KGAP - Knowledge Graph Analysis Platform - will allow you to investigate data provided in RDF format. In this case, we can read in the turtle files from the observatory logsheets, or the MetaGOflow outputs, and investigate them. At present you have to copy the ttl files to the data/ folder (following the examples already there); to be added is a config file that will do this for you.
Steps:
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retrieve the source code from github
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to build the services simply run
.$ cp dotenv-example .env # make sure you have an .env file
.$ cd docker && docker-compose build # use docker to build the services - to start up the services simply run
.$ cd docker && docker-compose up # use docker to run the services - open the jupyter notebook
Either go to http://localhost:8896
or try:
.$ xdg-open $(docker/jupyter_url.sh) # this gets the url for the service and opens a browser to it- open the graphdb browser ui
Either go to http://localhost:7206
or try:
.$ xdg-open http://localhost:7200 # opens the web ui in a browser- run a test-ingest
This introduces forcefully at least the data/project.ttl into the triple store This should not be needed when the ingest runs automatically
.$ docker exec -it lwua_ingest /bin/bash # interactively gets you into the ingest env
root@f226b253fbd4:/lwua-py# python -m lwua.ingest # run the ingest