Making Data Stories

The data stories tool was built in collaboration between academic researchers and a web developer, in an iterative process over a period of about two months. The tool was built as a WordPress plugin.

In previous research, Anna (Wilson, 2020) noted how research participants create speculative stories around elicitation materials in order to fill in gaps and generate meanings.  A similar phenomenon has also been described in the relationship between viewer and film in the cinema (Singh, 2011). In both contexts, it seems that spontaneous, wild imaginings arise out of encounters between people and stimuli that become, in the interaction, “story-objects”. Our aim was to build on this natural turn to storytelling in order to draw out important insights about surveillance in higher education.

Initially the project was intended to involve co-creating speculative stories in face-to-face workshops. The Covid-19 pandemic and its impact on universities forced a rethink of these plans. The project team drew back from the initial aim of co-creating stories during the project lifetime and instead worked to design a tool that would allow participants to create stories in the future. 

Our first step was to explore whether story-objects could be generated from existing speculative data stories and then whether these could be used to encourage the generation of new story-object assemblages.  To this end, Anna analysed two stories created by Amy (one of these can be read in Collier and Ross, 2020 – see the Reading List). These stories were broken down into actors and actions/interactions. The original story-assemblages explicitly reflected lines of articulation and flight through references to emotion, affect and contextual factors such as place, time, procedures and (often hierarchical, territorialising) organisation. We created four lists of story-objects from the two original objects, under the headings Actors, Actions/Interactions, Attributes and Context, with Context subsequently broken down further into Time, Space, Backstory and Economic Context. A random-number generator was used to choose a selection of story-objects from each list. Anna then worked with these story-objects to create a new story, breaking the relationships between them in the original stories and re-configuring them to express a new possible future.

Reflections and discussions within the team on this process suggested that the lists of story-objects were over-specific and might constrain rather than enable potential participants’ imaginations.  The process also neglected the lived experiences of the potential participants. Following further research into other story-generating tools, we adapted the process to use prompt questions to generate the initial story-objects. The prompt questions were scripted following a detailed analysis of research literature on surveillance in Higher Education (see the Reading List).  This literature was read and analysed to identify repeated themes and concerns, and a series of questions was drafted that prompted respondents to explore whether these themes or concerns were relevant in relation to an experience they had personally undergone. 

These questions, and their usefulness in helping participants to start to create speculative stories, were trialled with seven Learning Technologists and other stakeholders in sessions conducted over video calls. These resulted in stories of varying degrees of development, with some participants more quickly able than others to take the story-objects generated by answering a few of the prompt questions and turn them into a narrative. 

An iterative process of building, testing and refining led to a three-part data storytelling tool: prompts; mapping and writing. Prompts and mapping help users identify actors and explore possible interactions between them, while the writing section gives a space to write an anonymous story. We have not been prescriptive or assumed that everyone has to use all three. People can opt to bypass either of the first two stages, and ‘writing’ can  mean visual or multimodal storytelling through images, videos and drawings as well as text. The finished story can be saved, and also (optionally) submitted to be shared publicly on the datastories site. 

To develop the data stories creator, we worked with Pat Lockley, whose expertise in developing for WordPress meant we could create a tool that would subsequently become open as a plugin for others to adapt and use. In a series of discussions we identified key functionality, drawing from Anna’s trials, discussions with Jane about storytelling, the analysis of the existing stories, and considering concepts like mindmapping, multimodal writing, and the use of questions to generate fictional accounts. 

The tool allows for formatted HTML text (bold, italic, underline and varying font sizes), various embedded options (primarily twitter and youtube), gifs from GIPHY, images and an option for the author to draw something. The author can add any of these items and present them in any order. 

Although based in WordPress, the system runs in a peripheral form and engages with WordPress via a series of API calls. A problem with any platform which allows for user content to be created is whether or not to force people to register. Registration approval creates a work overhead, but doesn’t guarantee the creation of stories. By moving the work into story approval, the overheads are more focussed on content, and not user administration. WordPress has recently changed the default editor, and this has led to much discussion over the benefits and drawbacks of each one. The Data Stories editor has a specific feature set for this project, and doesn’t depend on which editor the WordPress site uses. 

The tool uses a WordPress feature called “custom post type”, to allow for the system to treat the stories like other WordPress content. Using filters and actions (key WordPress development features) the standard WordPress administrative tasks can be recreated for data stories, hopefully reducing any issues with learning how to use the tool. The tool does require stories to be approved before they are publicly available. 

The tool was launched in mid-September 2020.

  • Anna Wilson, Pat Lockley & Jen Ross