Attributes and Values
Describing Entities
Metadata
At the most basic level, metadata is just another
term for description, or information about an
entity.
In creating a descriptive schema, you are
creating a template for assigning metadata to a
particular group of items in a structured way.
Attributes and values
Attributes—also known as characteristics,
properties, or elements—are the categories we
use to describe a specific kind of entity more
precisely.
Values are a way to describe the possible
contents of an attribute.
Slide 3
Examples of attribute/value pairs
These metadata elements for automobiles would
seem familiar to many of us:
Attribute
Make
Model
Trim line
Year
Value
The name of the company that
produced the car (Toyota)
The product line or brand (Camry)
Model variation (SE)
The year the car was produced, in
YYYY format (2007)
Slide 4
Examples of attribute/value pairs
These metadata elements for wine would seem
familiar to many of us:
Attribute
Value
Country of origin
The name of country where the wine
was produced (France)
Region of origin
An area within the country of
production (Bordeaux)
Color
The overall tint (red)
Vintage
The year wine was made, in
YYYY format (2007)
Slide 5
More examples of attribute/value pairs
Attribute/value pairs that might enable more exploitative
control for cars could be something like:
Attribute
Value
Envy quotient
How much will others be jealous of my
sweet ride, on a scale of 1-10?
Carelessness negation
To what degree can one blow off regular
maintenance without having a
breakdown, on a scale of 1-10?
Commuter fatigue
How will you feel about the car after
driving it 25 miles each day, in
traffic (love car, hate car, indifferent
to car, don’t know just need a drink)
Slide 6
More examples of attribute/value pairs
Attribute/value pairs that might enable more exploitative
control for wine could be something like:
Attribute
Cuisines
Friendliness
Character
Value
With what styles of food will this wine go
best?
What percentage of guests at
my family barbecue will like this
wine?
Which term best describes this wine (silky,
bold, lush, succulent, opulent, zesty)?
Slide 7
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).
Slide 8
Dublin Core: a schema
The Dublin Core is a metadata schema for describing
(primarily) information resources. It includes a set of
elements (attributes) and associated value parameters.
A goal of Dublin Core is to provide a simple set of
standard attributes that apply to most documents. By
making it easy to comply with Dublin Core standards,
interoperability of metadata between different
collections may be facilitated.
Slide 9
Dublin Core elements (attributes)
Dublin Core includes 15 basic elements. When assigning
metadata to resources, all elements are optional and repeatable.
Some elements can be refined. For example, Abstract is a
refinement of the Dublin Core Description element, making the
element more specific.
To support the interoperability goal, metadata authors must
assume that refinements may be “dumbed down” if systems don’t
support them. That is, an Abstract element may be mapped back
to a Description element.
Slide 10
Dublin Core values
It is recommended that values for many Dublin come from
controlled vocabularies. The CDP guidelines recommend specific
vocabularies for different elements (such as the “DCMIType
vocabulary” for the Type element).
For example, the creator of metadata for a particular collection
might specify that values for the Subject element must be selected
from the Library of Congress Subject Headings (LCSH) and not
by entering free keywords.
Slide 11
Metadata for people,
metadata for computers
The “audience” for Dublin Core (or any other) metadata
may be a person, or it may be a computer, using the
metadata to facilitate search or do other processing.
Slide 12
Dublin Core element descriptions
The CDP guidelines provide an example of how Dublin
Core elements have been interpreted for a particular set
of institutions and their common project goals of
providing access to digitized materials.
You may find this format useful in thinking about how
to create similar descriptions and guidelines for your
schema assignment.
Slide 13
Dublin Core Title element
Label: Title
Dublin Core definition: The name given to the resource.
Dublin Core comment: Typically, a Title will be a name by which the resource is
formally known.
CDP comment: The name given by the creator or publisher; may also be an identifying
phrase or name supplied by the contributing institution.
Examples:
Title=”Oral history interview with John Schulz"
Title=”Untitled"
Slide 14
Dublin Core Type element
A cautionary tale
Label:
Resource Type
Dublin Core Description:
The nature or genre of the content of the resource.
Dublin Core comment:
Type includes terms describing general categories, functions, genres, or aggregation levels for content.
Recommended best practice is to select a value from a controlled vocabulary (for example, the DCMIType
vocabulary). To describe the physical or digital manifestation of the resource, use the Format element.
CDP comment:
Use only the DCMIType vocabulary.
Examples:
Type=”Moving image"
Type="Sound"
Type="Text"
Type=”Collection”
Slide 15
Summary
• A schema is a set of attributes to describe a defined group of
entities, along with associated value parameters and usage
guidelines. We use the schema to produce metadata records that
describe specific objects.
• Dublin Core is a schema for describing information resources in
a way that facilitates semantic interoperability between metadata
systems.
• Defining attributes in a way that makes it clear how to create
records with them can be quite challenging, even for seemingly
basic descriptive attributes.
Slide 16
Some examples
A data model for biomedical resources: Eagle-i
Aggregations of cultural heritage data that
incorporate Dublin Core in their data models:
DPLA and Europeana
Slide 17