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Metadata

Metadata. Information about information. What is the information here?. Say we have part of a data set: 9 5 7 31 31 18 17 What do these numbers signify? Without additional information about the information, we have no idea. What is the information here?. Say we have some text:

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Metadata

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  1. Metadata Information about information

  2. What is the information here? Say we have part of a data set: 9 5 7 31 31 18 17 What do these numbers signify? Without additional information about the information, we have no idea.

  3. What is the information here? Say we have some text: I have something to say to you -- a word in your ear! I greet you -- please pay attention! In my city people are dying, and hearts are full of distress. People are lost -- that fills me with (1 ms. adds wretched) dismay. I craned my neck over the city wall: corpses in the water make the river almost overflow. That is what I see. That will happen to me too -- that is the way things go. No one is tall enough to reach heaven; no one can reach wide enough to stretch over the mountains. Since a man cannot pass beyond the final end of life, I want to set off into the mountains, to establish my renown there. Where renown can be established there, I will establish my renown; and where no renown can be established there, I shall establish the renown of the gods. Without additional information about the information, the significance of this text is unclear.

  4. Metadata At the most basic level, metadata is just another term for description, or information about an entity. For example, I open my dresser drawer and take out a sock: the sock color of the sock is white, material is cotton, and the length goes to my ankle.

  5. Structured metadata Attributes—also known as characteristics, properties, or elements—are the categories we use to describe a specific kind of entity more precisely. Color, material, and length are attributes of socks. Values are a way to describe the possible contents of an attribute. White, cotton, and ankle are values of the Color, Material, and Length attributes.

  6. Unstructured metadata We can also just apply values (tags) to entities without specifiying attributes. The metadata for a sock might then be: white cotton ankle

  7. Problems with unstructured metadata What if my socks are tagged: Hot Normal Are my socks reeeaaally stylish and yet also utterly typical?

  8. Examples of attribute/value pairs For socks, attribute/value pairs might be: Attribute Value Color One of a set of 128 color values (white) Material One of a set of 15 fibers (cotton) Length One of a set of 5 lengths (ankle) The values here are controlled, or limited to a defined set of acceptable choices. Control can facilitate consistency.

  9. More examples of attribute/value pairs For restaurants to which I might consider taking visitors to Austin, potential attribute/value pairs might be: Attribute Value Sense of place A scale from 1-10 to represent the restaurant’s uniqueness as an Austin or Texas experience Grease quotient The number of margaritas required to cut through the richness of the food Ease of transport A percentage that represents the likelihood that I can get us there, park, and get us home without harming us, others, or property Thinking ahead to Wilson’s two kinds of power, the Web site attributes from the previous slide are very much descriptive. They help me to specify an existing item that I know about. But attributes, as we have seen, can also be optimized for a specific context. of course, while these exploitative attributes might be very useful, they are also limited to a very particular situation and may be quite difficult to define in a way that can be easily operationalized, in other words, where I can explain to other potential contributors of resources and metadata what the attributes mean and how the values should be assigned. So in many cases we likely want attributes that represent some middle ground between these two examples. However, don’t dismiss the potential usefulness of “subjective” attributes and values like this. This is where things get interesting. This is where I might actually learn something that I didn’t know before, or at least get an idea of what other people think, even if I decide that I don’t agree. The challenge with these is to define the value space precisely enough that people using the schema--and by that I mean people adding new instances, or new descriptions, as well as people reading the descriptions--can get a reasonable idea of what I mean when I say something like “grease quotient” and that these values can be used to consistently and coherently differentiate between the entities described.

  10. Schemas, or attribute sets A schema is a set of attributes and associated value parameters designed to describe a particular type of entity. Schemas may be encoded in a particular syntax for manipulation by people or computers. Schemas may also be associated with rules for creating records (that is, assigning attributes and values to specific resources).

  11. Types of metadata Gilliland defines five types of metadata: Administrative. Descriptive. Preservation. Technical. Use.

  12. Conflicting purposes for structured metadata Structured metadata can facilitate both exploitative and descriptive control, to use Wilson’s terminology. It can also facilitate interoperability. These goals may be at cross-purposes sometimes...

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