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.
Your data can be analyzed with the following reports:
- Monthly or yearly overview of your total circulation
- Breakdown of circulation by group (i.e. your dataset's single-select fields)
- Cross-tab relationship between single-select fields
- Distribution of circulation by call number classification
- Review of annual trends in total circulation, as well as circulation by group and call number classification
- 100 most popular titles, based upon number of copies circulated
In this Springboard, you'll learn how to create and configure a circulation dataset, as well as, upload, and analyze data.
Circulation datasets are only available in LibInsight Full. To create a new dataset, Admin users can go to Admin > Manage Datasets and click the Add New Dataset button.
Before you begin, you may find it helpful to do a little planning. This can make the process of creating your dataset go more quickly.
- What type of recording mode works best for your data? When you start recording data, the type of recording mode that you've selected will determine the type of data that can be accepted in the dataset. You can choose from: individual transactions or aggregate counts.
- Who should have access to the dataset? By default, only Admin users are allowed to manage, record data to, and analyze a dataset. However, you can choose to extend each of those permissions to selected Regular users, or all Regular users in your system. For example, if you only want a few people to add data to your dataset, you would extend them Record permissions. But, if you want everyone in your library to be able to view and analyze (but not edit) the data, you could choose to give Analyze permissions to all Regular users.
- What fields will be included with your circulation data? Because Circulation datasets only accept uploaded data, it's important for the field names in your dataset to match exactly with the field names in your import files. LibInsight allows you to either manually create the fields in the dataset or import them from a spreadsheet.
- Create a Circulation dataset
Learn how to create a circulation dataset from scratch -- including the recording mode and setting up the fields in the dataset.
- Change the info and recording mode of a Circulation dataset
Learn how to customize an existing dataset's info, description, and recording mode.
- Editing an existing dataset's user permissions
Learn how to add, edit, or remove permissions for Regular users in an existing dataset.
- Editing fields in a Circulation dataset
Learn how to edit the fields in an existing circulation dataset.
Records can be only be added to a circulation dataset by uploading the data via spreadsheet. You'll be taking the data that your ILS outputs in a spreadsheet file and uploading into LibInsight. As you're preparing your data for uploading, you will need to make sure that the columns in your file match exactly with the fields that you have set up in the dataset. Otherwise, your upload will fail.
- Uploading data to a Circulation dataset
Learn about all things related to recording/importing data to the dataset.
- Managing uploaded files
Learn how to manage files you've uploaded to the dataset.
Once you have some data in your dataset, you can utilize LibInsight's powerful analysis tools to get a better understanding of what the data you've collected means. For circulation datasets you'll have access to:
- Overview report: will provide you with a monthly or yearly look at your data between the date range you specified.
- Groups report: allows you to see the distribution of responses by group (aka your dataset's Select fields). For example, if you have a Select field for Location, this would give you a breakdown of your transactions by location.
- Cross Tab report: allows you to see the relationship between two groups. For example, if you have a Fund Code field and a Location field, you could see how many items were checked out by fund code for each location.
- Classifications report: when your dataset contains a Call Number Class field, this report allows you to see the distribution of circulation transactions by call number classification.
- Trends report: allows you to compare the current year to previous years so you can analyze trends in your circulation. This will not only help you visualize these trends, but you will also be able to see details such as year-over-year changes and a comparison of the current year to the first year included in your report.
- Popular report: ranks the 100 most popular titles, based on the total number of copies acquired.
- Show recs report: allows you to view a detailed list of all records included in your analysis.
Additionally, you can compare your circulation data with other datasets using the Cross Dataset Analysis tool. For example, you may want to compare your book circulation totals with the number of visitors to the library to see how often they're checking books out when they're in the library.
Lastly, you can pull your circulation data into a dashboard to provide an overview of how circulation impacts your library's metrics. Dashboards can be used internally, or you can create public-facing dashboards to give your community real-time insight into the usage of their library's services.
- Analyzing and exporting a Circulation dataset
Learn how to analyze your circulation dataset.
- Comparing multiple datasets using the Cross Dataset Analysis tool
Learn how to use the Cross Dataset Analysis tool.
- Create, edit, and manage a dashboard
Learn how to build and manage a dashboard.