Re: ANN: LDIF - Linked Data Integration Framework V0.1 released.

Thanks Chris,

In HCLS, we have been using proxy and Common Reference Ontologies in
some of our linked data work, in several task forces. A local
namespace that could be redirected/remapped to more appropriate
namespaces was motivated by the syndrome of having chosen a target
vocabulary and still hesitating about which term to use. The use of a
proxy ontology or namespace can help people over the threshold.

We were discussing the need for a framework in yesterday's HCLS LODD
(Linked Open Drug Data) telcon that would help one choose the URIs for
creating one's own linked data and otherwise aid in creating a mapping
to, e.g. LODD sets. One notion that came up was how such a framework
could make use of ontologies, for example, served from BioPortal's
SPARQL endpoint[1] to offer ontological terms to linked open data
developers. My sense is that the interplay between choice of
URIs/terms, mappings, and the resulting level of effort to integrate
or link to existing linked data confounds many would-be adopters.

Best,
Scott

[1] http://sparql.bioontology.org/webui/

-- 
M. Scott Marshall, W3C HCLS IG co-chair, http://www.w3.org/blog/hcls
http://staff.science.uva.nl/~marshall

On Wed, Jun 29, 2011 at 3:23 PM, Chris Bizer <chris@bizer.de> wrote:
> Hi all,
>
>
>
> we are happy to announce the initial release 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:
>
>
>
> 1. data sources use a wide range of different RDF vocabularies to represent
> data about the same type of entity.
>
> 2. 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 framework.
>
>
>
> Best,
>
>
>
> Chris
>
>
>
>
>
> Acknowledgments
>
>
>
> The development of LIDF is supported in part by Vulcan Inc. as part of its
> Project Halo and by the EU FP7 project LOD2 - Creating Knowledge out of
> Interlinked Data (Grant No. 257943).
>
>
>
> --
>
> Prof. Dr. Christian Bizer
>
> Web-based Systems Group
>
> Freie Universität Berlin
>
> +49 30 838 55509
>
> http://www.bizer.de
>
> chris@bizer.de
>
>

Received on Thursday, 30 June 2011 15:13:17 UTC