Users can choose any topic attribute as the collection criterion as an easy and intuitive way to collect data.
Create a topic and set the Priority 1 icon on it. Select the topic, and click the Collect Data button. MultiMaps will collect topics with the Priority 1 icon under this topic.
Remove the Priority icon and set the Progress to 100% so MultiMaps will collect all topics with this icon (completed tasks).
Assign a Resource to this topic, and MultiMaps will collect topics with this Resource.
If you haven't previously removed the Progress icon, MultiMaps will collect only completed tasks with this Resource. So, you can combine topic attributes. This method gives you added flexibility when designing collection criteria.
You also can create a topic with a Priority 1 icon and assign a Resource to a subtopic. MultiMaps will collect topics with this Resource and the Priority 1 icon. This construction is an example of a simple cascade of filters.
This is a very simple and intuitive way, but not flexible enough. In addition, you can’t fulfill complex queries in this way at all. For example, MultiMaps can collect data for such queries (and these are far from the most complex queries):
These methods are simple and intuitive but not flexible enough. They will not allow you to design complex queries. MultiMaps can collect data using complex filtering. The following moderately difficult search criteria illustrate what is possible:
of these queries uses the appropriate topic attributes (listed in parentheses). But how to set them on the collection topic?
No way. This is done with a data collection Macro Language.
It tells how to combine criteria, how to use a date range, how to compare numeric attribute values ("costs greater than 1000"), how to copy the collected data, how to sort it, and so on.
You may not understand it, and yet create any queries you need, MultiMaps has all the necessary tools to make it easier for you to build them.
In the following sections, you'll see how you can use different topic attributes to collect data and how the data collection Macro Language extends their capabilities.