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TrailMarks Value Proposition

This post was composed in TrailMarks. It was supposed to also showcase high resolution addressing. It will need a couple more days to complete. But the text without the linked context provides pointers to how interoperability between the knowledge graph (propositional knowledge) can interface with more discursive human level understanding using Hypothes.is. The headings indicate nodes and are a “left forward” of  the structure needed for high resolution addressing and recall. They should be visible only when the viewspec for it is activated. Shame I have to fake it till I make it still.

The problem

Summary

do summary

Too much content
Capable recommendation engines appear everywhere, on Medium, LinkedIn, Research Gate,  Discuss, Slack, Riot. The list is a long one. Not to mentions the all the notifications that enter one’s inboxes.
We are drowning in a deluge of well filtered relevant content.
Poor recall
We lack reliable ways of recalling things just when we wish to use them. Searching for things we encountered earlier, often fail, but are always a distraction.
Web annotations
Web annotation tools, such as hypothes.is, address this problem, but the more you use them, the harder it gets to find things. There must be a better way: Finding without searching. But how?
Losing control of contributed content
Even worse, sites usually provide their own ways of creating content. This undermines our sovereignty and ability to build upon our own content.
The solution
Summary
TrailMarks gives users a private place, where they can keep, remix, curate, and create content, and via deep
linking, facilitate perfect recall by creating a meaningful context for all content.
Contextualize all content
In this place everything is a “dot” that we can connect  so that all content  is always
in context,
Augmented authoring
The dots which are created by narrative trails are self-organized via bi directional links into
meaningful contexts, eventually connecting everything to everything else.
Create Mashups
Dropping links into a Trailmarks “linked text editor” triggers sensible default actions.
Handling Hypothes.is annotations
If you drop a
hypothes.is
link into the editor, it creates a dot linked to the dot you are editing, connecting your
annotations to relevant contexts.
Google Searches
If you drop a Google keyword search result page into a dot, it creates a dot which is connected to the existing dot. Google knows that collecting your search terms is a valuable way of mapping your interests. Trailmarks not only maps those interests, it automatically enriches the
context of the dots to which they are added, enhancing our quality of recall within our own personal knowledge repositories.
What’s in a bidirectional link

We know the keywords we care about. Use them to create them as dots. When you link from a dot you created to capture meaning, to a resource that link creates a context for the resource without your labeling or organizing. Vice versa, when looking at a dot with your own keywords baked into the title of dots, you find all relevant resources without searching anywhere else. It’s like in science fiction: “Travelling without moving.” except you do not need to take mind expanding drug to accomplish it. Finding without repeated searching on the web liberates the mind itself.

Key benefits
Summary
TrailMarks helps you to bring to mind what you have in mind, creating an emergent interest graph, that goes beyond propositions, which connects what you have written to that which you had been bombarded with recommendation engines, have already searched for and gathered as you surfed the net. The trails you blaze expand the frontiers of your Personal Knowledge. These trail will “never fade” and let you recall them along with the “scaffolding with which they were erected”.
HyperMap Personal Knowledge
A HyperMap of your explored territories not only improves your comprehension it also helps with your articulation.
Collective Extelligence
HyperMapped Narrative Trails can be shared and built upon.
TrailMarks can be hub for all your interests and at the same time it can be a portal operating autonomously on the edges for others to discover and build upon the knowledge you wish to share.
With minimal extra effort, through peer to peer collaboration and pooling of personal  knowledge through  community HyperKnowledge
Portals, using TrailMarks, in the near future you can contribute to the emergent “Collective Extelligence” of a “decentralised web”.
Conclusion

By augmenting our ability to understand and be understood, TrailMarks can facilitate intelligent, responsive, nay, responsible, conversations on “matters that matter”.

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