The value of the data at a particular time is called as a snapshot. This is used in temporal data.

Functional dependencies that have a time associated with them during which they are valid are called as temporal functional dependencies. All snapshots of the relation should satisfy the functional dependency for it to be a temporal functional dependency.

IF a system supports a native valid time type, then the system can detect and prevent overlapping time intervals.

Crosstabs may be useful for the users but they are not desirable in a database system because the queries would get more complicated due to the addition of cross tabs.

To specify the foreign keys in relations referencing temporal data we need to specify the time interval. The time interval specification thus preserves referential integrity in the relation.

Joining multiple relations together to form a single relation containing all the attributes is not a method for the development of good relational schema because it might violate the normal forms if it is combined.

The transaction time is the time of temporal data that records when a fact was recorded in a database.

Unique role assumption means that the attribute names must have unique meaning in the database. This prevents us from using the same attribute to mean different things in different schemas.

The data that have a time interval associated with them during which they are valid are called as Temporal data. We use the term snapshot to mean the value of the data at a particular point in time.

The process of making a normalized schema unnormalized is called as denormalization. Designers use it to tune performance of systems to support time-critical operations.