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Understanding metadata Renée Register
Metadata is … a set of data that describes and gives information about other data …  WHAT IS METADATA? yikes! Not much help, right? Metadata is used to describe the context, content and structure of materials. Metadata is … a file of information, which captures the basic characteristics of a data or information resource. It represents the who, what, when, where, why and how of the resource. ... Metadata means data about data. Metadata is … information about a piece of content. Metadata describes other data. It provides information about a certain item's content.
LET’S TALK ABOUT SHOES!
BASIC PRODUCT METADATA Company:	Stuart Weitzman Name: 		Curling SKU:	#7793281 Color:	Bordo Suede Price:	$495.00 Size:		Choose a size Width:		M Product image
BUT HOW DID WE FIND THE ITEM?
OTHER METADATANARROWS THE SEARCH
CORE AND MORE METADATA
BASIC METADATA Shoes and Books BOOKS Product image Publisher Title ISBN Price Product form Subject/Genre SHOES Product Image Company Name SKU Price Color, Size, Material, Width, Heel height, etc. Styles, Occasion, etc.
CORE BOOK METADATA 31 Core Data Elements  From BISG Product Metadata Best Practices ,[object Object]
ONIX Audience Code
Age Range of Target Audience
Case Pack / Carton Quantity

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Understanding Metadata

Hinweis der Redaktion

  1. Most of the definitions of metadata don’t tell you much about practical usage. Why do we need it? What are the basic building blocks and standards that should be used? How do we create, use, maintain, and distribute it? Who in an organization should be responsible for it? This just makes my head hurt! Let’s look at metadata in a way that’s less abstract and turn to one of my favorite subjects ….
  2. Everything on this page is metadata or is driven by metadata -- designed to help you find the shoes you want. Behind the scenes, someone has applied appropriate metadata to each pair of shoes and it’s been indexed to allow the user to narrow the search or to just browse within certain categories. Better than looking at 38,000 + pictures of shoes! “Women – Shoes” is an example of a very broad category that doesn’t help much. I really don’t want to browse over 38,000 items! If I knew exactly what I wanted by name or product identifier, I could probably just type it in search. But if I have that info, I’ve already discovered what I want somewhere else.
  3. Let’s jump ahead for a moment and assume we’ve found the item we want. Some of the basic or ”core” metadata elements for shoes can be found on the item level page. Available size and width are displayed in the drop-down boxes. Image once could be considered an enhanced metadata element but these days it’s so expected that users may even skip over products lacking an image.
  4. First we had to pick the broad type of product that we want – Women’s Shoes. When we pick boots under women’s shoes, we’ve gone from 38,059 items to 7,017 and the options expand to allow us to choose size, width, and other things we want – other data elements.Shoes could be comparable to the books section of a website with many types of products. Choosing “women” is comparable to choosing an “audience”, e.g. childrens’ books, etc. It’s generally assumed that the audience is adult unless otherwise indicated. Choosing boots after going to shoes is somewhat comparable to a BISAC heading of Fiction – General. But the scale – the number of items – will be much, much larger.
  5. If we narrow boots to “ankle” boots, the options change to show metadata applicable to that category and the number or items to view gets smaller. We can see how this would be true for books as well. Metadata applicable to an audio or eBook won’t all be the same as for print. In this slide, I’ve already narrowed by size and width. We can then continue to narrow by material, price, color, etc. Notice how many options there are! And I haven’t displayed all of them here. Keep in mind that this metadata has to be applied to each individual record/item in order for this to work.The options change as you narrow – not categories will have the same options. At this point we can see the number of selections. Through each step you can scroll through images that have brief metadata attached. Notice the stars when there are user reviews. Reviews are a good example of enhanced data. They don’t exactly describe the item in objective terms but expose people’s reactions to the item. They bring a more emotional context.
  6. Product information includes some of the same data used for selection. Other data appears only in the description: leather lining, stylish overlays, wrapped heel, Made in Spain, etc. If your system or your partner’s system doesn’t have a bucket for the data, it won’t show up anywhere except for in a text description. Also, some data must be normalized according to industry standards in order to work. For example, do you express inches in heel height? Should it be in no period, in., inches spelled out? Or maybe your words need to be translated to a standard vocabulary – Bordo Suede is translated to burgundy in the features list we used to get to this item.Keep in mind that if you have a wonderful free-text description of an item it still doesn’t replace getting the right metadata in the right bucket.Also, notice that the color description here doesn’t match the vocabulary in the search – bordo suede – red/burgundy. That info about these shoes has to have been entered somewhere else behind the scenes and can’t have been indexed from the info here.
  7. So let’s compare shoes to books more directly. Some basic (or core) metadata elements are pretty obvious, even across multiple product types. Here we can see metadata that is comparable across shoes and books. Of course some will be specific to the product – a shoe doesn’t have an author. But it could have a contributor such as a designer. Or the company and the designer could be synonymous.
  8. Let’s go back to books. How do we know what our “buckets” are? Some data elements are no-brainers: title, price, etc. Others not so much. Industry standards developed over years serve as a guide. To effectively share or display information about your book you have to organize it and transmit it in a way that makes sense to the systems that hold and “read” it. Behind that scenes, this metadata drives both web-based search and the algorithms that can expose such things as forthcoming mysteries, bios, recommendations (if you like this …), etc. The “magic” is only as good as the tools behind it.It’s also crucial to buy/sell business functions and the reporting that is needed throughout the life of a title.Some of these metadata elements are mandatory for all product records; some are recommended as core elements only when applicable. For example, not all books will be part of a series. eBooks won’t have a binding but they will have a format. A few that are mandatory for print may not apply to digital, e.g. case pack/carton qty.
  9. The publishing cycle can be fairly long from decision to publish to published works. It’s important to get your metadata as good as possible as soon as possible but it’s very important to be able to add and change metadata within your own system and to share that with your trading partners. A lot of important information that enhances your product data occurs after publication: reviews, awards, customer feedback, etc.
  10. All of these are questions are important. As you may have noticed in the core elements, some of the metadata is never seen or explicitly used by the consumer. It serves the buying and selling needs of the supply chain. It supports business needs and business intelligence for your organization and those of your supply chain partners. I hope this presentation has been helpful as a VERY brief introduction to metadata. There are many resources available to help you make metadata decisions for your organization or for your authors.Even some of the metadata exposed to end-users may not be explicitly “used” by them but supports the way content is displayed to them for potential selection. It may also drive business-to-business purchases by libraries and others through the creation of lists used for selection.