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Data Dictionary

In our data flow diagrams, we have given names to data flows, processes and data stores. Although the names are descriptive of the data, thy do not give details. So following the DFD, our interest is to build some structures place to keep details of the contents of data flows, processes and data stores. A data dictionary is a structured repository of data about data. It is a set of rigorous definitions of all DFD data elements and data structures.

To define the data structure, different notations are used. These are similar to the notations for regular expression. Essentially, besides sequence or composition ( represented by + ) selection and iteration are included. Selection ( represented by vertical bar "|" ) means one or the other, and repitition ( represented by "*" ) means one or more occurances.

The data dictionary for this DFD is shown below:

Weekly timesheet = Emplyee_Name + Employee_ID + {Regular_hours + overtime_hours}

Pay_rate = {Horly | Daily | Weekly} + Dollar_amount

Employee_Name = Last + First + Middle_Initial

Employee_ID = digit + digit + digit + digit

Most of the data flow in the DFD are specified here. Some of the most obvious ones are not shown here. The data dictionary entry for weekly timesheet specifies that this data flow is composed of three basic data entities - the employee name, employee ID and many occurrences of the two - tuple consisting of regular hours and overtime hours. The last entity represents the daily working hours of the worker. The data dictionay also contains entries for specifying the different elements of a data flow.

Once we have constructed a DFD and its associated data dictionary, we have to somehow verify that they are "correct". There can be no formal verification of a DFD, because what the DFD is modeling is not formally specify anywhere against which verification can be done. Human processes and rule of thumb must be used for verification. In addition to the walkthrough with the client, the analyst should look for common errors. Some common errors are

1. Unlabeled data flows.

2. Missing data flows: Information required by a process is not available.

3. Extraneous data flows: Some information is not bein used in the process

4. Consistency not maintained during refinement

5. Missing processes

6. Contains some control information

The DFDs should be carefully scrutinized to make sure that all the processes in the physical environment are shown in the DFD. It should also be ensured that none of the data flows is actually carrying control information.

Related Topics

• Functional Modeling Techniques
  Data Flow Diagrams
  Elements of Data Flow Diagrams - Processes, External Entities, Data Flow, Data Stores
  
• An Example of a DFD for a System That Pays Workers
• Conventions used when drawing DFD's
• DFD Example - General model of publisher's present ordering system
• Data Dictionary
• The procedure for producing a data flow diagram

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