Hi all,
we are happy to announce the release of the initial version of the LDIF – Linked Data Integration Framework today.
LDIF is a software component for building Linked Data applications which translates heterogeneous Linked Data from the Web into a clean, local target representation while keeping track of data provenance.
Applications that consume Linked Data from the Web are confronted with the following two challenges:
- data sources use a wide range of different RDF vocabularies to represent data about the same type of entity.
- the same real-world entity, for instance a person or a place, is identified with different URIs within different data sources.
The usage of various vocabularies as well as the usage of URI aliases makes it very cumbersome for an application developer to write for instance SPARQL queries against Web data that originates from multiple sources.
A successful approach to ease using Web data in the application context is to translate heterogeneous data into a single local target vocabulary and to replace URI aliases with a single target URI on the client side before starting to ask SPARQL queries against the data.
Up-till-now, there have not been any integrated tools available that help application developers with these tasks.
With LDIF, we try to fill this gap and provide an initial alpha version of an open-source Linked Data Integration Framework that can be used by Linked Data applications to translate Web data and normalize URI aliases.
For Identity resolution, LDIF builds on the Silk Link Discovery Framework. For data translation, LDIF employs the R2R Mapping Framework.
More information about LDIF and a concrete usage example is provided on the LDIF website at
http://www4.wiwiss.fu-berlin.de/bizer/ldif/
Lots of thanks to
Andreas Schultz (FUB)
Andrea Matteini (MES)
Robert Isele (FUB)
Christian Becker (MES)
for their great work on the LDIF Framework.
Cheers,
Chris Bizer
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