Dataliterature

Dataliterature is a contemporary literary and artistic movement that explores the intersection of data, computation, and literary expression. It encompasses a range of practices where data, algorithms, and digital technologies are not merely tools for creation but are integral to the conceptual and aesthetic fabric of the work itself. Creators of dataliterature often engage with large datasets, statistical analysis, and programmatic generation to produce texts, narratives, and experiences that reflect or critique our increasingly data-driven world.

The movement can be seen as a response to the ubiquity of data in modern society and a way to understand and articulate complex informational phenomena. Dataliterature often blurs the lines between author and reader, programmer and poet, and traditional literary forms and computational processes. Works may take the form of interactive narratives, generative poetry, data visualizations with narrative elements, or experimental fiction that uses data structures as its underlying framework. The thematic concerns frequently revolve around issues of surveillance, privacy, algorithmic bias, information overload, and the human relationship with technology.

While not a strictly defined genre, dataliterature shares common ground with fields such as digital literature, computational art, and speculative fiction. Its practitioners often draw inspiration from scientific methodologies, critical theory, and avant-garde literary traditions. The intent is frequently to make visible the invisible forces of data that shape our lives, offering new perspectives and critical engagement with the digital age.