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SEMANTIC SPACETIME

The programs in this repository accompany a series of blog posts.
They are meant as pedagogical examples, not necessarily as production
quality reference implementations. The blog posts start here:

https://mark-burgess-oslo-mb.medium.com/universal-data-analytics-as-semantic-spacetime-dee7a76661c2

The examples assume that you have ArangoDB and golang installed
locally on your Linux based computer, as described in Part 2 of the
series.

For your own work, you may want to alter the programs. Here my
priority has been to show how to do most things, but also keep the
code as simple as possible. My choices are probably ad hoc, but I hope
there's enough here to guide you towards optimizing your own version
of this.

To keep the reasoning clear, I've simplfied error handling in many
cases. Use these to learn, but be aware that additional cases and
checks might be needed for stress testing applications.

To link the package to your golang installation, you can create a symbolic link

   git clone https://github.com/markburgess/SemanticSpaceTime

   ln -s ~/path/SemanticSpacetime/pkg/SST ~/go/src/SST


You are free to copy and use the code here as per the Apache 2 terms

        https://www.apache.org/licenses/LICENSE-2.0 

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