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This blog post is for anyone responsible for Enterprise data management who would like to save time and costs by re-using a great piece of modeling work. It updates an earlier blog post, “A brief introduction to the gist semantic model”.

A core semantic model, also called an upper ontology, is a common model across the Enterprise that includes major concepts such as Event, Agreement, and Organization. Using an upper ontology greatly simplifies data integration across the Enterprise. Imagine, for example, being able to see all financial Events across your Enterprise; that kind of visibility would be a powerful enabler for accurate financial tracking, planning, and reporting.

If you are ready to incorporate semantics into your data environment, consider using the gist upper ontology. gist is available for free from Semantic Arts under a creative commons license. It is based on more than a hundred data-centric projects done with major corporations in a variety of lines of business. gist “is designed to have the maximum coverage of typical business ontology concepts with the fewest number of primitives and the least amount of ambiguity.” The Wikipedia entry for upper ontologies compares gist to other ontologies and gives a good sense of why gist is a match for Enterprise data management: it is comprehensive, unambiguous, and easy to understand.

So, what exactly is in gist?

First, gist includes types of things (classes) involved in running an Enterprise. Some of the more frequently used gist classes, grouped for ease of understanding, are:

The most used gist classes in seven groups: who (Person, Organization), what (Artifact, Collection, Equipment, Event, Landmark), where (Place), when (xsd:dateTime), why (Intention, Commitment), how (Agreement, Language, Template), and how much (Aspect, Magnitude, Unit Of Measure).

Some of these classes have subclasses that are not shown. For example, an Intention could be a Goal or a Requirement.

Gist also includes properties that are used to describe things and to describe relationships between things. Many of the gist properties can be approximately grouped as above:

gist properties in the same groups, such as hasGiver and hasRecipient for who, isAbout and owns for what, hasAddress and occursIn for where, actualStartDateTime for when, hasGoal for why, conformsTo for how, and hasMagnitude for how much.

Other commonly used gist properties include:

Other common gist properties: isIdentifiedBy for identity, isCategorizedBy for category, hasMember and hasPart for part and whole, precedes for sequence, and links for networks.

Next, let’s look at a few typical graph patterns that illustrate how classes and properties work together to model the Enterprise world.

An Account might look like:

An account in gist: gist:Account links to an obligation (hasDirectPart), an organization (hasGiver), a balance (hasMagnitude), a person (hasParty), and a degree of commitment (isCategorizedBy).

An Event might look like:

An event in gist: gist:Event has actual start and end times, a goal, a participant (gist:Person), and a behavior it is characterized as, and any thing can be linked to it with isAffectedBy.

An ID such as a driver’s license might look like:

An ID in gist: a person is identified by a gist:ID, which is allocated by an organization and holds the ID’s unique text.

To explore gist in more detail, you can view it in an ontology editor such as Protégé. Try looking up the Classes and Properties in each group above (who, what, where, why, etc.). Join the gist Forum (select and scroll to the bottom) for regular discussion and updates.

Take a look at gist. It’s worth your time, because adopting gist as your upper ontology can be a significant step toward reversing the proliferation of data siloes within your Enterprise.

Further reading and videos:

3-part video introduction to gist:

  1. https://www.youtube.com/watch?v=YbaDZSuhm54&t=123s
  2. https://www.youtube.com/watch?v=UzNVIErpGpQ&t=206s
  3. https://www.youtube.com/watch?v=2g0E6cFro18&t=14s

Software Wasteland, by Dave McComb

The Data-Centric Revolution, by Dave McComb

Demystifying OWL for the Enterprise, by Michael Uschold

Diagrams in this blog post were generated using a visualization tool.

Related reading: What is gist, and what does it stand for?