DBpedia Development Wiki devilopment bible

This page was included from https://github.com/dbpedia/dbp-same-thing-service.

NOTE: Service is under development, some things might change, give feedback here: https://github.com/dbpedia/dbp-same-thing-service/issues

DBpedia Same Thing Service

Microservice that looks up global and local IRIs based on the most recent DBpedia ID Management release.

Query the DBpedia Same Thing Service with the IRI of a Wikidata or DBpedia entity (more will follow) and it will return the current DBpedia global IRI for the queried IRI and all known “local” IRIs which are considered to be the same thing. The “local” IRIs for a global ID are the members of the cluster represented/identified by the global ID. The members of a cluster are assigned by the DBpedia ID Management Cluster algorithm based on transitive closure of owl:sameAs links.

For each local IRI, a corresponding DBpedia singleton ID has been minted. This identifier is also used to represent the cluster in the microservice output. This service can be queried with either global, local, or singleton IRIs, and will return the same representation of a cluster in every case.


You can query the experimental service deployed within the DBpedia Association infrastructure


or setup your local instance based on the latest DBpedia ID Management release. The service is based on simple HTTP requests, and accepts the uri parameter, which may be any global or local IRI.

curl "http://localhost:8027/lookup/?meta=off&uri=http://www.wikidata.org/entity/Q8087"

  "global": "https://global.dbpedia.org/id/4y9Et",
  "locals": [
  "cluster": [

Percent-encoding of the uri parameter is optional. If this example does not work when running the service locally, after it has fully loaded, check which port is specified in docker-compose.yml.

Local Deployment

The microservice is shipped as a docker compose setup.


Running from a pre-built docker image

  • Download the compose file: wget https://raw.githubusercontent.com/dbpedia/dbp-same-thing-service/master/docker-compose.yml
  • Run: docker-compose up

This will download the latest image and runs two containers: the loader and the webserver (http). The port on which the webserver listens is configurable in the compose file.

When running multiple containers in this way, the loading progress can unfortunately not be displayed. To monitor the progress of the (initial) Global ID snapshot downloading and ingestion, instead run the following:

  • docker-compose run loader

After the loader is finished, both containers may be run with docker-compose up.

Bulk Loading

The loader downloads the latest Global ID release from downloads.dbpedia.org and proceeds to load any source files that haven’t been loaded yet into the database. This might take several hours to complete. After all data is loaded, a backup is made and the loader stops running.

On subsequent restarts of the loader container (e.g. with docker-compose run loader or docker-compose up) the loader will check if a new snapshot release is available on the download server, remove old cached downloads, and load the new ID release into a fresh database.

Update, Maintenance, & Zero Downtime Features

Initial loading

To start running, the webserver (http container) waits for the database to initialize. Only on the first run, it will have to wait until the source file has been downloaded, and will start listening for requests once the (empty) database has been created. While files are being loaded, the service will respond to requests, but will return 404 for any URI that hasn’t been loaded yet. Output may also be incomplete until the loader is done.

Update to a new release

To check if a new dataset is available, use docker-compose run loader or simply rerun docker-compose up. The loader will discover the new release, download it, and start to create a new database version. The running webserver however, will not be affected during the download and update process. It will keep serving requests from the already existing fully-loaded database, and will not switch to the newer database while it is running. The next time the http container is booted it will use the most recent database (which is typically the one that was latest to download).

Database versioning (Backup) and Rollback

All database versions will stay in the dbdata volume until they are manually removed. This allows to switch back to an older database version at any time (e.g. in case the loading of the latest release was interrupted and led to an inconsistent state. In order to do so:

  • get the mountpoint of the dbdata volume: docker volume inspect dbp-same-thing-service_dbdata
  • cd into the mountpoint directory
  • touch the folder of the database version you would like to ‘restore’
  • restart the http container

After restarting the http container, it will use the database folder you touched (i.e. the database folder with the most recent timestamp). In order to reduce storage consumption, the database versions should be cleaned occasionally.

Development Setup

In case you would like to modify the behavior of your local instance (by editing python files) or to contribute enhancements to this project, you can build your own docker image. In order to do so:

  • Clone or fork this repository
  • docker-compose -f docker-compose.yml -f docker-compose.dev.yml up
  • any changes to the webapp code will trigger a live reload

We use pipenv for package management. Set up a local python environment by running pipenv install from the project root. Introduce new dependencies with pipenv install <package_name> and ensure that the latest Pipfile.lock (generated with pipenv lock) is included in the same commit as an updated Pipfile.

After making any changes other than to python source files, rebuild the image with docker-compose -f docker-compose.yml -f docker-compose.dev.yml build. The compose file automatically builds the image if none exists, but will not rebuild after changes when using docker-compose up.


If the pre-compiled version of the embedded RocksDB does not work on your CPU architecture (e.g. virtual machine, or older AMD), this is likely due to an optimization that depends on an instruction set which is not available on your CPU. To build your own image that runs with production settings, follow these steps:

  • Clone this repository
  • Run docker-compose up

This works because the docker-compose.override.yml file is automatically applied, which specifies a local image instead of the one from Docker Hub. To rebuild the image, e.g. after updating with git pull, run docker-compose build.


This work may be used, modified, and distributed under the terms of the Apache 2.0 License. See LICENSE for the terms and conditions.


The microservice is developed and maintained by Alex Olieman (@aolieman). His work has been supported by @stamkracht / Qollap and the University of Amsterdam (under a grant from The Netherlands Organisation for Scientific Research).