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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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