# Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface
## 2 sdcApp
### Anonymize
#### 2.3.2 View/Analyze the SDC Instance  
The first part of the left navigation sidebar labeled View/Analyze existing sdcProblem allows to select from four different features which are summarized in Table 4.  
In the Show Summary-view, the SDC problem is summarized by showing the most important (key) variables of the problem and some statistics, such as the number of suppressed values for each categorical key variable. Furthermore, a table showing the number and percentages of records violating \(k\)-anonymity [12; 13] for \(k\) of 2, 3, and 5 is displayed both for the current problem as well as for the initial problem to which no anonymization procedures have been applied. The user is also presented with information about risk in numerical key variables if any have been defined. In this case, additional tables show the estimated minimal and maximum risk for numeric key variables for both the original and the (possibly) modified continuous key variables as well as measures of information loss. Specifically, measures IL1s[14] and the Difference of Eigenvalues[15] are shown for both the original and (possibly) modified variables. If numeric key variables have been modified, a table containing the six-number summary (identically to the one on the right-hand side below the plot in the page when the problem was defined, see \"Defining a SDC problem\" in Section 2.3.1) for each the unmodified variable from the micro-dataset and the perturbed variable. Finally, at the bottom all the anonymization procedures that have already been applied are listed.  
Clicking on Explore variables allows to explore all variables in their current state. The functionality is exactly the same as it was already described in Modify and analyze microdata (see Section 2.2.2) for original microdata. The only difference being that the analyzed variables are now those from the current SDC problem. The other two features in this section are modifying the SDC problem.  
Using Add linked variables it is possible to connect a set of variables to a specific categorical key variable. This variable then serves as a \"donor variable. This means that after the anonymization process, all suppressions of the donor variable will be transferred to the variables linked to it.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Feature** & **Description** \\ \hline Show Summary & gives an overview about the current problem instance \\ Explore variables & analyze the current state of variables in the SDC problem \\ Add linked variables & connect variables \\ Create new IDs & create random identifying variables \\ \hline \hline \end{tabular}
\end{table}
Table 4: Analyze/view the statistical disclosure control (SDC) problem instance.  
Sometimes it is useful to create a new random identifying variable. Therefore, this task can also be performed within the GUI by clicking on the link \"Create new IDs\". After specifying a new variable name and optionally a variables that serves as grouping variable (the new variable will have random, but common values for each value of the grouping variable), the new variable can be created by clicking on a button labeled Add new ID variable which appears at the bottom of the page. After the variable has been created, the page switches to the Show Summary view.