Relations
In Science Architect relations are elements that can be created only in system diagrams. Relation indicates how one node relates to another node, for example, how one Statement relates to another Statement. What makes system diagrams different from standard text is that single node can have many connections to other nodes. For example, a single Statement could have many different relations to other nodes in one diagram and the same statement could have even more relations in other diagram. Below you can find examples of different types of relations and how they connect different types of nodes.
Relations with the arrow on one end are called directed relations, and relations without the arrows, or with arrows on both ends are called undirected relations. The goal of directed relations is to show the reading direction to the reader. In directed relation the end without arrow is called Source and the end with arrow is called Target. Node to which Source end is connected is called Source node. Node to which Target end is connected is called Target node. The saying “A targets B” means that A component was connected with the relation Source end and B component was connected with the relation Target end.
Causation Group
Positive, Negative, Affect and Affectless relations belongs to the Causation Group of relations, which indicate that Source node has or has not an effect on the Target node.
1. Positive
Positive relation most often is used to target Problem and Goal nodes by Source nodes.
Both, primitive and non-primitive nodes can target Problem component. In Case of primitives, for example, Process “Alcohol consumption” could target “Breast Cancer” Problem with Positive relation. This means that “Alcohol consumption” contributes or causes “Breast Cancer” problem. Situation is different with non-primitive component (e.g. Statement) targeting “Lung Cancer” Problem. In this scenario Statement node should state that something solves or contributes to the solution of “Lung Cancer” problem. This Statement node should target “Lung Cancer” node.
Notice that in non-primitive case, relation to the problem adds no additional information, because Source node already states that information. For example, statement “A causes B problem” has all the needed information. It might seem that it is redundant to show the same information by connecting statement “A causes B problem” to the B problem node. However, this relation serves as very important visual clue for the reader, where reader can very quickly choose what to read and what to exclude.
On the other hand, primitive node that targets problem component does not duplicate information and serves as real source of information.
Positive relation could also target Goal. However Goal targeting is different compared to Problem targeting. In case of the Problem, positive relation indicates that Source node has information that indicates the contribution/cause of the Problem. In the case of Goal, positive relation indicates that the Source node helps to achieve the Goal.
2. Negative
Negative relation is opposite to the Positive relation. It provide information about solutions/mitigations to the problem, or information which blocks/hinders the achievement of the goal.
3. Affect
Affect relation should be used when it is known that Source node has information that indicates the effect on the Target node, but it is not clear if it is Positive or Negative. For example, “Diet habits” could have Positive or negative effect on “Body weight”. Both Positive and Negative relations are Affect relations, but they provide more specific information and if this information is known, one of them should be used instead.
4. Affectless
Affectless relation indicates that Source node has information indicating that some thing has no effect on the Target node. It might seem pointless to indicate that there is no effect, however in certain scenarios it might be useful. For example, it might be believed A has effect on B, but newest research rejected this statement. In this scenario we can use Affectless relation to indicate that A has no effect on B.
5. Direction
In standard linear text writer dictates the path of thought to the reader. In order to understand information of standard text, reader is forced to follow this path. In Science Architect you can achieve this by creating nodes in diagram and connecting them with the Direction relation. The main difference from standard linear text is that nodes can have many connections to other nodes. Therefore, with systems modeling writer no longer dictates the path of thought to the reader, instead reader is capable to choose what to read next. See section Analysis of Systems for more information.
Additional Information Group
Additional, Condition, Because and Example relations belongs to the Additional Information Group of relations, which indicate that Target node provide in various forms provides additional information to the Source node.
6. Additional
In Science Architect it is possible to provide additional information to the main statement by using Additional relation. The relation arrow indicates Target node that has additional information and the Source node is the main statement.
Which node is the main node depends on the context. Let say that we have two nodes A and B. In one context A can be the main node (Source node), therefore the arrow will point towards B node: A —>> B. In other context B node could be the main node, in which case the arrow will point towards the A node: B —>> A. It is up to the creator of the diagram to decide, which node is the main node (Source node) and which one provides additional information (Target node).
7. Condition
Condition relation is an Additional relation, however it is more specific. In this case we a have the main node (Source node) and node that provides additional information – Target node. However in this case Target node must indicate the condition when information in the Source node is true.
8. Because
Because relation is an Additional relation, however it is more specific, where information in the Target node must indicate why the statement of main node is true.
9. Example
With Example relation Target node indicates concrete examples of the thing stated in Source node.
10. Similarity
11. Contrast
12. Contradiction
13. Inheritance
14. Outcome
Correlation Group
Correlation, Positive Correlation and Negative Correlation relations belongs to the Correlation Group of relations, which indicate that Source node has correlation to the Target node, but it does not show the causation. If causation is was proven, user should use relations from Causation group.
Correlation, Positive Correlation and Negative Correlation relations belongs to the Correlation Group of relations, which indicate that Source node has correlation to the Target node, but it does not show the causation. If causation is was proven, user should use relations from Causation group.
15. Positive Correlation
16. Raise
Three nodes can be raised – targeted by the Raise relation: Question, Hypothesis and Goal.
17. Answer
18. Part
19. Composition
20. Aggregation
21. Solution
22. Alternative
