KARMA from University of Southern California takes tools for a wide variety of sources and maps it to your ontologies and generates linked data. It is open source and free. [I have not even re-read this post. Running to the next session.]

They are demo-ing using a folder full of OWL ontology files. [OWL files contain the rules that define ontologies. KARMA runs in your browser. The mapping format is R2RML, which is designed for relational databases, but they’ve extended it to handle more types of databases. You can import from a database, files, or a service. For the demo, they’re using CSV files from a Smithsonian database that consists of display names, IDs represented unique people, and a variant or married name. They want to map it to the Europeana ontology. KARMA shows the imported CSV and lets you (for example) create a URI for every person’s name in the table. You can use Python to transform the variant names into a standard name ontology, e.g. transforming “married name” into aac-ont:married (American Art Consortium), You can model the data and it learns it. E.g., it asks if you want to map the original’s ConstituentID to saam-ont:constituentID or saam-ont:objectId. (It recognizes that the ID is all numerals.) There’s an advanced option that lets you mp it to, for example, a URI for aac-ont:Person1.

He clicks on the “display name” and KARMA suggests that it’s a SKOS altLabel, or a FOAF name, etc. If there are no useful suggestions, you can pick one that’s close and then edit it. You can browse the ontologies in the folders you’ve configured it to load. You can have synonyms (“a FOAF person can be a SKOS person.”) [There’s yet more functionality, but this where I topped out.]

You can save this as a process that can be run in batch mode.

Categories: libraries dw