Anatomy of System Notations: A comprehensive inventory of graphical devices
Bibliographic record
Abstract
System graphical notations are standardised shorthands for diagramming systems. Most take the form of node-and-link diagrams (hypergraphs), stacks, and spatial-map encodings. These graphical notations remain in widespread use but have not evolved significantly over the last thirty years. That plateauing is conspicuous given the many advancements in other forms of system visualisation and systems thinking in general. The Pattern Atlas of System Vulnerabilities was presented at RSD11. That work included a poster itemising 30 forms of problematic system entanglement. The new exhibit presents subsequent work that attempts to visually disentangle complex interactions within and between systems. A poster itemises and illustrates the various graphical devices used in system graphical notations. In a sense, this would be an anatomy chart of system notations in all their diversity. The poster identifies which forms work better, which are dysfunctional, and which are innovations that have been under-used (or otherwise neglected). Those insights provide a stepping stone to the creation of updated notations, ideally, ones better suited to our era in which multi-media maps are overtaking static ones. Those insights would also suggest good practices for those who integrate system notations into other forms of graphics, such as infographics, gigamaps, and synthesis maps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".