Master data contains the basic characteristics of a panelist as specified by the panel administrator. It is stored independently from projects and is permanently available, e.g. for evaluation purposes or for creating subpanels (“groups”).

Before you start

Please mind:

Up to at most 2,800 master data per installation can be created.
The maximum number of master data which are available on a specific installation depends on various factors, as e.g. type and size of the master data created, the content stored in them and the number of characteristics. The maximum number of available master data may be lower than 2,800.
In particular, it is recommended to use not more than 300 master data of type “Text”, and to carefully select the smallest possible size range for these. Text variables need considerably more storage space than other types. Therefore, if you use more text variables, both the available storage space and the maximum number of variables which can be created will get smaller.
The number of master data affects the performance of the panel. The higher the numbers, the slower the panel installation will be. If any master data are not needed anymore, make sure to export and store the values contained therein and then delete the redundant variables.
The consistency of master data is of fundamental importance for your panel. Therefore, only one change process can be executed at a time (e.g. creation of a new master data, change of data type or size, deletion or automated creation in context of master data allocation). If you try to trigger a change while another process is still running (e.g. started by another user), EFS will ask you to repeat the action at a later date.

Master Data Overview

If you open the People → Master data menu, an overview of all existing master data is opened. The table contains the following information for each master data variable:

Variable: Variable name.
Title: This column contains the names of the master data. Clicking on a title will open the entry form in which you can edit the respective master data item. Tips on choosing titles are given in the “Master data nomenclature” section below.
Variable type: The following variable types are available:
– Standard: Master data that was manually created or generated by import.
– Recoded: Master data that was generated by recoding.
Data type: Indicates which type of data can be saved in the master data item.
Characteristics: The number of characteristics (answer categories) relating to master data of the type “Integer”. When you scroll with the mouse over the question mark icon, the characteristics will be listed in a popup window.
Created: Creation date.
Last change: The date of the last change.
Category: Master data can be sorted by categories in order to make them more
manageable.
Survey allocations: The existing survey allocations of each master data are listed. By clicking on the number of allocations you will get to a list of the allocated surveys.
Only in panels with Social Insight Connect: SINC allocations: The existing SINC allocations are listed as well. By clicking on the number of allocations you will get to a list of the allocated language versions.

The contents of the overview can be exported. Excel and CSV export is available, as usual.

Display

By default, the master data are displayed in the preset order. You can change the sort order of the table, though, by clicking on the column headers.

The View function allows you to display or hide table columns as required.

As usual, simple and extended search are available as well. Using extended search, you can search the list for a variable name or title, you can restrict it to master data with a specific data type or master data assigned to a specific master data category.

Actions

The following actions may be applied to individual, multiple, or all master data:

Add to category: Makes it easier to assign master data to a particular master data category.
Delete: Initiates the process for removal of master data.

In order to apply an action, first tick the “Actions” checkbox of the relevant master data, then select the desired action from the drop-down list and confirm with Execute.

Alternatively, you can also use the options “Mark all master data on this page” or “Mark all master data found”.

Creating New Master Data

There are different ways to create new master data:

Manually: This process is explained below.
By mass import: This process is suitable for creating several new entries in the master data, especially when a list of the desired master data already exists, e.g. in MS Excel.
Automatically when allocating project variables and master data variables.

Creating master data manually

Clicking on the Create master data button will open the entry form that allows you to create new master data.

Enter the variable name. It must start with m_ or md_ and must not exceed 20 characters in length. If you do not specify a variable name, a variable name will automatically be assigned by the system.
Enter the title.

Information

For panels that have a registration form and for large panels with a lot of master data, it is recommended that you draw up a nomenclature to improve clarity.

Select the master data type and size range.
Select the appropriate master data category.
Confirm by clicking on Create.

Creating answer categories for master data of the “Integer” type

For master data of the “Integer” type, further steps are required to complete the operation:

Answer categories must be created. Please proceed as follows:

After saving, the section for creating the answer categories will be displayed. Enter the first answer category (in the example shown, code = 1, answer category = yes) in the line “New”.
Confirm by clicking on Save.
Enter the second answer category (in the example shown, code = 2, answer category = “no”) and confirm by clicking on Save.
Check the result in the Master data codebook: The master data variable titled “Smoker” will appear there with the different answer categories and codes.

If you want to modify or expand the answer categories at a later stage, first open the edit dialog of the master data item, then click on Edit answer categories to open the modifiable input fields.

Information

If you are creating a large number of answer categories or need the same answer categories for several master data questions, it is recommended that you use the Mass-import answer categories function.

Sorting Master Data by Categories

You can sort master data by categories in order to make them more manageable, especially in panels with large amounts of master data.

Managing master data categories

The dialog for managing the master data categories is opened via the Manage categories button in the master data overview.

The overview table lists all existing categories, including their IDs, titles, descriptions and number of assigned master data. In a new panel, there’s only a “Default” category, which cannot be deleted. All master data are assigned to it per default.

Via the Create category button, you can open a dialog which allows to create new categories. All you need to enter is category title and description.

To edit existing categories, use the icons in the “Actions” column:

Edit category [Name]: You can change the title and description of a category, via the same dialog that was used for creating the category.
Delete category [Name]: If you click on the icon and confirm the pop-up message that follows, the respective category will be removed.

Assigning master data to categories

You can assign master data to categories

via the „Assign category“ action in the master data overview. This is recommended if you want to assign several master data at once.
via the editing dialog of a master data. This is recommended if you want to change the assignment of a specific master data.

Quick Changes to Master Data Labels

The labeling of master data is done to aid internal orientation: Whenever you work with master data, e.g. when defining a master data filter or a quota, labels will be output in the codebook and export function.

The quick change function allows you to change the labeling of your master data variables quickly and easily. This is particularly helpful if you have created your master data automatically, when preparing the master data allocation for a project: This operation uses the question texts and labels from the questionnaire as master data labels. However, these are often too long or not in the right order and do not conform to the desired nomenclature. Please proceed as follows:

Click on the Quick change labels button in the People → Master data menu. The following entry form will be opened.
The entry form shows all the master data that has been created in the system: The first part of each line contains the master data variable, which cannot be changed. After the separator, you will find the title that serves as a label. Change the label as desired.
Lastly, click on the Submit button.

Information

You cannot delete or add variables. If you remove a line, this will be ignored.

Editing the labels externally

You can also edit the master data labels externally in MS Excel:

Click on [tab] in the “Choose a separator” row. The first and second column will now no longer be separated by a semicolon but by a tab character.
Highlight the content of the window.
Copy the content of the window to MS Excel (under Windows, you can press Ctrl-C).
Edit the labels in MS Excel. After that, copy the changed data back to the window and confirm by clicking on Submit.

Mass Import of Master Data

You can create master data including the related answer categories by means of mass import or by copying out master data that have already been created in a special format, editing them externally and then reimporting them. This is particularly helpful if you already have a list of the planned new master data and answer categories in Excel.

Deleting data by means of mass import is not permissible because the risk of accidental data loss is too high. If you wish to delete master data or answer categories, please perform the operation via the user interface.

Formatting import data

1. Formatting master data

The following format should be used:

item;master data variable;title;data type;order;category ID

Example:

item;md_001;Birthday;int;2;5;3

This sample master data item is used to save the date of birth. The variable is “md_001”, and it is labeled “Birthday”. The data type is “integer”, i.e. a whole number. The field has 2 digits. The order of the master data is such that date of birth is in position 5 and belongs to the category with the ID number 3.

Field	Meaning	Example
Information to be created	Indicates whether the element is a master data variable (item) or an answer category (r_cat).	item -> master data item
Master data variable	Indicates the master data item: The format for manually created master data is “md_”. The format for master data created by mass import is “m_number”.	m_001
Title	The label.	Birthday
Data type	Data type and size in the database.	int
Order	The position in the order of master data.	5
Category ID	The master data category.	3

2. Formatting answer categories

The following format should be used:

r_cat;master data variable;code;title;

Example:

r_cat;md_001;Birthday;0;Please select

This sample answer category belongs to the variable “md_001”, in which the birthday is saved. The answer category has the code “0” and is labeled “Please select”, i.e. it is the defaulted field in a drop-down list that prompts the panelist to set the correct date.

Field	Meaning	Example
r_cat	Indicates whether the element is a master data variable (item) or an answer category (r_cat).	rcat -> answer category
Master data variable	Indicates to which master data item an answer category belongs.	md_001
Code	The code of the answer category. You can use negative numbers, however these cannot contain blank spaces. E.g., “-77” can be imported “- 77 not”.	0
Title	The label.	Birthday

Performing the import

Open the People → Master data menu.
This will open the overview of the master data. Instead of manually creating new master data, click on the Mass-import master data button.
Select the desired separator.
Usually, default master data and answer categories will already be available. Add the new master data and answer categories in the correct format. If you have created an Excel table, transfer the content, but not the column labels, using copy & paste.
Confirm by clicking on Import.
At the beginning of the import operation, the entries are checked for the following errors:
– Is the master data correctly named according to the “m_number” convention?
– Does the type and size information match?
– Does a master data variable already exist? You cannot create another variable with the same name (e.g. m_15) as an existing one.
– Does each row have exactly five columns? You should also make sure that there is no empty row at the end in the import window.
If the data is error-free, the master data will be created. Otherwise, an error message will result.

Editing and exporting master data by means of the mass import function

Master data and answer categories that have already been created will be output in the input field and can then be edited. External editing is also possible:

Copy the content of the input field into Excel.
Should Excel copy the data into a cell instead of formatting it correctly, select Data → Text to Columns. Choose the data type “Delimited”, and confirm by clicking on Next.
Choose the separator, and confirm by clicking on Next again.
Check the display, and then confirm by clicking on Finish.

Changing the Order of the Master Data

You can specify the order in which master data should normally be displayed in the admin area. To do so, click on the Change order button in the People → Master data menu.

You can define the order yourself. To do so, enter the desired numbering in the “Order” field, and confirm by clicking on Save (see the following figure).
You can sort the master data in a panel or master data survey by means of the associated variables. To do so, click on the Sort by project questionnaire order button. Select the desired project and then confirm by clicking on Submit.

Deleting Master Data

You can remove master data by activating the corresponding “Delete” checkbox in the master data overview and confirming with Save. Please note that already recorded information and information stored in these master data are irrevocably deleted and are no longer available for future searches in the panel, group forming or evaluations.

This can also damage functions which access master data such as recodings.

Therefore, a list will be output when deleting master data, in which you can see whether the master data are still being used. This covers normal recodings and lookup recodings, filters in surveys, the grouping filters, update rules and panel settings. In the column “Usage” you can see which function has access to the master data. The traffic-light icon in the column “Status” shows, whether another conjunction exists (red traffic light icon).
The check does not cover formel recodings.

Tracking Changes of Master Data

To view the change history of your master data, open the People → Master data → Master data logs menu. The overview table lists all changes along with their respective dates, the variables concerned, the responsible user, and the types of operation performed.

Via the Detail view icon, you can access the details of a particular change.

Recoding Master Data

You can recode existing master data in order to generate new master data variables that are more compact. For example, you can recode a master data variable titled “Year of birth” into a variable titled “Age group”, with various characteristics such as “Teens”, “Adults” or “Senior citizens”. The master data gained by recoding can be used, for example, to create groups. When creating a group, apply the master data filter, and select as the filter criterion the desired code of the recoded master data variable.

During master data export, the variable generated by recoding will be included in the data record just like any other master data.

There are different ways to recode master data:

Characteristics of a master data variable can be rearranged.
A recoding can be calculated, based on the values of one or several master data variables.
So-called table-based recoding is performed using a table (“lookup”) containing a list of all possible values as well as the allocation of the destination values.

Information

Please mind: The usage of many and/or complex recodings can have a negative effect on the performance of your panel installation.

Automated recoding, i.e. recoding with every individual master data change, puts a heavy load on the server. Therefore, it is recommended to use not more than 20 master data recodings per installation. Instead, use the possibility to group recodings and trigger the recoding of these groups via an update rule e.g. once a day during a low traffic period.
Check regularly if the existing recodings are really necessary.

Rearranging the Characteristics of Master Data

Recoding is frequently used to rearrange the characteristics of a master data item. This requires the following steps:

Defining the mapping
Defining the recodes definition
Defining the target categories
Specifying the target categories
Executing the recoding

1. Defining the mapping

Before you create the recodes definition in EFS, think about which characteristics your new recoding variable should have. Then, define which characteristics of the source variable should be allocated to each characteristics of the recoding variable.

2. Creating a recodes definition

When creating a new recodes definition, you have to specify the master data variable that is used as source variable.

Please proceed as follows:

Switch to the People→ Master data → Recoding of master data menu.
Click on the Create recoding variable button.
Enter the title for the recodes definition.
Select the master data variable whose values serve as starting point for the recoding process.
Select a master data category for the new recoding variable which is about to be created.
Specify whether the recoding should be triggered automatically. In the example shown above, the panelists are allocated to age groups. In this case, automatic recoding does not make sense: instead, you could e.g. allocate the recodes definition to a recoding group and trigger it only once a week.
Optionally, you can assign the recodes definition to a recoding group.
Optionally, you can specify the recoding order.
After that, confirm by clicking on Create.
A new master data variable is created: it will be used to store the results of the recoding process. The newly created recodes definition appears in the overview table.

3. Defining target categories

In this step, you define the characteristics of the new master data variable, i.e. the target categories of the recoding process.

Click on the title of the new recodes definition, “Age group”.
On the Recodes definition tab, you can change the title, activate automatic recoding subsequently and change the recoding order.
Switch to the 1. Define target categories tab.
Enter the desired target categories successively, including their sort numbers and codes. After that, confirm each entry by clicking on Save. If, for example, you wish to perform a recoding with three different characteristics based on the variable titled “Year of birth”, specify three different target categories (characteristics) such as “Teens”, “Adults” or “Senior citizens”.

4. Specifying the target categories

In this step, the characteristics of the source variable are allocated to the target categories of the recoding variable.

Click on the 2. Specify assignments tab.
All the characteristics of the master data variable to be recoded will be displayed (in the example shown, all years of birth since 1910). Tick the checkboxes for the characteristics that fit the target categories. In the example shown, select the years of birth from 1910 to 1944 for the “Senior citizens” target category, the years of birth from 1945 to 1985 for “Adults” and the years of birth from 1986 to 2004 for “Teens”.
Confirm by clicking on Save.

5. Executing the recoding

Click on the 3. Run recoding process tab. The result display shows you how many records were affected.

Calculating Recodings with Formulas

In many cases, you can use a mathematic formula to calculate the recoding, using the values of one or several master data as starting point for the calculation.

Recodings are frequently used to rearrange the characteristics of a master data item.

This requires the following steps:

Defining the formula.
Creating a new recoding.

1. Defining the formula

Define the formula which describes your recoding. The following rules apply:

Use wildcards #md_xxx# resp. #m_xxx# to insert master data.
The operators + - / * and ( and ) can be used.
It is possible to perform date calculations. For details, please see the explanations for grouping filters in Chapter "Creating and Editing Groups".

Information

Please mind: only the functions named below can be used and are supported in future versions of EFS. No other functions can be used.

Function		Explanation	Example
case	CASE WHEN expr1 THEN value1 ELSE value2 END	Returns the THEN value for which the condition applies.	CASE WHEN md_country = 'Germany' THEN 1 WHEN md_country = 'Austria' THEN 2 ELSE 99 END
ceil	CEIL(x)	Returns the smallest integer value not less than X.	CEIL(1.23); → 2
concat	CONCAT(str1,str2,...)	Returns the string that results from concatenating the arguments.	CONCAT('My', 'S', 'QL'); → 'MySQL'
date_format	DATE_FORMAT(date,format)	Formats the date value according to the format string.	DATE_FORMAT ('1997-10-04 22:23:00', '%W %M %Y'); → 'Saturday October 1997'
datediff	DATEDIFF(expr,expr2)	Returns expr1 – expr2 expressed as a value in days from one date to the other.	DATEDIFF('1997-12-31 23:59:59', '1997-12-30'); → 1
day	DAY(date)	Returns the day of the month for date, in the range 1 to 31.	DAYOFMONTH('1998-02-03'); → 3
floor	FLOOR(X)	Returns the largest integer value not greater than X.	FLOOR(1.23); → 1
from_unixtime	FROM_UNIXTIME (unix_timestamp) FROM_UNIXTIME (unix_timestamp, format)	Returns a representation of the unix_timestamp argument as a value in 'YYYY-MM-DD HH:MM:SS' or 'YYYYMMDDHHMMSS' format. If format is given, the result is formatted according to the format string, which is used the same way as listed in the entry for the DATE_FORMAT() function.	FROM_UNIXTIME(875996580); → '1997-10-04 22:23:00'
greatest	GREATEST(value1, value2,...)	With two or more arguments, returns the largest (maximumvalued) argument.	GREATEST(2,0); → 2
if	IF(expr1,expr2, expr3)	If expr1 TRUE (expr1<> 0 and expr1 <> NULL), than IF() returns expr2; otherwise it returns expr3.	IF(1>2,2,3); → 3
instr	INSTR(str,substr)	Returns the position of the first occurrence of substring substr in string str.	INSTR('foobarbar', 'bar'); → 4
least	LEAST(value1,value 2,...)	With two or more arguments, returns the smallest (minimumvalued) argument.	LEAST(2,0); → 0
left	LEFT(str,len)	Returns the leftmost len characters from the string str.	LEFT('foobarbar', 5); → 'fooba'
length	LENGTH(str)	Returns the length of the string str, measured in number of characters.	LENGTH('text'); → 4
lower	LOWER(str)	Returns the string str with all characters changed to lowercase according to the current character set mapping.	LOWER('QUADRATICALLY'); → 'quadratically'
month	MONTH(date)	Returns the month for date, in the range 1 to 12.	MONTH('1998-02-03'); → 2
now	NOW()	Returns the current date and time as a value in 'YYYY-MM-DD HH:MM:SS' or YYYYMMDDHHMMSS format, depending on whether the function is used in a string or numeric context.	NOW(); → '1997-12-15 23:50:26'
right	RIGHT(str,len)	Returns the rightmost len characters from the string str.	RIGHT('foobarbar', 4); → 'rbar'
to_days	TO_DAYS(date)	For a given date, it returns the number of days passed since year 0 until this date.	TO_DAYS(950501); → 728779
trim	TRIM([{BOTH \| LEADING \| TRAILING} [remstr] FROM] str), TRIM(remstr FROM] str)	Returns the string str with all remstr prefixes or suffixes removed. If none of the specifiers BOTH, LEADING, or TRAILING is given, BOTH is assumed. remstr is optional and, if not specified, spaces are removed.	TRIM(' bar '); → 'bar'
upper	UPPER(str)	Returns the string str with all characters changed to uppercase according to the current character set mapping.	UPPER('Hej'); → 'HEJ'
unix_timestamp	UNIX_TIMESTAMP() UNIX_TIMESTAMP(date)	If called with no argument, returns a Unix timestamp (seconds since '1970-01-01 00:00:00' UTC) as an unsigned integer. If UNIX_TIMESTAMP() is called with a date argument, it returns the value of the argument as seconds since '1970-01-01 00:00:00' UTC.	UNIX_TIMESTAMP('1997-10-04 22:23:00'); → 875996580
year	YEAR(date)	Returns the year for date, in the range 1000 to 9999, or 0 for the “zero” date.	YEAR('98-02-03'); → 1998

2. Creating a recoding

In the People → Master data → Recoding of master data menu, click on the Create recoding variable (formula) button.
Enter the title of the recodes definition.
Enter the formula.
Specify whether automatic recoding should be applied. In the example shown above, the panelists’ age is calculated. In this case, automatic triggering does not make sense: instead, you could e.g. allocate the recoding to a recoding group and trigger it only once a week.
Optionally, you can assign the recodes definition to a recoding group.
Optionally, you can specify the recoding order.
Confirm by clicking on Submit.
A new master data variable is created: it will be used to store the results of the recoding process. The newly created recodes definition appears in the overview table.
To execute the recoding process directly, follow the instructions in this chapter. Alternatively, you can either execute the recoding process in self-defined intervals, or use automated recoding.

Using Allocation Tables to Define Recodings

A third recoding possibility is an allocation by means of a table containing a list of all possible values as well as the allocation of the destination values. A typical example of a recoding that can be implemented in this way is the recoding of zip codes according to states or Nielsen areas (see http://de.wikipedia.org/wiki/Nielsen-Gebiet). EFS Panel allows you to create such allocation tables (so-called lookups) and access them via special recoding variables.

1. Creating the allocation list (lookup)

Lookups are allocation lists containing the source and destination codes used to recode a variable. Recoding operations are performed on the basis of these lists.

You can create and edit lookups in the People → Master data → Recoding of master data → Lookups menu.

Encoding lookups

Usually there is already an existing table containing the lookup allocation available to you. Format the content of the table as follows:

The table should have two columns.
The left-hand column contains the source variable’s code value that will be recoded. This value must be unique. Both master data and address data can be used as source variable.
The right-hand column contains the destination code of the automatically created target variable. This value does not have to be unique. Two different source codes can be assigned to the same new code.

You can use numeric values equal to or greater than “0” as code. In order to make the data import feasible, the table should be in CSV or XLS format. Strings can also be used as codes (e.g. AU (Australia) or AT (Austria). In the panelist's master data, the recoding variable created via the lookup, which is a text variable, must be changed into a numeric variable.

Creating a lookup

Switch to the People → Master data → Recoding of master data → Lookups menu.
Click on the Create lookup button.

Entering data manually

The lookup has now been created, but does not contain any recoding data yet.

Click on the title of the lookup or on the Edit data icon.
Select the desired separator. You can choose between semicolon and tab.
The assignment of values can be entered in the in the main input field.
Save the values.

Importing data

If the allocation table is available in CSV or XLS format, you can import the data. To do so, click on the Import data icon, and follow the instructions given in the already familiar import dialog.

2. Using lookups for recoding

Switch back to the overview of the recoding menu by clicking on the Master data recodes menu item.
Click on the Create recoding variable (lookup) button.
Enter the title.
Select the lookup table from which the recoding information is to be taken.
Select the source variable.
Specify whether the recoding is to be performed automatically. In the example shown above, the panelists are allocated to Nielsen areas. In this case, an automated recoding does not make sense: instead, you could e.g. allocate the recoding to a recoding group and trigger it only once a week.
Optionally, you can assign the recodes definition to a recoding group.
Specify the recoding order.
Confirm by clicking on Create.
A new master data variable is created: it will be used to store the results of this recoding. The newly created recodes definition appears in the overview table.
To execute the recoding process now, follow the instructions in this chapter. Alternatively, you can either execute the recoding process in self-defined intervals, or use automated recoding.

Specifying the Order of Recoding Processes

The order of the recoding processes is important when the recodings are based on the values of other recodings. Because EFS Panel allows you both to apply automatic recoding function and to execute all defined recodings, it is necessary to specify the order in advance.

To do so, click on the Change order button to open the corresponding form. The “Recoding order” field allows you to specify the sequence. After that, confirm by clicking on Save.

Executing Recodings Manually

You can trigger recodings manually, both individually and as a block.

In order to execute an individual recoding, locate it in the overview table and click on the Run recoding procedure icon.
Before executing all recodings, you should first check the overview table to verify that the specified recoding order makes sense. After that, trigger the process by clicking on Execute all recodings.

Configuring a Regular, Effective Execution of Recodings

In many cases, importance is attached to regular synchronization of data, while automatic recoding with every individual master data change is not necessary. Manual recoding, on the other hand, is not effective and error-prone. And the update feature for groups, which may in some cases be used as an alternative to recodings, does not provide comparable flexibility e.g. when defining conditions.

By a clever combination of recoding groups and group update rules, you can optimize the point in time and/or the extent of master data recoding in such cases.

You can, for example, subsume several recodings which require a daily update into a recoding group, and then trigger the recoding automatically once a day during a lowtraffic period.

Creating recoding group

Switch to the People → Master data → Recoding of master data → Recoding groups menu.
This will take you to the overview of existing recoding groups.
Select Add group.
Enter a name and description and confirm with Save.

Assign recoding to a recoding group

Open an existing recoding.
Select the appropriate group in the “Recoding group” drop-down list.
Then confirm by clicking on Save.

Executing recodings for a recoding group manually

Switch to the People → Master data → Recoding of master data → Recoding groups menu.
This will take you to the overview of existing recoding groups.
Click the icon Execute recoding in group icon for the desired recoding group. All recodings assigned to this group are now executed.

Configuring the automated execution of recodings for a recoding group

Switch to the Groups → Update rules menu.
When you create a new rule or edit an existing rule the action “Execute recodings from recoding group” becomes available. Select this action and then Save.
Select the desired recoding group in the “Value” field.
As usual you can for example select automatic execution at a specified point in time and at a set interval. Make all the settings and Save. All recodings of the desired recoding group are executed in accordance with the specified schedule.

Configuring an Automated Execution of Recodings

EFS Panel provides the option of automatically executing recodings in a preset order under specific circumstances. The following will be automatically recoded:

A candidate’s data upon self-registration via the registration form.
The data of a panelist who has edited his data using the re-registration form.
The data of imported or updated panelists.
The data of a panelist when their master data is saved in the admin area.

Activating automatic recoding

You can activate the “Auto recode” function when you create a new recoding or subsequently click on the Edit icon in the recoding table to open the form and activate this function.

Information

If you are applying the “Auto recode” function and wish to delete old recodings or add new ones, be very careful that the recoding order does not become incorrect.

Master Data Codebook

The master data codebook provides an overview of the panel’s master data and their encodings. It is used, for example, for the definition of filter conditions or for evaluation. You will find the codebook in the People → Master data → Master data codebook. It contains the variable name and label, data type, variable type, answer code and label (if available) as well as the master data category for each master data item.

Above the list, you will find various features which allow you to restrict, to reorder or to extend the list:

Restrict to category: This option allows you to restrict the list to a single master data category.
Sort by column: With this option you can order the list by category label, variable name, variable label, or variable type.
Show recoding information: Master data of “recoded” type are displayed along with recoding details such as the recoding formula.
Hide answer categories: The columns “Answer code” and “Answer label” are hidden, the list of master data is simplified.

Via the Export button you can download the codebook in its current configuration.

Master Data Logs

Master data administration includes a logfile which keeps track of changes made to the master data variables. This allows you, for example, to easily identify and track any changes made by other users. To view the change history of your master data, open the People → Master data → Master data logs menu. The overview table lists all changes along with their respective dates, the variables concerned, the responsible user, and the types of operation performed.

Via the Detail view icon, you can access the details of a particular change.

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