In other words, the complexity can sit behind the experience. For the person using the archive, discovery should feel straightforward.

### Metadata migration doesn’t have to mean achieving perfection first

Moving an existing collection to a new digital platform often raises another question: should all of the metadata be cleaned up before migration?

There is no single answer.

Some organizations have time to review and restructure their metadata before moving systems. Others may need to migrate quickly because an existing platform is becoming obsolete or is being withdrawn.

As Casper put it, there is:

> *“A fine line between trying to get everything absolutely perfect... and actually getting it into the system.”*

There is a balance to be found between spending significant time trying to make every element of the data perfect and getting the collection into a new system where it can begin to be used and improved.

Metadata also isn’t static.

Collections grow. Organizations acquire new material. Audiences change. New people join teams, and existing terminology evolves.

Migration can therefore be viewed as an opportunity to review what is working, identify weaknesses, and establish a better foundation, rather than trying to create a supposedly ‘finished’ metadata structure that will never need to change.

### Think twice before deleting old metadata

Cleaning up a collection does not necessarily mean deleting anything that appears outdated or inconsistent.

Legacy metadata can provide valuable context about an asset, its provenance, and the way in which the original physical collection was organized.

That is particularly important where historic terminology is now considered outdated or offensive.

There may be good reasons not to expose particular terms through a public-facing search interface. However, removing them completely could mean losing part of the historical record.

Modern archive platforms can allow organizations to retain information while controlling whether it is displayed publicly, indexed for search, or restricted to particular users.

The distinction between **preserving information** and **publishing information** is an important one.

### AI can help with the heavy lifting

Unsurprisingly, AI played a significant part in the conversation.

For organizations managing thousands or even millions of digital assets, the ability to automatically analyze content has obvious appeal.

AI can already assist with tasks such as basic image classification, identifying whether an image was taken indoors or outdoors, recognizing landmarks, and grouping photographs containing the same person.

Within archive collections, technologies such as facial recognition also have the potential to help teams work through large quantities of imagery much more quickly.

This can be particularly valuable for archivists working with limited resources. But AI-generated metadata should not automatically be treated as authoritative.

### Why AI still needs human oversight

One problem with automated tagging is scale.

If an AI tool adds one incorrect tag, correcting it is easy. If it generates thousands of irrelevant or inaccurate tags across a large collection, resolving those errors can quickly become a major task.

That is why it is better to establish rules before deploying AI wherever possible.

A controlled vocabulary, for example, can restrict the terminology an AI system is allowed to apply rather than allowing it to generate unlimited labels.

Human oversight adds something else that technology currently struggles to replicate: context.

A person can understand why a collection exists, who is searching it, the terminology an organization uses, and how language may be changing.

As Clemency noted:

> *“AI can only ever really be behind the humans in that aspect. They are one step behind.”*

AI may recognize that the same individual appears in hundreds of photographs, but a knowledgeable person may still need to identify who that person is and understand why that identification matters.

Similarly, an automated system cannot necessarily understand when terminology has become inappropriate, sensitive, or misleading.

The most useful role for AI in this context is therefore likely to be assistive rather than autonomous: helping people work faster while leaving knowledgeable humans responsible for accuracy, relevance, and judgment.

### Trust and authenticity matter

Search relies on an implicit level of trust.

When somebody searches an archive and receives a result, they generally assume the information presented to them is accurate.

That makes the quality and provenance of metadata increasingly important, particularly as AI becomes more widely used to generate or enhance it.

Organizations need to consider not only whether AI can add metadata, but also whether they can identify how that metadata was created, review it, and correct it where necessary.

Maintaining that chain of accountability helps protect both the integrity of the collection and the trust of its users.

### Metadata is an ongoing process

Perhaps the most important takeaway from the webinar is that metadata should not be viewed as a one-off exercise completed during digitization.

Collections change. Language changes. Technology changes. Most importantly, users and their expectations change.

The metadata and search experience surrounding a digital collection need to evolve with them.

That means reviewing search behavior, listening to users, refining vocabularies, and deciding carefully where emerging technologies can genuinely improve discovery.

When digitization, metadata expertise, and technology are considered together from the outset, the result is more than a collection of digital files.

It becomes a resource that people can genuinely search, explore, and use.

### Key takeaways for making digital collections easier to discover

The most effective digital collections put discoverability at the heart of the digitization process.

That means:

- structuring metadata around how users actually search;
- using clear, consistent taxonomies and controlled vocabularies;
- keeping search experiences simple rather than adding unnecessary complexity;
- preserving valuable legacy metadata while controlling what is publicly visible;
- treating metadata as something that evolves alongside the collection;
- and using AI as a supporting tool, with human expertise providing context, accuracy, and judgment.

Ultimately, successful digital discovery depends on bringing **digitization, metadata, and user experience together**. When these elements are considered as part of the same strategy, archive collections become easier to search, explore, and use, helping organizations unlock more value from the material they preserve.

### Get in touch

For more insights into taxonomy, metadata, AI, and designing digital collections around the needs of their users, you can get in touch with us to learn more:

[TownsWeb Archiving](http://townswebarchiving.com) (digitization)

[PastView](http://pastview.com)(immersive online access and discovery platform)

[clemency.co.uk](http://clemency.co.uk)and<http://clemency.co.uk>[makesearchbetter.com](http://makesearchbetter.com)(UK’s leading provider of keywording services and consultancy)<http://makesearchbetter.com>

 

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