In this section we go into some of the details of explaining the entity relationship diagram used to depict the Cadastral Data Content Standard. This involves defining such things as entities, attributes, associations (relationships), cardinality, and keys.
By investigating this page and the following pages, you can begin to gain a good understanding of how to read the entity relationship diagram.
Why is this important? When its time for you to do such things as organize a new cadastral database, restructure an existing cadastral database, or work out ways to translate your own data to the Standard, it will be very useful to understand the Cadastral Data Content Standard's entity relationship diagram, and relate that understanding to the relationships within your own data. It will also help immensely when working out ways to exchange your data with others.
The entity relationship diagram illustrates three components of an object definition: Entities, Associations, and Cardinality.
A data entity is any object about which an organization chooses to collect data.
Attributes are additional information which describe an entity. Entities and their attributes are defined in a data dictionary.
Data entities are shown in boxes on the entity relationship diagram. In the Cadastral Data Content Standard the entity name is underlined and is the first item listed in the box, as shown below for an entity known as "Legal Area Description."
The entity's attributes are listed below the entity name. The entities and their attributes are defined in Part 3 of the Standard.
Associations (also known as relationships) describe how data entities are related to each other. The associations in the data model for this Standard are: one-to-one, one-to-many, and many-to-many.
One-to-one association (1:1) means that at a point in time a given value of A has one and only one value of B. For example, one person has one social security number. The person and their social security number is a one-to-one association. Most one-to-one associations are described as a unique attribute of an entity.
One-to-many association (1:m) means that item A could have an arbitrary number of items C associated with it. For example, a geodetic control mark may have many names or mark identifiers, such as the name stamped on the cap and location identifiers in a database. In this case the geodetic mark has a one-to-many association with its names and identifiers.
Many-to-many associations (m:m) occur when at a point in time a given value is associated with many other values and the converse is also true. For example, one parcel can be located in many administrative districts such as fire, police, school, and emergency response. Conversely, one administrative district is composed of many parcels. Click the green forward arrow below to see Figure 2-1 which illustrates the three associations described above.
Learning the Cadastral Data Content Standard
Presented by the United States Department of the Interior Bureau of Land Management, and
the Federal Geographic Data Committee Cadastral Subcommittee