Identity Matching (Correlation) Implementation

Last modified 31 Mar 2022 12:37 +02:00

This is a description of an implementation of so-called identity matching using ID Match API.

The midPoint term for matching resource objects with midPoint user population is correlation. In this document we will use the terms of "identity matching" and "correlation" interchangeably; preferring the latter one.


Before midPoint 4.5, the correlation process was quite limited: It was possible to provide a query - or a set of queries - along with optional confirmation expression. These were evaluated against midPoint repository, and produced zero, one, or more candidate owners. If this process resulted in a single candidate, it was perceived as the owner of the account. If no object was found, this meant that an owner should be created (if appropriate reaction was set). And if multiple objects were found, the synchronization situation was said to be disputed, and practically no further processing was possible.

Starting with midPoint 4.5, the correlation process is much richer. First, midPoint can deal with multiple candidate owners. In such situation - if configured so - it can create a correlation case, i.e. something that can be manually resolved. The case contains a list of candidate owners, and asks the human operator to choose among them. Second, midPoint is no longer restricted to internal actions when doing the correlation. It can now invoke external ID Match API provider that does the matching, and returns the owner (or a list of candidate owners) to midPoint.

Basic midPoint - ID Match communication
Figure 1. Communication between midPoint and ID Match service

Sample Scenario

Let us now describe how the matching is configured.

We will use the most basic scenario, where we have a single source resource (Student Information System), supplying user personal data: given name, family name, date of birth, and national ID. We ignore other attributes for now.

We will match accounts from this resource to midPoint users using the sample ID Match Service, pre-configured with three simple matching rules.

Before specifying the correlation details themselves, please have a look at correlation-time mappings. We’ll use them in the description below.

Configuring the Correlation

The correlation definition is written in new correlationDefinition item, which is eventually going to supersede both correlation and confirmation items.

The most simple definition of ID Match-based correlation looks like this:

Listing 1. Simple definition of ID Match-based correlation

Let us describe it in detail.

The correlators Section

This section specifies how the correlation should take place. You can define a lot of various correlators here. However, the only one that is officially supported in 4.5 is idMatch correlator.

ID Match Correlator Configuration

The configuration contains the URL of the ID Match service to be used, along with the credentials.

Then it contains so-called follow-on correlator. What’s its purpose?

ID Match service does not know about midPoint users nor their OIDs. It works with the concept of reference IDs - globally-unique identifiers assigned by the service to individual persons. Therefore, the result of a matching process can be threefold:

  1. Either the reference ID of already known person is returned,

  2. or a new reference ID is generated,

  3. or a list of reference IDs (candidate matches) is returned.

MidPoint then must somehow deal with this information.

The most natural way of using reference IDs is this:

  1. A reference ID for a person is stored somewhere in the user object. It can be in a selected standard property (like employeeNumber or name), or in an extension property (e.g. extension/referenceId as in our example).

  2. When ID Match service returns a reference ID or IDs (either as a definite match, or as part of the list of match candidates), the follow-on correlator looks up user or users by looking for these values in the user population. In our example, midPoint tries to find a user with extension/referenceId equal to the ID obtained, which is available in $correlatorState/referenceId property.

Reference ID resolution
Figure 2. Reference ID resolution process

As we describe later, there is a mapping that puts the reference ID to this property. See Listing 4 below.

Besides ID Match, there are the following experimental correlators:

Correlator Description


Correlate using specified set of items (computed by correlation-time inbound mappings).


Traditional filter-based correlation.


Correlation that uses custom expression.


Composite correlation that invokes a set of child correlators (with a different level of authority) and combines their results.


Always returns "no owner" response. For development/testing purposes.

You may use them on your own risk. But beware, the supported way of correlating (except for ID Match) is still to use correlation and confirmation items.

The cases Section

When multiple potential owners are found, the default midPoint behavior is to simply store them in the shadow object. (In the correlation item.) This may be useful in the initial stages of midPoint deployment when the correlation rules are not tuned enough, and may provide a lot of false matches. But, as you become more confident in your correlation rules, you may turn on the creation of case objects that trigger human resolution of correlation-related questions.

You do that by including (empty) <cases> item in your <correlationDefinition>, as can be seen in Listing 1.

The items Section (Optional)

By default, midPoint sends to ID Match service all single-valued properties that it finds in the focus object computed by "before-correlation" inbound mappings. This may or may not be suitable in your case. If you need to customize this information, you can specify these properties explicitly.

The basic configuration may look like this:

Listing 2. Specification of items to be sent to ID Match service

This simply tells midPoint to take the values of givenName, familyName, extension/dateOfBirth, and extension/nationalId, and send them to ID Match service under respective names: givenName, familyName, dateOfBirth, and nationalId.

This section has an additional purpose. When displaying the correlation case for human operator, midPoint needs to know what properties are relevant for the correlation, so that they should be shown. By default, all properties that were computed by "before-correlation" mappings are shown. But if items section is present, only properties mentioned in it are shown.


Now let us see how attributes from resource accounts (along with reference ID from ID Match service) are mapped to midPoint user properties.

Let us describe sample objectType definition from the resource. The start of the definition is quite standard:

Listing 3. Start of the object type definition
    <!-- ... -->

Mappings for sisId and referenceId

Here is the first attribute of sisId (a unique account identifier):

Listing 4. Declaration of sisId attribute
    <inbound> (1)
    <inbound> (2)
            <!-- Before correlation, this ID may not be known. -->
1 Mapping of sisId attribute to the user extension property.
2 Mapping of referenceId property (not an attribute!) to the user extension property.

There are two mappings here.

The first one is quite standard one: we store the ID in specific extension property (sisId).

The second one is - in fact - not related to sisId at all. It stores the referenceId obtained from the ID Match service (and stored in the shadow in correlation/correlatorState/referenceId property) in user extension/referenceId property. We have to do this to allow this user be correlated by this ID later.

It is not in its own <attribute> definition, because it is not, in fact, an attribute. So we had to use a little "hack" to ensure it’s executed by listing it along with another attribute: sisId.

We explicitly forbid execution of this mapping before the correlation. It is because at that time we have (obviously) no reference ID.

Mappings for other (regular) attributes

Mappings for other attributes are fairly standard. An example:

Listing 5. Declaration for a regular attribute

Enabling processing of mappings before the correlation

Finally, we have to ensure that the regular mappings are executed both before correlation and in regular clockwork processing.

Listing 6. Enabling execution of inbound mappings both before correlation and during clockwork

The exception is a mapping for referenceId that overrides this default by excluding beforeCorrelation phase from the execution (see Listing 1).

For More Information

The whole resource definition can be seen on GitHub.

There is also the multi-accounts scenario, covering a single resource with potentially more accounts per user. It shows how we can deal with multiple sources of personal data: i.e. something that often occurs in connection with the problem of identity matching itself.