As a research output of the Algocount project, PlacPlac is a digital dissemination format to store, stage, and access the results of data sprints after research activities. Within the academic context, data sprints are multidisciplinary events where teams of researchers, doctoral and master students from various disciplines, such as Science and Technology Studies, Future Studies, Sociology, Media Studies, and Digital Humanities (Bounegru et al., 2018; Ciuccarelli and Elli, 2019) come together to best achieve a given goal through practice-based research.

The dissemination format is intended as a digital place that allows researchers to expose the research process with Digital Methods (Rogers, 2013), namely collections of web-native techniques for research on cultural change and societal conditions. PlacPlac emphasizes telling the research process and articulating the content that reinforces the use of images, visualizations, and audiovisual material, among others.

Indeed, it condenses and reinterprets good practices already used in current formats for disseminating data sprints such as Wikis, written reports, or slides. Working with different layouts and ordering blocks requires a clear perception of the results that are being presented. However, as emerged from the focus group, the stress test, and the application case, the format gives users room to be thorough, and it provides complete information while still maintaining flexibility. The suggestion to contextualize the research object situates the experiments in space and time.

Providing information about the characteristics of the research object at the time the experiment was done becomes significant when imagining researchers reading the experiment in a couple of years. Thanks to the possibility of adding datasets, tables, animated images, and interactive visualizations the research process has more space in the format. Explaining the steps using screenshots simulating the actual use of tools not only gives researchers the freedom to describe the research as thoroughly as possible but helps future researchers repeat the process.