DataBlocks is a table-top, graspable user interface with which to interact with data and create visualizations. We are developing a package that includes software that allows users to transform tabletop objects into interactive tokens. Our setup consists of a webcam, and everyday objects that are tagged with fiducial markers. The unique markers on the objects are read by a webcam, and manipulating the objects creates and alters visualizations that are displayed on screen.

This video demonstrates a simple two user scenario for DataBlocks. In this example, we are looking at radio station listener demographics in the Greater Toronto Area, broken down by age and gender.

What does it do?

DataBlocks allows users to create and interact with data visualizations
using table-top objects.


We define two sets of objects, tokens and widgets.

This video demonstrates some specific interactions with a bar graph visualization of radio station listener demographics, walking through adding and removing data from the visualization. It also shows how bars can be sorted on screen, and demonstrates the use of a widget to provide additional detailed views of the data.

How does it work?


The objects are tracked by means of a camera placed beneath a transparent tabletop. The bottom of each object is marked with a fiducial marker specially designed to be identified by the reacTIVision software, and the camera placed below the table captures the image of the fiducial markers in real time. The fiducial markers are read using open-source reacTIVision software. The reacTIVision software outputs the ID of each identified marker and its X and Y coordinates, if they are in the field of view of the camera, and this information is interpreted by the TUIO protocol and then input into our software, which constructs the visualizations from a database, filtered by the user’s query.

Why did we make it?

Research has shown that interacting with tangible user interfaces enhances collaborative behavior, enhances learning, and improves user experience. We have developed Datablocks to bring these benefits to data analytics. Data analytics tends to be something that people undertake by themselves, but our product allows people to work collaboratively with complex datasets.

What makes Datablocks unique is that it is flexible and accessible. We have designed an open source software that is user friendly and easy to disseminate. Our product does not require any specialized hardware. Users can download our software, enter or upload a dataset, print out markers, and attach them to whatever objects they want to use.

Datablocks makes analytics enjoyable and playful. Our design allows people to interact with data in a direct and intuitive way, and helps to improve communication and engagement amongst working groups. It can break down language barriers and make data analysis more accessible to people with different learning styles, or be used as a learning tool for both children and adults.

About us

This research was undertaken at OCAD University
in the Visual Analytics lab.

Ana Jofre*
Stephen Tefeinbach-Keller
Lan-Xi Dong
Steve Szigeti
Sara Diamond

*Now at SUNY Polytechnic

For more about the Visual Analytics lab at OCAD University, see:
The Visual Analytics Lab at OCAD U
Project Publications
  • Jofre, A., Szigeti, S., Tiefenbach-Keller, S., Dong, L.-X., Diamond, S. “Manipulating Tabletop Objects to Interactively Query a Database” (2016) CHI’16 Extended Abstracts (Chi 2016 San Jose May 7-12)

  • Jofre, A., Szigeti, S., Diamond, S. "Citizen engagement through tangible data representation" Foro de Educación (January-June 2016) vol. 14, n. 20

  • Jofre, A. Szigeti, S., Tiefenbach-Keller, S., Dong, L.-X., Tomé, F., Czarnowski, D., Diamond, S. (2015) "A Tangible User Interface for Interactive Data Visualization" Proceedings of the 2015 Conference of the Center for Advanced Studies on Collaborative Research. IBM Corp., CASCON2015, November 2-4, 2015, Toronto, Ontario.

  • Szigeti, S., Stevens, A., Tu, R., Jofre, A., Gebhardt, A., Chevalier, F., Lee, J. & Diamond, S. (2014) Output to Input: Concepts for Physical Data Representations and Tactile User Interfaces. Proceedings of CHI14 Works‐in‐Progress (Toronto, ON).