Temporal Reasoning in Oracle Intelligent Advisor : Entering and Converting Data

In this, the fourth part of our series (here’s a link to the previous part) about Temporal Reasoning in Oracle Intelligent Advisor , we are going to look at the business of entering data. Specifically, how users can enter the information they need during an interview. Thinking back to the scenario we have been discussing in the previous articles (part one, two and three), we need to enter information about our bank balance.

In a non-temporal world, entering the data would be as simple as entering a value in an input box. But we cannot have that, since there is no built-in capability to enter different values on different dates. Unlike some CRM systems like my old friend Oracle Siebel, there is no user interface element designed to facilitate the entry of temporal data.

So what options do we have? We can ask our users to enter data in row format, with each row representing a specific amount on a specific date. Put simply we can create an Entity and each instance can be converted into a temporal value. Let’s see how that works. Consider the following new Project with a simple data model:

Temporal Reasoning in Oracle Policy Automation 3

As you can do doubt see, a single entity has been added and a few attributes. In addition I have changed the default text provided for the Containment Relationship to make it more natural looking. For our purposes we are interested in the date and the currency attributes which will form the basis of our conversion. To make this easier, we are going to use an Excel table to infer instances of the bank balance entry using the following table:

Oracle Intelligent Advisor Table

With this data we can now use one or other of the Temporal Reasoning functions that allow us to build temporal values from entity instances. As a first example, enter the following in a Word document in the project.

Temporal Reasoning in Oracle Policy Automation 5

The expression targets a new attribute, the temporal bank balance, which will be populated with the output of the TemporalFromStartDate function. The function takes the relationship as the initial argument, followed by the date attribute and our currency attribute. The result in the Debugger is this (note I have superimposed the Temporal Visualization from the Debugger on the Interview output) :

Temporal Reasoning in Oracle Policy Automation 6

Awesome. Our instances have become temporal values for our temporal attribute. But beware what this function is giving you. The implication of From Start Date is that any date prior to the first date in your Excel will show a temporal value of uncertain. Change the function to the following:

Temporal Reasoning Oracle Policy Automation 7

In this case, you are indicating that From the End Date of your instances, the temporal attribute will be uncertain.

Temporal Reasoning Oracle Policy Automation 8

If you have instances where there is both an end and a start date for each instance (which is not the case in our bank balance Excel table), you could also use this function to calculate when something was (for example) valid or invalid:

Temporal Reasoning Oracle Policy Automation 9

This of course assumes you have an entity, relationship and attributes that match the example above. It produces output like this:

Temporal Reasoning Oracle Policy Automation 10

In case you were wondering, you can reverse this process (go from temporal to instances) using a different method. In the final part of this series we will look at displaying the temporal data in cool ways.

Thanks for reading and see you soon! If you want to formalize your Temporal Reasoning in Oracle Intelligent Advisor learning experience, check out our new Oracle Intelligent Advisor Temporal Reasoning training class.

And now for something completely different : Fancy a cheeky challenge to test your knowledge? – try this brain teaser for size. Still no right answers after 5 years!

Author: Richard Napier

After 8 years in case management and ERP software roles, Richard Napier joined Siebel Systems in 1999 and took up the role of managing the nascent Siebel University in Southern Europe. He subsequently was Director of Business Development and Education for InFact Group (now part of Business & Decisions) for 8 years. He now runs Intelligent Advisor IT Consulting OÜ. Owner of intelligent-advisor.com, he also is Co-Founder of the Siebel Hub.

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