The content of this forum - not just this thread - is golden. It's applied epistemology.
I see Sasha's point. The best context for a link is in the originating end of the link. However, if the link itself had properties, maybe a link's context could be visible from either source or destination.
The best example I could think of for a productive use of backlinks is investigation.
The doctor sees your symptoms. Backlinking, so to speak, from your symptoms leads to syndromes worthy of consideration. What he has to work with are symptoms. What he wants to find are possible causes.
Of course, restructuring would make symptoms a workable point of entry without backlinking.
Humbly submitted, of course. I am a beginner at all this.
I see Sasha's point. The best context for a link is in the originating end of the link. However, if the link itself had properties, maybe a link's context could be visible from either source or destination.
Right, @msteffens was quick to point that out in the third comment above. When you add link types (or even just note types that imply link types) and clear visualization of them in your software, it changes the game and can give automated backlinks (or any automated visualization of relationships) epistemic relevance.
An example (perhaps not the best example, but simple) is the Scaling Synthesis collaborative "hypertext notebook" website of Rob Haisfield, Joel Chan, and Brendan Langen. It is just a set of Markdown note files that are published to the web using the Quartz static site generator. All the links are color-coded by the note type of the target note, and every page has a list of automatic backlinks similarly color-coded. Their system could be improved, but it shows how much more information one can get from both inline links and automatic backlinks when there is a visible note schema.
The best example I could think of for a productive use of backlinks is investigation.
The doctor sees your symptoms. Backlinking, so to speak, from your symptoms leads to syndromes worthy of consideration. What he has to work with are symptoms. What he wants to find are possible causes.
Of course, restructuring would make symptoms a workable point of entry without backlinking.
The kind of problems that you describe here as analogous to backlinking is what Mario Bunge since the 1960s has called inverse problems: "the hardest problems are likely to be inverse, in that they go from effect to cause, from goal to means, or from conclusion to premises—as in diagnosing disease from symptoms, looking for a westward passage from Europe to Asia, and designing public policies to face social issues. In other words, forward thinking proceeds from premises to conclusions, whereas backward thinking goes the other way around, that is, in search for grounds."1
The analogy forward problem solving : inverse problem solving :: forward links : backlinks may indeed be a close analogy if one has a relevant schema of note types, e.g. premises/reasons and conclusions/positions, or causes and effects.
There are more rigorous relevant models in computational approaches to investigation, but I don't know much about them. I recently mentioned in a comment in another discussion the example of software for government intelligence analysis.
Comments
Here’s my view on the value of back links:
For me terms with back links are best for finding hidden connections.
Edmund Gröpl
100% organic thinking. Less than 5% AI-generated ideas.
The content of this forum - not just this thread - is golden. It's applied epistemology.
I see Sasha's point. The best context for a link is in the originating end of the link. However, if the link itself had properties, maybe a link's context could be visible from either source or destination.
The best example I could think of for a productive use of backlinks is investigation.
The doctor sees your symptoms. Backlinking, so to speak, from your symptoms leads to syndromes worthy of consideration. What he has to work with are symptoms. What he wants to find are possible causes.
Of course, restructuring would make symptoms a workable point of entry without backlinking.
Humbly submitted, of course. I am a beginner at all this.
@Amontillado said:
Right, @msteffens was quick to point that out in the third comment above. When you add link types (or even just note types that imply link types) and clear visualization of them in your software, it changes the game and can give automated backlinks (or any automated visualization of relationships) epistemic relevance.
An example (perhaps not the best example, but simple) is the Scaling Synthesis collaborative "hypertext notebook" website of Rob Haisfield, Joel Chan, and Brendan Langen. It is just a set of Markdown note files that are published to the web using the Quartz static site generator. All the links are color-coded by the note type of the target note, and every page has a list of automatic backlinks similarly color-coded. Their system could be improved, but it shows how much more information one can get from both inline links and automatic backlinks when there is a visible note schema.
The kind of problems that you describe here as analogous to backlinking is what Mario Bunge since the 1960s has called inverse problems: "the hardest problems are likely to be inverse, in that they go from effect to cause, from goal to means, or from conclusion to premises—as in diagnosing disease from symptoms, looking for a westward passage from Europe to Asia, and designing public policies to face social issues. In other words, forward thinking proceeds from premises to conclusions, whereas backward thinking goes the other way around, that is, in search for grounds."1
The analogy forward problem solving : inverse problem solving :: forward links : backlinks may indeed be a close analogy if one has a relevant schema of note types, e.g. premises/reasons and conclusions/positions, or causes and effects.
There are more rigorous relevant models in computational approaches to investigation, but I don't know much about them. I recently mentioned in a comment in another discussion the example of software for government intelligence analysis.
Mario Bunge (2019). "Inverse problems". Foundations of Science, 24(3), 483–525. https://doi.org/10.1007/s10699-018-09577-1 ;↩︎