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Taxonomy is the part of science that focuses on naming and classifying or grouping organisms. Swedish naturalist, Carl Linnaeus, developed the current hierarchical classification system of taxonomic classification in the 1700s. This classification is hierarchical so one class has many orders, and one order has many families.
Birds can be classified under the Linnaean hierarchical taxonomy as "Aves". In one system of classification, Aves has 23 orders, one of which is the order Ciconiiformes, which holds six families within it.
Spoonbills constitute one of the families within the order Ciconiiformes. Data can be collected about spoonbills, such as length of the bill or beak, and is included in the database.
Outline, using an example, how data verification can ensure that data is entered into the birds database correctly.
Method #1
Data verification can ensure that data is entered into the birds database correctly through:
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Double entry
1 mark - Data is entered twice
- The system will only allow data entry if both entries match, ensuring accuracy
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Proof reading
1 mark - Provides a visual check that the data is correct before submission
- Allows the user to identify and correct any errors
Identify two characteristics of a conceptual schema.
Identify two characteristics of a conceptual schema.
- A high-level / overall / general view of the database
1 mark - Shows the main concepts
1 mark
Distinguish between data and information when entering the length of a spoonbill’s beak in the database.
Data vs Information
- When the length of the bill/beak of the spoonbill is measured, it is simply a decontextualized figure such as 10 cm, which is considered data.
- When it is included in the database and interrogated, it will have a meaning, so it then becomes information.
Alternative:
- The database will contain only the figure "10" as data.
- The "cm" will not be included in the database and is part of the meaning/context of the attribute/field, making it information.
Explain, using the example described in the scenario, why referential integrity is important in databases.
Explain, using the example described in the scenario, why referential integrity is important in databases.
Referential integrity ensures that relationships between tables in a database are maintained and consistent. In the context of the birds database, referential integrity is important for the following reasons:
- It requires that a value used as a foreign key (e.g., the order ID for a bird species) corresponds to a valid value of a primary key in the related table (e.g., the order table).
1 mark - Therefore, if the order "Ciconiiformes" (the order to which the spoonbill belongs) is not present in the orders table, you will not be able to add the spoonbill record because of referential integrity constraints.
1 mark
Explain why the use of data modelling is critical to the success of a database, such as the one used in this scenario.
Method #1
Data modelling gives a visual representation of the proposed system;
Method #2
The data model will take the information from the conceptual schema and logical schema to informs the physical model for the development of the database;
Outline, using an example, how data validation can ensure that data is entered into the birds database correctly.
Method #1
Data validation can ensure that data is entered into the birds database correctly by using:
- Length check
- This could ensure only a value within an acceptable range is entered for the length of a spoonbill's beak (e.g. between 10 cm and 20 cm)
- Type/format check on bill length
- This would only allow numerical values (integer or float) to be entered for the bill length field
