Define items

Define items is a way of allowing MINT to recognise where an item (a record) begins in your dataset. In a simple flat dataset this may seem quite obvious. In an XML file which includes a header and different blocks of information, you need to identify the point (or node) that forms the root of the item records in your dataset.
Go to your workspace and click on the name of the dataset. Under dataset options, click on Define Items. A pane will open showing a tree representing the structure of your dataset on the left side and the information that you need to specify on the right:
  • The item level of your dataset
  • The item label (title) to use in listings
  • The unique identifier for each item
Define items
You can drag the relevant elements listed in the tree and drop them in the appropriate text boxes on the right. By clicking on the information icon
you can get more information and statistics about each element. Notice also that the elements displayed in green have a unique (or distinct) value for every item in the dataset.
  • The item level is the point at which item records begin
  • The item label is the information that will be displayed in listings in MINT, it must be a unique value
  • The item id is used for identification in MINT and must be a unique value.
  • You may use the same element to provide both the item label and the item id.
Once you have defined the item level, the label to use and the unique identifier click Done.
When you return to the Dataset options, you will see the number of items is displayed next to the option to Show all the items.
Show all items
Note: It is important to check that the number of items displayed by MINT after defining the item level matches the number you expect to see. If there are less than expected this may be because you made a mistake in selecting the item level or because your dataset lacks a unique identifier. Contact the CARARE support desk if you need advice on how to proceed.
Once the item level has been defined correctly you can browse the items, look at the dataset statistics and start the mapping process.