https://github.com/biocomputingup/idpregistry-kg
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: BioComputingUP
- Language: Shell
- Default Branch: master
- Size: 26 MB
Statistics
- Stars: 0
- Watchers: 5
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Instantiate the IDP Registry backend
Prerequisites
OR
Create a new context for the remote deployment
bash
docker context create ermes --description "ermes" --docker "host=ssh://<user>@ermes"
Set the new context as default
bash
docker context use ermes
Volumes
We now need to create two separate volumes for the two different triplestores. The volumes will be used to store the data of the triplestores. The volumes will be created on the remote machine and will be mounted on the containers on startup.
GraphDB volume:
bash
docker volume create -d local kg-graphdb
Virtuoso volume:
bash
docker volume create -d local kg-virtuoso
Use docker-compose to start the containers
This should download the two remote images (graphdb and virtuoso) and start the containers on the remote machine.
Configuration options can be passed to the containers from the docker-compose.yml file.
bash
docker compose -f docker-compose-kg.yml -p idp-kg up -d
Show logs
bash
docker logs -f kg-graphdb # For a single container
docker compose logs -f docker-compose-kg.yml logs -f # For all containers
Import pre-saved data into the volumes
If you want to import the pre-saved data into the created volumes, you can use the following commands:
bash
./docker-volume-snapshot.sh restore /projects/volumes_dump/GraphDB.tar.gz kg-graphdb
bash
./docker-volume-snapshot.sh restore /projects/volumes_dump/Virtuoso.tar.gz kg-virtuoso
Import to a remote volume without copying the file to the remote machine
bash
pv <dump>.tar.gz | docker run --rm -v <volume name>:/destination -i busybox tar xzf - -C /destination
Export from a remote volume without copying the file to the local machine
bash
docker run --rm -v <volume name>:/dest -i busybox tar -czvf - -C /dest . > <dump>.tar.gz
Import triples into the triplestores
GraphDB
- Open the GraphDB Workbench at http://localhost:7201
- Create a new repository, just set the name, the rest leave it as default
- Open the repository and go to the
Importtab - Import the triples from the file
./data/*.ttl - For each of the
ttlfile, click import and select target graphsNamed graphs - Set the name of the graph to
https://idpcentral.org/registry/<name of resource> - The name of the resource can be one of
ped,mobidbordisprot - Click
Import - Now if you go to the
Explore/Graphs overviewyou should see the imported graphs
Virtuoso
- Open the Virtuoso interface at http://localhost:8890
- Click on
Conductor - Login with the default credentials
dba/dba(password can be changed in the docker-compose.yml file) - Go to
Linked Data->Quad Store Upload - Upload the file
./data/*.ttl - For each of the
ttlfile, set theNamed Graph IRItohttps://idpcentral.org/registry/<name of resource> - Click
Upload - Now if you go to the
Linked Data->Graphs->Graphsyou should see the imported graphs
Export volume data as a tar.gz file
bash
./docker-volume-snapshot.sh create kg-graphdb GraphDB.tar.gz
bash
./docker-volume-snapshot.sh create kg-virtuoso Virtuoso.tar.gz
Owner
- Name: BioComputing Group, University of Padova
- Login: BioComputingUP
- Kind: organization
- Email: biocomp@bio.unipd.it
- Location: Italy
- Website: https://biocomputingup.it/
- Repositories: 31
- Profile: https://github.com/BioComputingUP
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