Periodic Reporting for period 1 - COSE (Coded Secrets: Artistic Interventions Hidden in the Digital Fabric)
Berichtszeitraum: 2022-09-01 bis 2025-02-28
A narrowly defined, yet heterogeneous corpus – online graffiti – was studied to analyse and reveal their embeddedness in the specific online platforms. COSE is interested in how the online works are locally or regionally entangled with their ecosystem. The team explored topics like artistic browser extensions as graffiti, hacking as artistic interventions, works that bridge online and offline graffiti, and how digital graffiti on platforms like VR Chat relates to broader ecosystems of cultural production. This further solidified the project's contributions to understanding affordances and hidden behaviours in digital spaces.
On the methodological and technical side, another major achievement is the creation of COSE’s software tool Net Art Detector (NAD). This tool links the algorithmic behaviour of digital works with their phenomenological aspects, offering a new method for understanding how these artworks function both on a technical and experiential level. By visually mapping interaction flows, identifying hidden elements, and highlighting deprecated code, Net Art Detector equips researchers with the ability to study the complexities of net-based art in greater detail than ever before. Moreover, it helps track how their behaviour might change over time due to software updates or browser changes. This makes it a vital resource for qualitatively analysing the progression of the decay and for eventually preserving the integrity of these works.
Having analysed software visualisation software (mainly developed by software engineers) for their usefulness in studying relatively small programs (artworks), COSE determined that they were hardly suitable to answer the questions posed in the art world or the humanities. Helping ourselves and others, COSE developed the tool Net Art Detector that visually maps the elements of the code and their interactivity. It enables researchers across disciplines to gain a deeper understanding of digital artefacts, especially when analysing generative or interactive works. The tool's flexible interface supports further knowledge transfer by making complex digital phenomena more accessible to scholars from diverse academic backgrounds. The Net Art Detector tool also helps researchers understand the deeper structures of net-based art, which often involves complex combinations of CSS, JavaScript, and other code layers. This innovation is crucial for documenting the fragility of these digital artefacts. This tool is of potential interest for a broad range of disciplines dealing with the Internet.