Custom datasets: everything you need to know
Custom datasets allow you to design your own dataset from scratch, allowing you to analyze data for just about anything! You define the type of date/time stamp to use, as well as the different types of fields (such as text entry, checkboxes, radio buttons, etc.). The distribution of responses in each field can be analyzed, as well as your dataset's overall distributions and trends over time.
These types of datasets are great for time-based or transactional data, such as:
- Reference questions
- Instruction session requests
- Pre- and post-session assessments
- Library feedback surveys
With widgets, you can even allow users to record data from outside of LibInsight. This is especially convenient if you have a feedback survey, as this will allow patrons to easily submit data.
In this Springboard, you'll learn how to create and configure a custom dataset, as well as record, upload, and analyze data.
Custom datasets are available to both LIbInsight Lite and LibInsight Full customers. To create a new dataset, Admin users can go to Admin > Manage Datasets and click the Add New Dataset button.
Remember: if you're using LibInsight Lite, your subscription will have a limit to the number of datasets you can create. Your limit will display at the top of the Manage Datasets page. If you're interested in increasing your limit or upgrading to the Full version of LibInsight (which allows for unlimited datasets), contact our Springy Sales team.
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 timestamp works best for your data? When you record a new entry, it will include a timestamp. For datasets where you want to analyze durations (such as instruction sessions), select the Start & End Date/Time option. Otherwise, you can choose to record a single date & time; just the date; or the month & year (not the day). You can also choose to automatically calculate a single date & time stamp, which will happen at the moment a user submits the new record.
- Important: once you start collecting data, you cannot change the timestamp type. This can only be changed while the dataset is empty, so it's important to think carefully about what option will work best ahead of time.
- 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 extended 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 data do you want to collect? It can help to sketch out a list of all of the data you want to collect and analyze. Once you have a list, consider what type of field is best suited for that data. See the Available field types panel below to learn more about each type.
- In addition to the required timestamp, all submissions will include a required Entered By field (who "owns" the record), as well as an optional Internal Notes field where you can leave a comment about the data.
- You can also choose to enable or disable recording the submitter's IP address and submission source (where the record was entered, such as the Record Data page or a widget).
- When adding your fields, you can arrange them in up to three columns.
|Field type||Ideal use||Options||Analysis features|
|Text||Choose Text Fields to capture text-based information, such as names, comments, etc. Use the Instructions field to instruct users on how to enter data, ex: "Use the format Lastname, Firstname".||
||When analyzing data, you can search/filter for info in Text Fields. If you want to restrict the data entered, you should set up Option Select fields instead.|
|Numeric||Choose Numeric Fields to capture numerical info (integers only), ex: # of attendees, # of items, # of minutes spent preparing, etc. Use the Instructions field to instruct users on how to enter data, ex: "Record time in minutes".||
||When analyzing data, you can run statistical analysis on the numeric field to capture things like average values, totals, maximum/minimum/median values, etc.|
|Monetary||Use this field when entering amount values like money or cost. It accepts whole amounts and up to 2 decimal points. Amounts will be displayed using the Currency Symbol from your System Settings.||
||When analyzing data, you can run statistical analysis on the monetary field to capture things like average values, totals, maximum/minimum/median values, etc.|
|Calculated||Use this field when calculating the sum, difference, product and quotient of 2 or more Numeric or Monetary Fields. Because this field types uses information in other fields, its contents cannot be edited except on this screen.||
Replace field_* with your Numeric or Monetary field ID found in the Fields drop-down.
|When analyzing data, you can run statistical analysis on the calculated field to capture things like average values, totals, maximum/minimum/median values, etc.|
|Single Select||Single Select is best when selecting a single value from many. Can be formatted as a drop-down menu, list or radio buttons. To be able to select multiple values, use Multi Option Select instead.||
||The best thing about Single Select fields? The reports! Create Line, Column, and Pie charts, and run Cross Tab reports to compare 2 Option Select fields. (Note: The number of options you have will affect the speed of generating your reports. Fewer options will generate faster reports than fields with more options.)|
|Multi Select||Use this option when you want to capture multiple values with a single field. It can be formatted as a scrolling list, or as checkboxes. Want to make sure users can only select one option? Choose Single Option Select instead.||
||Just like Single Select fields, Multi Select fields include powerful reporting options. Create Line, Column, and Pie charts, and run Cross Tab reports to compare 2 Option Select fields. (Note: The number of options you have will affect the speed of generating your reports. Fewer options will generate faster reports than fields with more options.)|
|Scale||Use the Sliding Scale Field when you want to present users with values on a 1-5 or 1-10 scale. Examples include "Strongly Agree / Strongly Disagree", or "Very Likely / Not Likely", "It was mind-blowing / It was mind-numbing", etc.||
||Just like Single and Multi Select fields, Scale fields include powerful reporting options. Create Line, Column, and Pie charts, and run Cross Tab reports to compare 2 Option Select fields.|
Use DateTime when users need to enter time-related information - either date, time, or both. You can have just the date, or just the time, or the complete date/time information as part of the input.
||Unlike each record's timestamp, please note that DateTime fields are not used in distributions, duration, or time-based analysis reports. The data in these fields can only be viewed in the Data Grid or in export files.|
|Text Block||Use this field when you want to put a title, heading or information that do not need any user input.||This does not accept user input -- it is only used to display text on the Record Data page.||n/a|
|Divider Line||Use this field when you want to put a dividing line (i.e.
||This does not accept user input -- it is only used to display a line separator on the Record Data page.||n/a|
- Create or copy a Custom dataset
Learn how to create a custom dataset from scratch, or copy fields from another custom dataset in your system; define the dataset's permissions; and set up your dataset's fields.
- Editing the info and timestamp options for an existing Custom dataset
Learn how to customize an existing dataset's info, description and (if the dataset is empty) timestamp option. You will also learn how to add optional custom JS/CSS code and a custom page footer.
- Editing an existing dataset's user permissions
Learn how to add, edit, or remove permissions for Regular users in an existing dataset.
- Customizing fields in an existing Custom dataset
Learn how to add, edit, delete, and reorder fields in an existing custom dataset.
There are three primary ways you can add data to your custom dataset:
- Manual entry: users who have permission to record data can enter it manually via the Record Data page in LibInsight. Depending upon your dataset's settings, users can add one or multiple records at a time.
- When manually adding records, you can create and use pre-defined entries. Think of these as templates that can make recording commonly-added records quicker and easier: when a user selects a pre-defined entry, it will automatically populate the Record Data form's fields using the entry's preset values. Users can then make any changes they need before submitting the new record.
- Upload in bulk: in addition to manually adding individual records, you can upload data in bulk via a CSV or Excel file. LibInsight will provide you with the list of field names your file must include in order to be uploaded successfully.
- In general, the column headings in your spreadsheet must match the field names in your dataset. All required fields (such as the Start Date) must be present, but optional fields (such as Internal Notes) may be omitted.
- When uploading a file, make sure that you select the date format that matches the format used in your file's Start Date column. You can set the default date format for file uploads by customizing the System Date Format in your system settings.
- Widgets and APIs: these alllow you to add data from outside of LibInsight.
- Widgets can either be fully embedded in a page, launched via a button or side-tab, or display as a standalone page with a direct URL. No matter which type you choose, widgets can be configured to allow anyone (including non-account holders) to add records or require users to first authenticate with their LibInsight user account.
- APIs allow you to add data via a hosted script using the POST method. LibInsight will provide you with the the form data and parameters to use for adding records to your dataset.
By default, users who have permission to add data can also edit or delete their own records. Users with Admin permissions, however, can edit or delete any user's records in the dataset.
Add and manage data
- Record, upload, and manage your records in a Custom dataset
Learn how to manually enter or upload data, as well as editing or deleting the data you've added.
- Managing uploaded files
Learn how to view, download, and delete files that were uploaded to your dataset.
- Managing uploaded files
- Creating pre-defined entries
Learn how to create a new pre-defined entry for your custom dataset.
- Search and replace records in Custom and Reference datasets
Learn how a dataset's Admin users can search and replace values in a custom dataset's records.
Create widgets and APIs
- Creating a URL-based widget
Learn how to create a widget that displays as a page with its own friendly URL. Use this if you want to direct users to a standalone webpage to enter data.
- Creating an embeddable popup widget
Learn how to create a pop-up widget. When users click the embedded link, the data entry form will display inside a modal window on top of the current page.
- Creating an in-page iframe widget
Learn how to create a widget that displays the data entry form inside of an embedded iframe. Use this option if you want to display the entire form inside of another page.
- Creating a side button widget
Learn how to create a widget that displays as a button at the side of the page. When users click the side-button, the data entry form will display inside a modal window on top of the current page.
- Create a POST API for a custom, shared, reference (individual transactions), or gate count dataset
Learn how to create an API for adding data via your own script, using the POST method.
- Managing your widgets and APIs
Learn how to edit or delete your widgets and APIs.
When analyzing a custom dataset, you'll find the following reports:
- Data grid: provides a list of all records included in your report. From this view, records can also be edited and deleted. Admins have the ability to edit or delete any record. All other users can only edit or delete the records that they've entered.
- You can filter the data included in your report by one of several date & time filters, as well as by field value(s).
- Use the Export Data tab to download a copy of this data in CSV format.
- Field Analysis: provides you with an in-depth look at the responses for individual fields.
- Time-Based Analysis: allows you to track your data over time. This can include the total number of entries added to your dataset, as well as sum of Numeric fields and distribution of Select fields. You can analyze data by year, month, day, or hour.
- Duration: If your dataset includes both a Start Timestamp and End Timestamp, this report will allow you to analyze the duration of each record.
- Distributions: provides a breakdown of your data over time (i.e. year, month, day of the week, hour of the day) and by the Entered By user.
- Cross Tab: allows you to compare the relationship between two fields.
- Trends: allows to see how the totals of your numeric data has changed over time (i.e. the past 2 years, 3 years, 5 years, or even 10 years). In addition, you'll see year-over-year changes and the percentage change against the first year of the report.
In addition, LibInsight includes other tools to help you analyze, visualize, and share your data with others:
- Dashboards: dashboards allow you to display charts of key data points from one or more datasets on a single page. Dashboard pages can be public or private, allowing you to create and share dashboards internally with staff or with the public.
- Cross-Dataset Analysis: allows you to compare up to 4 variables from across one or more datasets. This can provide some really useful insight for seeing trends across services or resources over time.
- Analyzing and exporting a custom dataset
Learn how to generate a report, apply filters, and export your data. This includes an overview and example of each available report option.
- Comparing multiple datasets using the Cross Dataset Analysis tool
Learn how to generate a cross-dataset analysis report to compare multiple datasets at once.
- Creating a dashboard
Learn how to create a dashboard to visualize and share key data points from your datasets.