namedgraph
Joined 7 years ago
Joined 7 years ago
We participated in a huge RfP for a pharma company which planned RDF KG infrastructure for the next couple of years with 500 billion triple capabilities.
Biomedical, finance, defence, automotive -- all of those industries are using RDF/SPARQL. Just because your problems are not big or complex enough doesn't mean this tech is not used. It takes a certain organization size for Knowledge Graphs to make sense and pay off, that's why most industry users are Fortune 500-level companies.
What kind of data are you looking to transform?
Check the GH page for more screenshots: https://atomgraph.github.io/LinkedDataHub/
Can you ping me at [email protected]? Would be appreciated.
The enterprise Knowledge Graphs (yes, it's the same SemWeb tech stack in principle) in Fortune 500 sized companies have in-house platforms that present the graph to the end-users, with entity browsers, analytics, dashboards, structured content etc. LinkedDataHub is an attempt to bootstrap an open-source, standards-driven version of that.
It can be used as a framework but it's a standalone application as well, because it provides the default built-in ontologies as well UI for Linked Data and SPARQL consumption.
Disclaimer: I'm the main developer.
XML to XML, XML to RDF, JSON to XML and XML to JSON, XML to text -- XSLT can be used for all kinds of transformations. 3.0 also supports streaming transforms, which is very useful for large input files.
XSLT is a declarative DSL made specifically for the XML data model. It does limited things such as navigating the XML tree but does them really well. It lifts the abstraction level so you can focus on the transformation. You can transform XML with bash or a general purpose language like Java, but it will never be so concise or effective.