Apache TAP (Test Application Portal) is an experimental visual analytic sandbox for interacting with exploring Apache UserALE data. TAP features registration features served through Django–register your application, organization, and yourself to control access to your applications' usage data and manage custom configurations in TAP. TAP also provides you with a customizable array of interactive visual analytic libraries to extract insights from your usage data. Through TAP you can explore how users interact with each element of your application, and how they interacted with each of them. With TAP you'll also be able to visually compare usage between different segments of your user base and perform A/B usability testing between different versions of your application–you'll have access to any data you collect on your users and statistics, metrics or modeling output that is built into Distill. TAP also provides you with beautiful custom D3 visualizations of your users' workflows in your application. See how they do work with your application and learn how your application design augments their workflow or prevents them from discovering other features. TAP is designed for customization.

Features

Understand your users

TAP allows you to visualize how you application is used by different sets of users based on their characteristics (e.g., geography, demographics).

Understand how your application is used

TAP comes with custom visualization for how your users interact with elements of your application in sequence revealing insights about how application design affects usage and efficiency.

Control access to your data (coming soon)

Control permissions for how your organization can access user data by setting permissions at the institutional level down to access to data collected from specific applications.

The Bowie Plot

Tap uses the Bowie plot to present your users' micro-workflows and help you uncover insights into how your users interact with you apps. Start on the left, with the activity that starts the workflow, sized by the frequency of the activity. Next, the circles in the middle show the second activity in the workflow. The circles are downselected and sized by a graph metric to help uncover a particular type of insight. End on the right with the final activity of the workflow.

Graph Metrics