Table 2: Distribution of the functions of the interactive visualisations

Source: created by the authors

By focusing the study on the awarded works, it is observed that the visualisations are divided between static (66.67%) and “purely” interactive (33.33%). Except for the option to explore, which is incorporated in all the interactive works, there are no notable differences in the rest of the functions, since the possibilities of connecting, selecting, personalising, narrating, and summarising are used to same extent (50%). In the nominated projects, 50% of static displays are shown, 38.89% of mixed visualisations, and 8.33% purely interactive. Slight divergences are found here, as the functions are used differently, browse (100%), filter (52.94%), select (17.64%), summarise (11.76%), and connect (5.89%).

4. Discussion and conclusions

One of the main objectives of this study (O1) is to determine the characteristics of the visualisations incorporated into the referenced data journalism stories, those nominated for the 2019 Data Journalism Awards to offer a current analysis of their use.

Along similar lines to those in Knight’s research (2015), Loosen, Reimer and Schmidt (2017) and Stalph (2017), the works in the sample include an average of two visualisations per item (M=2,40), most often incorporating a single one structured as a story, giving it more space than the text in general. The visualisations mainly focus on showing relationships or associations between variables and temporal changes, an indicator similar to that obtained in the previously mentioned works (Knight, 2015; Loosen, Reimer and Schmidt, 2017; Stalph, 2017), in which they compared values and reflected changes over time.