Apparently this hasn’t been echoed enough times. A lot of teams are still wondering what they should use if they want to store RDF metadata in Nepomuk and how to query it.
What happened before
We have refactoring to bring Tracker’s codebase into a better state. This is being released as Tracker 0.6.9x. This one sentence is really not enough to describe the changes. We can’t continue talking about the past forever. Sorry guys.
We have introduced support for SPARQL and Nepomuk in Tracker. We also added the class-signals feature, Turtle import & export, and many other features like SPARQL UPDATE support. Making the storage engine effectively a generic Nepomuk RDF store that can be used to store and query RDF data.
What will happen
We are at this moment planning to rearchitect Tracker a little bit.
Among our plans we want to make the RDF metadata store standalone. The store stores your metadata using Nepomuk as ontology and enables the application developer to query in SPARQL. This means that it’ll be possible to use this storage service without the indexer even installed. This is already possible but right now we do the crawling and monitoring in the storage service.
We plan to move the crawling and monitoring to the indexer. One idea is that the indexer will instruct the extractor to do an analysis and then the extractor will push the extracted metadata to the RDF storage service. Making the indexer and extractor a provider & consumer like any other. Making them optional and separately packagable.
This because we get requests from other teams who don’t want the indexing. Modularizing is usually a good thing, so we now have plans to make this possible as a feature.
Other plans that we haven’t thoroughly planned yet include support for custom ontologies. We have a good idea for this, though. We want to wait for it until after the rearchitecturing. Support for custom ontologies will include removing ontologies, installing ontologies and asking for a backup that’ll contain the metadata that is specific for an installed ontology.
Support for custom ontologies doesn’t mean that application developers should all go spastic and start making ontologies. I know you guys! Don’t do it! We want applications to reuse as much of the Nepomuk set as possible. The more Nepomuk gets reused, the more interopability between apps is possible.