Designing interactive systems that meet conflicting user needs can be hard and costly. Sometimes, it’s not clear what design direction to follow and it can be difficult to anticipate people’s reactions.
In this project, we were looking at the design space of personal data management tools. We knew that different people manage their data in different ways, so we wanted to explore possible directions in the design space early in the design process before committing to costly prototyping efforts.
We decided to create five different concepts, in the form of video prototypes, that embody different ideas and design dimensions. Then, we used the five video prototypes in a user study with 16 participants, where we asked for reactions to the ideas behind each concept.
The videos allowed us to push the design dimensions in specific directions, often exploring their extremes in new combinations. They also let us show to participants the possible future scenarios of use we had in mind, rather than just telling them.
The five concepts we created are Patina, Data Recommender, Temporary Folder, Temporary App, and Future Filters. Read about each of them below.
- Ideated and designed the concepts.
- Created the prototypes, using Sketch and InVision.
- Ran the elicitation study with 16 participants (recruited, conducted all interviews, analyzed the data).
- Wrote the final paper based on the project.
Team: Will Odom and Joanna McGrenere.
The first concept, Patina, is a visualization on top of data in the geometric form of a spiral. It is inspired by a tree’s growth circles and symbolizes the temporal qualities of data. In the video for Patina, we show two different options for the spiral: on a desktop, it represents the age of folders; with a set of music playlists, instead, it represents the number of interactions over a period of time.
The second concept, Data Recommender, is a smart system that notifies users and provides recommendations on data that might need attention, using metadata like last access, creation date, or size. Users can decide to trash items, archive them in a central archive, move them in a specific folder, or be reminded of them at another time. Data Recommender will use machine learning to learn from their actions and provide new recommendations.
Temporary Folder & App
The next two concepts come as a couple: Temporary Folder and Temporary App. In this case, we created two videos on two different platforms. The first, Temporary Folder, takes place on a desktop computer: it acts as a standard folder, but users can decide to set an expiration date for it. After the expiration date, the folder will be automatically deleted.
The second, Temporary App, takes place on a smartphone. In this case, users can install a mobile application temporarily (e.g., for two weeks). At the end of the preset period, the application will be automatically uninstalled.
The final concept, Future Filters, is a mobile application that lets users decide what to do with data in the future by creating rules or filters. For example, “delete selfies and downloads that are older than two months when my free space is below 20%,” or “archive shared documents not looked at in 2 years,” and so on. Filters use a set of actions (e.g., delete, move, archive, remind me), criteria (size, use, number of copies, source of data, copied on the cloud, etc.), and triggers (a new update available, free disk space is below a certain amount, etc.)
In the paper we published at DIS 2019, you’ll find more details about the research questions we wanted to answer in the study and how participants reacted to the concepts. Spoiler alert: there was love for them, but also hate.