Mapping Contemporary Digital Musicking: A PACMMAN-Based Analysis of Patterns and Practices

Introduction

This chapter delivers an Ontology built from a comprehensive qualitative analysis of the DigiScore corpus through the lens of the PACMMAN framework (see chapter 3), uncovering the structural and experiential hallmarks of contemporary digital musicking. By coding paired “Intention” and “Reception” fields from over sixty case studies (including VR/AR installations, EEG-driven scores, robotic co-performers, latency-calibrated ensembles, tactile transducers and algorithmic improvisation scaffolds) the study identified seven high-level trends:

1. First, hybrid graphic-digital-traditional scoring dominated this corpus, weaving animated visuals, colour-coded symbols and familiar notation into a unified interface.
2. Second, agency was deliberately ambiguous: scores acted as semi-autonomous partners whose liveness invited performers to negotiate control rather than execute directives.
3. Third, structured improvisation scaffolds provided a safety net that stabilised ensemble cohesion while preserving personal creativity.
4. Fourth, pre-recorded material functioned as a structural backbone that anchored interaction and grounded the unfolding narrative.
5. Fifth, the proliferation of interaction modalities expands expressive possibilities but introduced new technical demands and a risk of cognitive overload.
6. Sixth, flow and immersion consistently emerge as central performer experiences, with breakdowns traced to synchronization lapses, temporal disorientation, fragile hardware and opaque algorithmic decision-making.
7. Outlier works (such as brain-computer-interface-centric pieces, robotic arm collaborators and network-latency-exploiting scores) illustrate fertile research frontiers where technical constraints are re-imagined as compositional resources.

These findings refine the theoretical scaffolding introduced in chapter 1, where digital musicking positions making, musicianship and meaning as inter-dependent subsystems, with the PACMMAN framework suppling the empirical granularity that operationalises those subsystems across seven dimensions (Physical, Agents, Code, Meta, Music, Acoustic, Networks). Likewise, this analysis extends the digital score signatures and seven defining features articulated in chapter 2, demonstrating how purpose, function and relational agency materialise in practice and how the “Taking-In - Taken-Into” model manifests in real-world performances.

The methodology leading up to this analysis is introduced in chapter 3 and has been previously released as academic papers elsewhere . And a full list of the case studies is presented at the end of this chapter. As an indicator of geographic distribution the dataset included works such as Nautilus (UK), My Mother is a Fish (Switzerland/ Germany), Villanelles de Voyelles (Canada), Machine à sons (France), The Legionnaires (Belgium), Digital Syzygies (UK), Shadow Aria (Australia), Wormwood (Australia), Kaleidoscope (US), GuitaRPG (US), Tendons for Transformation (US), Path/Fields (US), Dynamic Landscape (UK), Speechless (Australia/ Germany), Fold (US/ Belgium), Jess+ (UK), Returns & Simulacra (Australia/ UK/ Canada/ Ukraine), Queer Temporal (UK/ Canada/ Ukraine/ Norway), Horizon (China), Netronomia (China/ US), JoyInst (Kenya) among others.

The chapter culminates with actionable recommendations for composers, technologists, educators and researchers, including suggestions such as embed clear temporal anchors, design legible multimodal cues, adopt graceful-degradation strategies, provide modality-specific rehearsals and document algorithmic pathways to foster trust and collaborative negotiation. In doing so, this analysis presents PACMMAN as an analytical taxonomy but also suggests how the findings can act as a pragmatic roadmap for designing resilient, immersive and ethically aware digital music ecosystems, thereby bringing the abstract concepts of the previous chapters into more concrete practice.

Dimension-by-Dimension Analysis

In this section I systematically examine each of the dimensions that constitute the PACMMAN framework. For every dimension I have: • defined its analytical focus • discussed key patterns and themes that emerged from the corpus analysis; the intention is to generalise usable insights from the findings rather than analyse the merits and failures of specific case studies (although some exceptional examples have been directly referenced)

Although the framework was originally devised to analyse a corpus of digital scores, I adopt the broader term digital system to encompass all artefacts that mediate musicking in computational environments. A digital system therefore includes not only digital scores but also digital musical instruments, improvisation systems, autonomous agents and intelligent synthetic musicians. All these entities are appropriate subjects for the kind of multimodal, interaction-oriented analysis that PACMMAN supports.

This analysis reads like a large data dump; which it is, and I make no apologies for it. The DigiScore project generated a massive amount of deeply relevant experiences from professional musicians who were given time and support to immerse into their sound worlds and creative journeys. The corpus dataset captured an equally massive about of data (text alone amounting to over 1 million words) focussed on the theoretical frameworks presented in chapters 1, 2 and 3. As such there is a lot to tell, but I have tried to condense it down into manageable and usefully applicable insights. Furthermore, given the large amount of raw data, I employed friendly large-language models to sift and identify patterns that were tacitly embedded in the data (after all, it is what they are trained to do – and are very good at it). Much of this was rejected – by me – but at times, they produced golden nuggets that I had missed. I can confirm that what is written below is the result of my research, by me; and that the insights presented are from me. I merely needed a hand synthesising the raw data into something manageable, from which my theories and analyses emerged.

Conclusion

The PACMMAN analysis of the DigiScore corpus demonstrates that contemporary digital musicking is evolving from a model of top-down prescription to one of distributed influence, where performers, algorithms, visual media and the performance space co-author the musical outcome. Across the thirty-plus case studies, the recurrent motif of “influence over control” surfaces: composers embed probabilistic or habit-based engines that react to gestures, brain-wave metrics or network latency, thereby inviting performers to negotiate rather than merely execute. This shift aligns with ecological and enactive theories of cognition, positioning the score as a responsive partner rather than a static artifact.

A second, equally decisive insight is the primacy of legibility. Performers repeatedly cite the cognitive strain caused by dense multimodal cue streams, unsynchronised scrolling graphics, or opaque mapping logic. Effective designs therefore foreground clear temporal anchors (soft barlines, countdowns, visual scaffolds) and limit the semantic load of any single sense channel. When visual, tactile and auditory cues are orchestrated as complementary layers—each reinforcing the others without overwhelming the performer—the system sustains flow, reduces anxiety and preserves artistic agency.

Third, the outlier cases highlight fertile research trajectories. Brain-computer interfaces (Digital Syzygies), robotic co-performers (Jess+) and latency-calibrated network ensembles (Netronomia) push the boundaries of agency, embodiment and spatial perception. These works reveal that when technical constraints are deliberately re-framed as compositional material (e.g. embracing VR desynchronisation as “glitch aesthetic” or treating room reverberation as a narrative parameter) novel expressive vocabularies arise.

From these findings a set of concrete design recommendations emerges. Designers should:

1. embed explicit, low-latency temporal markers throughout the score to anchor ensemble timing
2. adopt colour-coded, size-coded visual grammars that map transparently onto sonic parameters
3. implement graceful degradation strategies such as fallback cues, redundancy across modalities and real-time monitoring dashboards, to mitigate technical fragility
4. provide rehearsals tailored to each technology, including latency calibration drills for networked participants and sensor-feedback conditioning for BCI-driven works
5. document algorithmic decision pathways (e.g. probability weights, threshold criteria) in performer-accessible formats to foster trust and collaborative negotiation.

Addressing the first research question posed in chapter 3 (Which PACMMAN dimensions most strongly predict performers’ sense of agency and immersion?) this chapter offers insights through the flow-and-immersion overview, which isolates the experiential cluster and in the detailed analyses of the Physical and Agents dimensions, and quoted reflections on “being in the flow” appear while agency correlates most closely with Physical, Agents and Code. The second research question (How do non-human actants reshape authorship and co-construct meaning versus a traditional performer-score dyad?) is explored in the ambiguous-agency & shared-control section and the system-transparency discussion, where musicians describe the score as an autonomous partner. Deeper insight comes from the Agents, Code, Meta and Networks subsections, each unpacking a class of non-human actant (interactive agents, algorithmic logic, cultural narratives, relational topology). The final synthesis links these analyses, arguing that authorship is now a distributed property shared among humans, sensors, AI and the acoustic environment.

Pedagogically, the PACMMAN framework offers a shared vocabulary for teaching multimodal musicking. Instructors can structure exercises that isolate individual dimensions (such as blind-folded tactile scoring or breath-controlled reverb) to train students in sensorimotor awareness before integrating full-stack systems.

Finally, future scholarship should extend the current analysis along three axes: (a) longitudinal ethnographic studies that follow ensembles across multiple performances to trace the evolution of networked agency; (b) systematic investigations of algorithmic explainability, probing how transparent visualisations of code state affect performer confidence and creative decision-making; and (c) inclusive design research that evaluates how diverse bodily and cognitive profiles interact with hybrid scores, ensuring that the emerging ecological model of digital musicking remains accessible.

Overall, the PACMMAN framework not only uncovers the structural and aesthetic DNA of today’s digital scores but also furnishes a pragmatic roadmap for advancing the field toward resilient, immersive and truly co-creative musical ecosystems and digital musicking.