How to Manage an Image Database (with Thousands of Assets)

Brands and organizations that manage thousands of images need a straightforward, consistent process for storing and locating relevant assets when required.

Otherwise, team members waste valuable time tracking misplaced images and sifting through hundreds of folders stored on cloud storage solutions.

Most images display thumbnails that can help a little, but thumbnails do not always tell the whole story. Typically it is necessary to open several image files to view them in full before the precise image is found.

Moreover, it is getting worse.

54% of US office professionals report wasting time searching for much-needed files in cluttered online filing systems. The research also noted that another 57% of office professionals said a quick search for files and documents is a "top-three problem."

It’s no wonder that we spend, on average, more than 4 hours per week searching for the right assets.

However, it does not have to be that way.

With a digital asset management software like Digizuite, teams can manage a complex but user-friendly image database that makes adding and storing images easier; teams can retrieve the images they need in seconds.

To help avoid the frustrating search for images, we have curated the best tips and practices for managing images at scale.

Choose the right digital asset management system

The first and most crucial step in managing an image database is to choose the right DAM system.

Digital asset management software allows users to organize, edit, and share images and other digital assets from one central source – with other valuable features to make images easily searchable and retrievable.

A powerful DAM provides brands with a way stakeholders can access them any place, any time, and anywhere.

In addition, you can easily distribute assets directly to digital channels within the platform.

This maintains global brand consistency across hundreds of products in different regions, industries, and multiple sales and distribution channels - leading to an increase in revenue by 10-20%.

Use a systematic way of naming images

Now, what about the image files themselves?

Consistent file naming conventions are necessary whether using a folder-based organization system or a sophisticated database.

  • Image file names should meet three essential criteria:

    • be unique

    • be descriptive

    • be organized around a date

    • and above all, be consistent

Typically this requires creating a set of written file naming rules that every team member must adhere to when adding new images to a DAM.

 An example would be the following:

Start with dating assets before adding an image name. By doing this, you will be aligning the metadata and making it easier to understand when the asset was taken or added. 

If you want to use a form of file naming, remember to start with the year, then the month, and then the day. So if photos are added on September 8th, 2022, the file should begin with a date like: 2022-09-08 or 2022.09.08

Consider this: Suppose image files are named with the date first, followed by the location or subject, and others are labeled starting with the subject first. In that case, images become scattered around the database or folder rather than in numerical chronological order.

Naming files should always be consistent, using the same format, for example, Date-Location-Subject. There are rules to apply to how dates are formatted in file names.

Although please note that there are tens of variations to consider and possible data to incorporate into image file data after data and location, like:

> Event (if relevant)

> Photographer identifier (initials, last name) if relevant

> Client's name

> Campaign name

> Product name

> Camera identifier

> Version

> Size

Choose a few aspects that make sense for your image library and needs. Remember that much of this data can be included as image metadata, so consistency is the primary consideration when establishing image file naming conventions.

Use consistent metadata rules

Using consistent metadata rules is about creating a process that allows attaching metadata to digital assets, whether manual or automated, using a DAM.

Embedding metadata into every asset optimizes images for searching, retrieving, creation and distribution. In other words, companies must infuse every element of their assets with metadata to deliver a consistent brand experience on demand.

Moreover, while this process is an extra, time-consuming step, there is a secret to making it as simple as possible.

Metadata tagging is automated if a company uses a DAM designed to add and store digital assets only after they have been tagged with metadata fields.

Metadata tagging is a key feature of using a DAM, making it feasible to search and retrieve images needed, regardless of the number of images or how big the company becomes.

Three types of metadata final

There are three main types of metadata: descriptive, administrative, and descriptive, all of which contain information that describes an image or other asset.

> Descriptive metadata are the keywords and fields needed to search and filter through stored digital assets.

> Administrative metadata ensures proper usage of every digital asset. It helps brands manage the entire lifecycle of digital assets and images.

> Technical metadata is the technical elements of the picture. These metadata fields and values include file type, dimensions, and resolution.

  • Other metadata could include:

    • Captions

    • Keywords

    • Date who created an image

    • Date who added an image to the DAM

    • Location of where the picture was taken

    • Camera model and manufacturer

    • Photographer's name

    • Editor's name

    • Subject matter

    • Client name

    • People's names from the image

    • Campaign name

    • Version

    • Usage rights information

Naturally, there could be tens of other metadata tags and keywords. Whatever you decide, ensure that all criteria are applied to every image.

Ensure image versions are noted

Version control is an essential feature in any DAM or image database software. Noting down image versions or using version control will avoid costly and embarrassing mishaps like:

> Posting unprofessional images of staff and team members (like at the office party)

> Using images featuring product names that have since been removed or amended

> Distributing an asset with old company branding or wrong data (like expiring sales campaigns)

> Using older images that are no longer relevant in today's societal attitudes (for example, objectifying images of a particular gender)

Furthermore, images go through several rounds of editing and approval through design, management, and legal teams.

Version control ensures that each team accesses only the most recent, relevant, and approved image iterations. While creative designers and content creators have access to all versions, allowing them to revert to previous versions can be useful if part of that digital image needs retrieving or amending.

Asset history in Digizuite DAM

Ultimately, version control prevents brands and organizations from releasing non-approved images for public consumption.

Are you using a DAM Platform to manage images?

Managing one hundred assets is no easy feat.

Managing thousands of assets is a whole other story.

These tips and best practices will help you build a user-friendly, optimized and functional image database that people can use to quickly locate and use the images they need, in seconds, rather than hours.

Best of all, they will avoid the time-consuming and costly process of recreating existing images because your team cannot locate them.

Of course, there’s a better way to organize assets at scale.

One way is to implement a powerful DAM solution like Digizuite.

Want to understand how Digizuite can help you manage your image database?

Book a demo today, and a Digizuite expert will walk you through the software and discuss your asset organization needs.

 
Lisa Grimm

Lisa Grimm

Lisa Grimm has been directing DAM, taxonomy and content programs in the US and Europe since the mid-1990s, for companies, museums and archives large and small, including Women.com, Nature Publishing Group, Drexel University College of Medicine, Elsevier, GSK, Amazon, Novartis and many more.

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