[ANN] DBpedia’s Databus and strategic initiative to facilitate 1 Billion derived Knowledge Graphs by and for Consumers until 2025

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[Please forward to interested colleagues]

We are proud to announce that the DBpedia Databus website 
at<https://databus.dbpedia.org/>_https://databus.dbpedia.org_ 
<https://databus.dbpedia.org/> and the SPARQL API 
at<https://databus.dbpedia.org/(repo/sparql|yasgui)>_https://databus.dbpedia.org/(repo/sparql|yasgui)_ 
(_docu_ <http://dev.dbpedia.org/Download_Data>) are in public beta now. 
The system is usable (eat-your-own-dog-food tested) following a “working 
software over comprehensive documentation” approach. Due to its many 
components (website, sparql endpoints, keycloak, mods, upload client, 
download client, and data debugging), we estimate approximately six 
months in beta to fix bugs, implement all features and improve the 
details. If you have any feedback or questions, please use 
the<https://forum.dbpedia.org/>_DBpedia Forum_ 
<https://forum.dbpedia.org/>, the “report issues” button, or 
_dbpedia@infai.org_.


The full document is available at: 
_https://databus.dbpedia.org/dbpedia/publication/strategy/2019.09.09/strategy_databus_initiative.pdf_ 


We are looking forward to the feedback and discussion at the_14th 
DBpedia Community Meeting at SEMANTiCS 2019 in Karlsruhe_ 
<https://wiki.dbpedia.org/events/14th-dbpedia-community-meeting-karlsruhe> 
on September 12th or online.


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      DBpedia Databus

The DBpedia Databus is a platform to capture invested effort by data 
consumers who needed better data quality (fitness for use) in order to 
use the data and give improvements back to the data source and other 
consumers. DBpedia Databus enables anybody to build an automated 
DBpedia-style extraction, mapping and testing for any data they need. 
Databus incorporates features from DNS, Git, RSS, online forums and 
Maven to harness the full workpower of data consumers.


      Vision

Professional consumers of data worldwide have already built stable 
cleaning and refinement chains for all available datasets, but their 
efforts are invisible and not reusable. Deep, cleaned data silos exist 
beyond the reach of publishers and other consumers trapped locally in 
pipelines.

*Data is not oil that flows out of inflexible pipelines*. Databus breaks 
existing pipelines into individual components that together form a 
decentralized, but centrally coordinated data network in which data can 
flow back to previous components, the original sources, or end up being 
consumed by external components,

The Databus provides a platform for re-publishing these files with very 
little effort (leaving file traffic as only cost factor) while offering 
the full benefits of built-in system features such as automated 
publication, structured querying, automatic ingestion, as well as 
pluggable automated analysis, data testing via continuous integration, 
and automated application deployment *(software with data)*. The impact 
is highly synergistic, just a few thousand professional consumers and 
research projects can expose millions of cleaned datasets, which are on 
par with what has long existed in deep silos and pipelines.


    1 Billion interconnected, quality-controlled Knowledge Graphs until 2025

As we are inversing the paradigm form a publisher-centric view to a data 
consumer network, we will open the download valve to enable discovery 
and access to massive amounts of cleaner data than published by the 
original source. The main DBpedia Knowledge Graph - cleaned data from 
Wikipedia in all languages and Wikidata - alone has 600k file downloads 
per year complemented by downloads at over 20 chapter, 
e.g.<http://es.dbpedia.org/>_http://es.dbpedia.org_ 
<http://es.dbpedia.org/> as well as over 8 million daily hits on the 
main Virtuoso endpoint. Community extension from the alpha phase such 
as<https://databus.dbpedia.org/sven-h/dbkwik/dbkwik/2019.09.02>_DBkWik_ 
<https://databus.dbpedia.org/sven-h/dbkwik/dbkwik/2019.09.02>,<https://databus.dbpedia.org/propan/lhd/linked-hypernyms>_LinkedHypernyms_ 
<https://databus.dbpedia.org/propan/lhd/linked-hypernyms> are being 
loaded onto the bus and consolidated and we expect this number to reach 
over 100 by the end of the year. Companies and organisations who 
have<https://github.com/dbpedia/links>_previously uploaded their 
backlinks here_ <https://github.com/dbpedia/links> will be able to 
migrate to the databus. Other datasets are cleaned and posted. In two of 
our research projects_LOD-GEOSS_ 
<https://www.enargus.de/pub/bscw.cgi/?op=enargus.eps2&s=14&q=BASF%20SE&v=10&m=2&id=1216225&p=1> 
and<http://plass.io/>_PLASS_ <http://plass.io/>, we will re-publish open 
datasets, clean them and create collections, which will result in 
DBpedia-style knowledge graphs for energy systems and supply-chain 
management.

The *full document* is available at: 
_https://databus.dbpedia.org/dbpedia/publication/strategy/2019.09.09/strategy_databus_initiative.pdf_ 


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