Meaning making through data representation: Construction and Deconstruction

November 10th, 2014 | EVALUATION

To better help museum visitors make sense of large data sets, also called “big data”, this study focuses on what museum visitors felt individual layers of a visual (alone and in combination with other layers) were communicating to them as the visual was constructed or deconstructed layer by layer. A second, smaller study, collected data to better understand how adult visitors would construct large data visualizations. This study was concerned with how people make sense of “big data” in their daily lives and how they engage with reference systems. The primary study used four different “big data” visualization booklets composed of the layers necessary to create the graph or map. The choice of visualizations was intentional, building on the results of a prior study on visualization recognition. Study participants were given one booklet and guided through the process of trying to describe meaning made from the various layers of the visualizations. Participants went through this process twice, once for construction and once for deconstruction. The evaluator notated what they heard for each layer as the participant viewed the visualization layer by layer. Participants in the second, smaller study thought aloud as they created the graph or map from the color transparency layers of one visual. A key insight that emerged from this study is the relationship between the complexity of a data visualization and guests’ ability to make meaning from those representations. Data visualizations exist on a continuum from simple to complex. Guests’ knowledge of and familiarity with data visualizations exist on a continuum from unfamiliar to familiar. Although typically science centers and museum visitors have more education than the general population, the visitors in this study represent a range of understanding of data visualizations. Those with less familiarity understood common graphics (map of the United States) and chart representations (XY axis, bar graphs). Those with advanced understanding of visual graphics were familiar with both basic and more complex visuals. To accommodate a wide variety of visitors, science centers and museums need to meet guests where they are and provide opportunities for increased engagement with and understanding of data visualizations. Given the range of familiarity with data visualizations observed across the four sites and two studies, exhibits should be designed to begin at a basic level and have the potential to increase in complexity to interest those with considerable knowledge of data visualizations. Visitors engaged in constructing the graphics were more likely to use cumulative reasoning; making deeper meaning as they viewed the graphic one layer at a time. Also, those involved in the freeform graphic construction appeared to better understand and interpret the visualization. Finally, visitors engaged in deconstructing the graphics were unable to “forget” contextual information provided in the complete versions and generally did not articulate new interpretations of the stripped down visuals. This suggests that deconstruction may be a less productive approach to use in an exhibit experience as it does not seem to support sustained engagement or exploration of the data being represented.



Team Members

Indiana University, Contributor
Mary Ann Wojton, Author, Lifelong Learning Group


Funding Source: NSF
Funding Program: ISE/AISL

Related URLs

Pathways: Sense-Making of Big Data


Audience: Adults | Evaluators | General Public | Museum | ISE Professionals | Youth | Teen (up to 17)
Discipline: Computing and information science | Education and learning science | Technology
Resource Type: Evaluation Reports
Environment Type: Exhibitions | Museum and Science Center Exhibits | Museum and Science Center Programs | Public Programs