ANN: LDIF - Linked Data Integration Framework V0.3 released.

Hi all,

we are happy to announce the release of the LDIF – Linked Data Integration
Framework Version 0.3.

The LDIF – Linked Data Integration Framework can be used within Linked
Data applications to translate heterogeneous data from the Web of Linked
Data into a clean local target representation while keeping track of data
provenance. LDIF provides an expressive mapping language for translating
data from the various vocabularies that are used on the Web into a
consistent, local target vocabulary. LDIF includes an identity resolution
component which discovers URI aliases in the input data and replaces them
with a single target URI based on user-provided matching heuristics. For
provenance tracking, the LDIF framework employs the Named Graphs data
model.

Compared to the previous release 0.2, the new LDIF release provides:

* data access modules for gathering data from the Web via file download,
crawling and accessing SPARQL endpoints. Web data is cached locally for
further processing.
* a scheduler for launching data import and integration jobs as well as
for regularly updating the local cache with data from remote sources.
* a second use case that shows how LDIF is used to gather and integrate
data from several music-related Web data sources.

More information about LDIF, concrete usage examples and performance
details are available at http://www4.wiwiss.fu-berlin.de/bizer/ldif/

Over the next months, we plan to extend LDIF along the following lines:

   1. Implement a Hadoop Version of the Runtime Environment in order to be
able to scale to really large amounts of input data. Processes and data
will be distributed over a cluster of machines.
   2. Add a Data Quality Evaluation and Data Fusion Module which allows
Web data to be filtered according to different data quality assessment
policies and provides for fusing Web data according to different
conflict resolution methods.

The development of LDIF is supported in part by Vulcan Inc. as part of its
Project Halo and by the EU FP7 project LOD2 (Grant No. 257943).

Cheers,

Andreas Schultz, Andrea Matteini, Robert Isele, Chris Bizer and Christian
Becker

Received on Friday, 7 October 2011 09:38:23 UTC