A Library of Systemic Relations
Birger Sevaldson 2011
Diagram of different ways to graphically treating relations between two entities. Line fonts and weight are used to codyfy the relations. (Birger Sevaldson, 2013, first version 2001 in article here >>>>> )
In our work, we realised that we needed to focus more of our attention on the relations. A simple line or arrow or a plus or minus, such as what one would find in casual loop diagrams, is not sufficient. Therefore, I developed this list of possible types of relations. It is probably incomplete and needs development. Please, go to the Forum to comment on the list and add more relations.
The colours are suggestions for colour-coded arrows or lines in a diagram. In addition to these, it would be wise to use different fonts for lines and label relations with descriptions.
This is a document under construction.
This is meant as an educational document and an ongoing research document. It is not a scientific document. For it to be this, it would need substantial discussions and a literature review for each point, something which is planned for later. Therefore, many of the sources and links might currently be off target and secondary and should be treated with care.
The library suggests colour coding and tagging with abbreviations for marking the relations.
Presentation from RSD5
Revision: 27th May 2018
December 2015: Changed the title from TYPES to LIBRARY of Systemic Relations, to emphasize that this is not meant to be a typology.
28th January 2013
24th January 2013
26th October 2012
16th August 2011
An example of a relation-oriented map as opposed to an object-oriented map. The relations are described according to the library at that stage of development (Young et al. 2013). Click the map to see a larger version, and use ctrl + and - to zoom in and out.
1. RELATIONS IN SYSTEMS THAT ARE DEPICTED WITH NODES AND CONNECTORS (typically objects connected with lines or arrows)
Network Theory >>>>>
Graph Theory >>>>>
1.1 STRUCTURAL RELATIONS, HIERARCHICAL SUPRA- AND SUBSYSTEMS (GREENS) (SR)
More on hierarchies here: >>>>>
1.1.1 Structural relations (Functional relations)(SRFR)
Example: There is no causal relationship between the wheels and the frames of a bicycle in the sense that the frame becomes smaller if the wheels grow larger. They are assembled in a structure where what they generate together creates a surplus output. The whole is more than the sum of the parts.
Example: Think of the relation in the air traffic system between the planes and the control system. The number of planes does not automatically decrease if the control system is reduced. This only happens through institutional regulations.
More on structural relations here: >>>>>
1.1.2. Macro-systemic relations (SRMA)
Example: Bikes and cars are related because they are sharing the same macro-system: the roads. (They are related in additional ways than this.)
1.1.3. Micro-systemic relations (SRMI)
Example: The rubber in the tires of cars and bikes comes from the same producer.
1.1.4 Horizontal structural relations (SRHO)
1.1.5. Vertical structural relations (SRVE)
1.2 SEMANTIC (Semiotic), THEMATIC, ASSOCIATIVE AND REPRESENTATIONAL RELATIONS (BLUE) (SA)
1.2.1. Semantic relations (SASR)
Semantic relations are entities connected through a sentence where one word forms the relation.
Example: Fish — lives in — Water. Fish and water are the entities while lives in is the relation connector.
Cow — is a — mammal
See more here >>>>>
1.2.2. Categorical relations (SACR)
Note: Categorisation has its own problems, especially when it comes to borderline cases and items that fit into multiple categories. See also thematic relations because the term is used in linguistics.
Example: The relation between universal design and ergonomics.
1.2.3. Associative relations (SAAR)
EuroVoc definition: The associative relationship is a relationship between two concepts that do not belong to the same hierarchical structure although they have semantic or contextual similarities.
Example: If two people are very similar to each other in their apperances, there is an associative relation.
For semiotic definitions on associative relations, see Ferdinand Saussure
1.2.3. Representational relations (SARR)
Example: The relation between a map and landscape.
1.3. SOCIAL RELATIONS (Yellows) (SO)
See also, Social Network Analyses >>>>>
Read about social relations here >>>>>>
1.3.1. Structural social relations (SOSR)
Note: There are always multiple relations between, for example, the members of a family; some are given while others are optional. The structural (biological) relation between family members is given (constant) while the social relation is optional or conditioned. One can choose to have a social relation with a relative. But it is not possible to have a social relation with your ancient foremothers.
1.3.2. Institutional social relations (SOIR)
1.3.3. Actions (SASR)
Example: Sharing political interests
1.3.4. Emotional relations (SAER)
1.4. HARD RELATIONS, CAUSAL RELATIONS, FLOWS, ETC. (REDS) (HR)
1.4.1 Causal relations (HRCR)
Example: If the heat is turned on, the kettle starts to boil.
Read more about causality here: >>>>>>
1.4.2. Qualitative causal relation (HRQR)
Example: The relation between architectural space and the micro-climate.
1.4.3. Relational Tools (HRRT)
Tools are typically modifying and influencing the relations, not the entities directly.
Example: AR used to increase a cultural understanding of biological systems.
1.4.4. Flows in human systems (HRFH)
Examples related to human society: Material flows, energy flows, information flows, knowledge, economic flows and stock markets
1.4.5. Flows in natural systems (HRFN)
Examples related to natural phenomena: water, air, magma, cosmic particle flows, etc.
1.4.6. Variables, stocks and flows (HRSF)
Example: A classic example is a bath tub: if the inflow of water is more than the flow out of the drain, the bathtub will fill up too fast and flood. If the flow out of the tub is larger, the tub will eventually be empty.
1.4.7. Negative relations (HRNR)
Example: The fox and rabbit example (tends to be a self-stabilising system)
1.4.8. Positive relations (HRPR)
Example: The a company showing increased profits on the stock market leads to an increase in the number of traders.
1.4.9. Feedback loops (HRFloop)
The effect of a chain of causal relations between variables that returns to the ‘starting node’.
Positive feedback loop (HR+Floop)
The sum of the relations is positive, so the system is unbalanced.
Example: (I find these very hard to get right because it is difficult to interpret, and it all depends on the variables one makes up.) Hostile negotiations accelerating into war
Negative feedback loop (HR-Floop)
The sum of the relations is negative, and the system is balanced.
Example: The fox and rabbit populations regulate each other.
2. SYSTEMIC RELATIONS THAT RESIST THE MODEL OF NODES AND CONNECTORS
Not all systemic relations can be abstracted to nodes with connections. They must be diagrammed with spatial maps, intensity maps or along timelines.
In many cases, we should challenge the predominant systems model of entities and relations. In many cases, it is more useful to use a model of continuum. When mapping out the myriad of relations, they will generate a weaving that is so dense that it generates a sense of a field more than an overview of a large amount of relations.
Examples are schools of fish or flocks of starlings, the phenomena called hive minds, collective intelligence or continuums as in oceans and weather systems.
2.1. Spatial proximity (SP)
Elements sharing the same space within an operational proximity for the agent (e.g., the user)
Examples: The relation between a chair and table. Of course, there is also a thematic relationship because they both are furniture and also may have a historic relationship because both could belong to the same style. There is also a functional and structural relationship. (Who said this is simple?)
Different use of proximity-based relations here >>>>>
2.2. Temporal proximity (TP)
Elements share a temporal proximity in relation to an agent (e.g., the user).
Example: Traffic regulation systems that are timed according to rush hours, which of course are caused by the working hours, which again are influenced by the planetary system (day length).
2.3. Spatial distribution (SD)
Intensity fields, variations and differentiation of the distribution of similar elements in space
Example: Temperature across a room with a stove in one corner
2.4. Temporal distribution (TD)
2.4.1. The distribution of elements over time
Example: The distribution of intensities in a music composition
2.4.2 Timing, rhythms and repetitions (TRR)
The same elements are appearing in a recognisable pattern.
Example: The repetitions in a music composition