DAM News Round-Up – 14th March 2022
A selection of DAM and marketing technology related articles from around the web.
Further to a recent article by DAM provider Tenovos, DAM News Editor Ralph Windsor discusses the pros and cons of the recent Forrester ‘Wave’ report, and a number of issues and shortcomings to be aware of when interpreting its analysis of the DAM vendor landscape. A key area for debate is the often opaque language used in the report, and how factors such as strategic vision and profitability are often favoured over more practical information about any given platform. Ralph concludes that, as ever, it’s crucial to tailor your own research – from multiple sources – based on your organisation’s specific needs.
Digital Asset Management software provider Tandem Vault has recently announced a number of updates to its TV3 platform. Two new Artificial Intelligence services have been introduced: bulk autotagging with Amazon’s Rekognition service (I’m glad to see they’re up-front with its limitations, admitting that it “can make some amusing mistakes”), and a corresponding NSFW (not safe for work) tagging for more sensitive or adult-oriented content such as nudity, violence, drugs, tobacco, alcohol, and gambling etc. Other updates include a like/dislike button, the ability to set an expiry date on shared lightboxes, and a new workflow interface.
Continuing with the DAM News Interview series, this week’s subject is Commercial Director of DAM vendor Aetopia, Stephen McAreavey. Discussing a broad range of DAM topics, Stephen offers up some sound advice on preparing and planning for a new DAM implementation, the importance of understanding the nature of your assets and their usage, being sensitive to your users’ needs, and how being able to see the bigger picture can turn a simple storage solution into a core feature of your business operations.
Paul Bischoff, Editor at pro-consumer research website Comparitech, highlights the potential security risks lurking within image metadata, commonly known as EXIF (although other metadata schemas and systems also exist, including IPTC and Dublin Core). Paul breaks down the different categories of metadata into three main groups: system, substantive, and embedded, along with a typical use case for each. Of more interest is the privacy issues that he raises, and by providing a number of examples demonstrates just how much personal information can be gleaned or ‘scraped’ from random photographs found online. Advice is also given on how to strip metadata from images, although as we’ve discussed in a previous article, the automatic wholesale removal of metadata that occurs when uploading images to social media can often discard valuable attributes such as copyright and licensing, in turn severing the connection between creators and their work, and thus a potential source of royalty-based revenue.
Continuing with the theme of metadata, this recent blog post from Digital Asset Management software provider MediaValet provides five tips for improving your metadata model. With a basic overview of what constitutes a metadata model, advice includes consulting with the subject matter experts among your ranks to gain a broad-brush idea of your taxonomy and categories, auditing your existing assets to see what’s missing, and governance tips to ensure metadata practices and responsibilities are observed and consistency is maintained.Share this Article: