Digital Financial Reporting

Just like [Line Items] have patterns or information models such as [Roll Forward], [Roll Up], and [Hierarchy], the [Member]s of an [Axis] likewise have an information model. I have put together a document which summarizes these moving pieces which you can get here.

Here are some example financial reporting use cases which show different types of dimensional aggregation schemes which will give you an I deal of what I am talking about:

• [Axis] with no aggregation: Subsequent events or property, plant, and equipment policies would be an example of where you would have an [Axis] with no aggregation. Subsequent events are rarely, if ever, added up to arrive at some total amount for subsequent events of an entity.  The same with PPE policies, they are not added up.
• [Axis] with basic aggregation: Nonmonetary transactions are a good example of a basic aggregation. There is no real grouping of nonmonetary transactions, it is simply a flat list.  That list has an amount of for each nonmonetary transaction, and the total for nonmonetary transactions is commonly reported. That total does not tie to any other location in the financial report, it stands alone.
• [Axis] with complex aggregation: Business segment reporting is a good example of potentially complex aggregation. You may have a Parent Holding Company [Domain], which has consolidation eliminations, and multiple business segments.  You may add to this a breakdown of continuing and discontinued segments. This could become even more complex with asset groups, reporting units, and disposal groups.

As the XBRL Dimensions Specification does not address dimensional aggregation, taxonomy creators are on their own to address this.  Fortunately, XBRL Formulas is available to articulate and validate against aggregation schemes.

In order to create these aggregations, a good understanding of what a domain is becomes important.

See the document for more information if you care to understand and eventually master this area.

Thank you to all the XBRL Dimensions heavy weights who contributed to my understanding of this important information.