LibInsight @ FIU

The Datasets page will display a filterable and sortable list of all of the datasets you have access to. Each will include shortcuts for recording and/or analyzing data (depending upon your permissions).

With a ​Circulation​ dataset, you can record either individual transactions or just your aggregate monthly transactions. These datasets are designed to import circulation data that you've exported from your ILS, so the type of recording option you choose should correspond to the type of data you are exporting.

In this course, you'll learn to set up and use a Circulation Dataset. Circulation datasets allow you to collect data about items that your library circulates. You can import either individual transactions or aggregate monthly totals. These datasets are designed to import circulation data that you've exported from your ILS, so the recording mode you choose should correspond to the type of data you are exporting.

In this course, you'll learn to set up and manage an ILL Dataset. ILL Datasets can be used to store aggregate data about the number of items you borrow from other institutions as well as the number you lend. When configuring the dataset, you can set up custom categories to track more granular information such as partner institutions that you borrow from and lend to or reasons why loans may not be fulfilled. In addition to dataset configuration, this course covers recording data, analyzing data, and managing records. You'll also learn about comparing data from one dataset to another.

The ILL dataset allows you to record and analyze your aggregate interlibrary loan data. Analyze your total borrowing and lending volume by day, month, or year. See the ratio of article requests vs. loan requests. Break down your requests by status and reason for cancelation. You can also track borrowing and lending with partner institutions, which is great if you need to compile stats for regional or consortial groups.

The Cross Dataset Analysis tool allows you to compare up to 4 variables from one or more datasets. This can provide some really useful insight for seeing trends across services or resources over time.