Regarding the typology of the graphic news representations, there is no standard classification reference, perhaps because digital techniques and tools are constantly evolving. Among others, the taxonomy proposed by Rodríguez and Salgado (1989) stands out, in which they divide the news graphics into two broad groups: statistical news graphs and illustrative news graphs. Those representations that inform quantitatively and relate numerical variables are in the first group, such as bar charts, column charts, circular charts, linear charts, area charts, or statistical tables. Those that show the reader how an event or fact has occurred and present information that is better understood visually rather than verbally are in the second group, such as infographics, maps, symbols, illustrations, comics, animated iconography, explanatory and organisational graphs.

Works based on data journalism show how the lack of standard categorisations leads to a lack of consensus when working with visualisations. Knight (2015) established a categorisation according to the complexity of the data elements and found that infographics and maps were used the most. Tandoc and Soo-Kwang (2017) analysed the Guardian data repository and noted that the tables were the most frequent element, while Stalph (2017) –examined Zeit Online, Spiegel Online, The Guardian, and Neue Zürcher Zeitung–, Loosen, Reimer and Schmidt (2017), Young, Hermida, and Fulda (2018) and Ojo & Heravi (2018) –focus on the analysis of the Data Journalism Awards– finding a predominance of static graphs, maps, and images.

As with typology, there is no common operalisation for the variables in interactive functions. The first to propose a reliable classification was Schulmeister (2003), who distinguished six levels: from the static visualisations to stage VI, which incorporates feedback. Yi, Ah-Kang, and Stasko (2007) established a classification with seven techniques according to the user’s intentions: select, explore, reconfigure, code, summarise, filter, and connect. Segel and Heer (2010) differentiated between floating details, filtering/selecting/searching, navigation buttons, limited interaction, explicit instructions, and tutorials. Finally, Boy, Detienne, and Fekete (2015) designed a categorisation based on Yi’s, Ah-Kang’s, and Stasko’s (2007): inspect, connect, select, filter, explore and narrate. The remaining works examine interactivity or combine the above approaches (Loosen, Reimer, and Schmidt, 2017; Stalph, 2017; Tandoc and Soo-Kwang, 2017; Young, Hermida, and Fulda, 2018; Ojo and Heravi, 2018; Appelgren, 2018). Despite the different methods used, the authors foresee reduced interactivity, as necessary and limited functions such as search, filtering, and selection are incorporated. This paper proposes three main objectives:

O1: To determine the characteristics of the visualisations incorporated into the reference data journalism stories, those nominated for the 2019 Data Journalism Awards, provide a current analysis of their use.

O2: To identify differences and similarities between the nominated stories and the award-winners in the 2019 Data Journalism Awards by analysing the visualisations’ typology, interactivity, and functionalities.

O3: To establish a classification of the interactive elements according to their purpose.