Our methodologies

UMARNA approaches each investigation through eight recurring criteria:

1. 1attention to evidence and evidentiary status
2. 2distinct registers of knowledge
3. 3long-duration observation
4. 4convergence across independent lines of information
5. 5awareness of the observer and the conditions of observation
6. 6a clear distinction between evidence and interpretation
7. 7curiosity towards origins and the assumptions beneath established paradigms
8. 8the living system as teacher

Imagination Knowledge Ancient Future Subtle Dense Micro Macro

Polarity, principles, disciplines

A second layer running through our work is the mechanics of opposites. Working through polarity, complementarity and degrees of difference allows us to weigh positions, reconnect what has been separated and expand perception across time, space and scale. And a third layer is guided by eight principles, shown below, that shape how the work is developed and carried forward. Our research may be multidisciplinary, interdisciplinary or transdisciplinary: bringing disciplines alongside one another, allowing their methods and models to interact, or creating something new when established boundaries no longer contain the question

• The criteria in practice

  The criteria provide a disciplined way of approaching complexity. UMARNA keeps four states distinct throughout the work: what has been observed, what has been documented, what has been inferred and what remains hypothetical (1). Different registers may contribute to the same investigation — scientific measurement, archaeological and historical records, ethnographic observation, oral transmission, embodied practice and long-duration cultural knowledge — while retaining the conditions through which each was formed, transmitted and validated (2, 3). When independent lines of information converge, the correspondence becomes a reason to investigate further, not a conclusion in itself (4).

• In both directions

  This allows ancestral knowledge and contemporary science to illuminate one another in both directions. A longstanding observation may become measurable through a contemporary instrument; contemporary research may clarify part of the mechanism behind an older practice; a comparison may reveal a recurring structure; or closer examination may show that an apparent correspondence does not hold. Continuity provides a historical record; convergence opens a line of investigation; explanation has to be earned.

• The practical repertoire

  The practical repertoire follows the same logic: archival research can establish provenance; archaeological survey can document sites and material culture; photogrammetry, LiDAR, geophysical and acoustic sensing can reveal spatial and physical relationships; physiological or behavioural measurement can test responses; computational modelling and simulation can explore systems that cannot be observed directly; reconstruction and reverse engineering can make historical artefacts or techniques available for renewed examination. Measurements are read against one another, with documentation kept distinct from interpretation.

• The observer

  Observation also includes the observer. Training, attention, cultural position, terminology, expectation and instrumentation influence what becomes visible (5). Reflexivity therefore belongs to rigour. Imagination can formulate propositions and construct provisional models; beauty, pattern and coherence can signal something worth examining, but they cannot establish truth on their own. Curiosity returns to origins, to observations beneath established terminology and to the assumptions that hold paradigms in place (6, 7).

• The living system as teacher

  Nature provides another source of instruction. Biological systems carry deep histories of organisation, differentiation, communication, adaptation, repair and coexistence, allowing us to study how complexity can remain viable through change (8). These processes may inform new technological, cultural or social approaches where their principles can be meaningfully translated or tested.

• Machine intelligence

  Computation, AI, robotics and emerging machine intelligence extend pattern recognition, comparison, mapping, modelling and simulation. Their increasing capacity also changes the conditions under which knowledge is produced, bringing questions of judgement, responsibility and governance into the work alongside technical development. The framework remains stable while the investigation remains capable of changing direction.