The past two posts I’ve made to this blog have been about metadata, but I realized this morning that I haven’t really defined the term metadata here yet. I know, many of you understand the term, but I thought it’d make sense to put together a post defining metadata for those who need a more in-depth understanding.
Let’s start off by using an example that most folks will be familiar with. Have you ever watched the Antiques Roadshow program on television? In this show people bring items to professional antique dealers to have them examined and evaluated. The participants hope to learn that their items are long-lost treasures of immense value. The antique dealers always spend a lot of time talking to the owners about their items. They ask questions like “Where did you get this item?” and “What can you tell me about its history?” Now, the item is sitting right there in front of them, yet they ask these questions anyway. Why? The answer is metadata! These details provide knowledge about the authenticity and nature of the item. The dealer also carefully examines the item looking for markings and dates that provide clues to the item’s origin.
So, the item being evaluated by the Antiques Roadshow experts is the “data.” The answers to the antique dealer’s questions and the markings on the item are the “metadata.” Value is assigned to an item only after the metadata about that item is discovered and evaluated.
The typical off-the-cuff definition for metadata is usually something like “data about the data.” That might help to quickly bring about a high-level understanding of metadata, but it is not a very good definition. It is self-referential and doesn’t add much to our understanding. My friend Bob Seiner (publisher of TDAN.com) calls this a cheeseburger definition (that is, a cheeseburger is a burger with cheese).
Metadata characterizes data. It is used to provide documentation such that data can be understood and more readily consumed by your organization. Metadata answers the who, what, when, where, why, and how questions for users of the data.
Users of data must be able to put their data in context before the data becomes useful as information. Metadata describes data, providing information like data type, length, textual description, and other characteristics of the data. So, for example, metadata allows the user to know that the customer number is a five digit numeric field, whereas the data itself might be 53781.
The basic building block of knowledge is data. Data is a fact represented as an item or event out of context and with no relation to other things. Here are a few examples of data:
Without additional details we know nothing about any of these three pieces of data. Consider:
- Is 27 a number in base ten, or is it in octal (which would translate to 23 in base ten)?
- If 27 is a number in base ten what does it represent? Is it an age, a dollar amount, an IQ, a shoe size, or something else entirely?
- What about 010110? Is it a binary number? Or is it a representation of a date, perhaps January 1, 1910? January 1, 2010? Or something else entirely?
- Finally, what does JAN represent? Is it a woman’s name (or a man’s name)? Or does it represent the first month of the year? Or perhaps it is something else entirely?
All of these are examples of data because of the lack of context. Information, on the other hand, adds context through relationships between data, and possibly other information. Data in context with metadata makes information. The relationships may represent information, yet the relations do not actually constitute information until they are understood. Also, the relationships that represent data have a tendency to be limited in context, mostly about the past or present, with little if any implication for the future.
Webster’s New Collegiate Dictionary defines knowledge as “the fact or condition of knowing something with familiarity gained through experience or association.” Knowledge adds understanding and retention to information. It is the next natural progression after information. To have “knowledge” requires information in conjunction with patterns between data, information, and other knowledge. So knowledge couples data with understanding and cognition.
The final step would be to move from knowledge to wisdom. Wisdom can be thought of as knowledge applied. You may have the knowledge that fatty foods are bad for you, but if you eat it anyway, you are not wise.
So… In order for data to be anything more than simply data, metadata is required. Without metadata, data has no identifiable meaning — it is merely a collection of digits, characters, or bits. Metadata gives data its form and makes it usable by information professionals.