Modeling the MDM Blueprint – Part 2

whiteboardIn Part 1 of this series, we discussed what essential elements should be included in an MDM blueprint. The important thing to remember is that MDM is a business project that requires establishing a common set of models that can be referenced independently of the technical infrastructure or patterns you plan on using. The blueprint should remain computation and platform independent until the models are completed (and accepted by the business) to support and ensure the business intent. The essential elements should include:

– Common Information Model
– Canonical Model
– Operating Model, and
– Reference Architecture (e.g. 4+1 views, viewpoints and perspectives).

We will now turn our attention to the first element, the Common Information Model.

A Common Information Model (CIM) is defined using relational, object, hierarchical, and semantic modeling methods. What we are really developing here is rich semantic data architecture in selected business domains using:

  • Object Oriented modeling: reusable data types, inheritance, operations for validating data
  • Relational: manage referential integrity constraints (primary keys, foreign keys)
  • Hierarchical: nested data types and facets for declaring behaviors on data (e.g. think XML schemas)
  • Semantic models: ontologies defined through RDF, RDFS and OWL

I believe (others may not) that MDM truly represents the intersection of Relational, Object, Hierarchical, and Semantic modeling methods to achieve a rich expression of the realitycim_diagram in which the organization operates. Expressed in business terms, this model represents a “foundation principal” or theme we can pivot around to understand each facet in the proper context. This is not easy to pull off, but will provide a fighting chance to resolve semantic differences in a way that helps focus the business on the real matters at hand. This is especially important when developing the Canonical model introduced in the next step.

If you want to see what one of these looks like visit the MDM Alliance Group (MAG). MAG is a community that Pierre Bonnet founded to share MDM Modeling procedures and pre-built data models. The MDM Alliance Group publishes a set of pre-built data models that include the usual suspects (Location, Asset, Party, Party Relationship, Party Role, Event, Period [Date, Time, Condition]) downloadable from the website. And some more interesting models like Classification (Taxonomy) and Thesaurus organized across three domains. Although we may disagree about the “semantics”, I do agree with him that adopting this approach can help us avoid setting up siloed reference databases “…unfortunately often noted when using specific functional approaches such as PIM (Product Information Management) and CDI (Customer Data Integration) modeling”. How true. And an issue I encounter often.

Another good example is the CIM developed over the years at the Distributed Management Task Force (DMTF). You can get the CIM V2.20 Schema MOF, PDF and UML at their web site and take a look for yourself. While this is not what most of us think of as MDM, they are solving for some of the same problems and challenges we face.

Even more interesting is what is happening in semantic technology. Building semantic models (ontologies) includes many of the same concepts found in the other modeling methods we’ve already discussed but further extend the expressive quality we often need to fully communicate intent. For example:

– Ontologies can be used at run time (queried and reasoned over).
– Relationships are first-class constructs.
– Classes and attributes (properties) are set-based and dynamic.
– Business rules are encoded and organized using axioms.
– XML schemas are graphs not trees, and used for reasoning.

If you haven’t been exposed to ontology development, I encourage you to grab the open source Protege Ontology Editor and discover for yourself what this all about. And while you are there see the Protégé Wiki and grab the Federal Enterprise Architecture Reference Model Ontology (FEA-RMO) for an example of its use in the EA world. Or see the set of tools found at the Essential project. The project uses this tool to enter model content, based on a model pre-built for Protégé. While you are at the Protégé Wiki, grab some of the ontologies developed for use with this tool for other examples, such as the SWEET Ontologies (A Semantic Web for Earth and Environmental Terminology. Source: Jet Propulsion Laboratory). For more on this, see my post on this tool at Essential Analytics. This is an interesting and especially useful modeling method to be aware of and an important tool to have at your disposal.

This is hard challenging work. Doing anything worthwhile usually is. A key differentiator and the difference between success and failure on your MDM journey will be taking the time to model the blueprint and sharing this work early and often with the business. We will be discussing the second element of the MDM blueprint, the Canonical model in Part 3. I encourage you to participate and share your professional experience via the comments here.

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