Virtuoso with latest DBpedia Dumps / missing data

Support Query DBpedia SPARQL
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@jfrey @klaus82 Jan is providing the recommended solution. Klaus has updated a local spotlight version and now he wants more information about found entities, such as Trump. This info is not in 2016, but it is in https://databus.dbpedia.org/dbpedia/collections/latest-core (2019-09).
The collection will update automatically, so re-deploying the DBpedia Docker brings you fresher data now and then.
@klaus82 we established latest-core for users to adapt:

  1. get a databus account and log in
  2. go to https://databus.dbpedia.org/dbpedia/collections/latest-core and click on Actions-> Copy Edit . This will create a collection in your space
  3. Add the Italian datasets you need.
  4. (Optional) remove some datasets, that you don’t need, so loading is faster
  5. Publish your collection and put the collection URL into https://github.com/dbpedia/Dockerized-DBpedia
  6. do your queries, either SPARQL or use the IP, e.g. 127.0.0.1:$port for linked data (might need some setup, so sparql is easier).
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Thanks @kurzum for your reply.

I noticed that the databus endpoint used to download data for spotlight, as you suggested to me in the post [1]:

My goal is: Given a text, analysed by spotlight, I need to understand what are the entity, recognised by spotlight, that are changed between the 2016 release and this last release, but could be traced with an entity of 2016. Eg: http://dbpedia.org/resource/Adobe_Systems and http://dbpedia.org/resource/Adobe_Inc.
To do this I query Virtuoso and try to match the entities, but If the dataset downloaded for spotlight and for virtuoso are different I could have match errors or mismatch.

Do you have any suggestions to achieve my goal?

[1] Consolidate Update Interval of DBpedia Spotlight

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I am suggesting, that you build this synchronization yourself.

  1. we are currently working on updating the pre-built tar.gz for spotlight on the bus. But you also know how to build it.
  2. Then you select matching versions from the DBpedia and load it in a local endpoint via https://github.com/dbpedia/Dockerized-DBpedia

dbpedia.org/sparql and the spotlight service might be synchronized in the future, but I don’t know when. Until then you need to build this yourself.

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