ANN: Silk - Link Discovery Framework Version 2.3 released

Hi all,

we are happy to announce version 2.3 of the Silk - Link Discovery
Framework for the Web of Data.

The central idea of the Web of Data is to interlink data items using
RDF links. However, in practice most data sources are not sufficiently
interlinked with related data sources. The Silk Link Discovery
Framework addresses this problem by providing tools to generate links
between data items based on user-provided link specifications. It can
be used by data publishers to generate links between data sets as well
as by Linked Data consumers to augment Web data with additional RDF
links.

The new Silk 2.3 framework provides an improved Link Discovery Engine
with a significantly increased performance:
1. Improved loading perfomance: Multiple parallel SPARQL queries are
executed, while their results are merged on the fly.
2. Improved matching performance: New blocking method offers greatly
improved performance.
3. Improved overall performance: Matching tasks are now executed
concurrently to loading data instead of waiting for the complete data
set to be loaded.

Silk is provided in three different variants which address different use cases:
1. Silk Single Machine is used to generate RDF links on a single
machine. The datasets that should be interlinked can either reside on
the same machine or on remote machines which are accessed via the
SPARQL protocol. Silk Single Machine provides multithreading and
caching. In addition, the performance can be further enhanced using an
optional blocking feature.
2. Silk MapReduce is used to generate RDF links between data sets
using a cluster of multiple machines. Silk MapReduce is based on
Hadoop and can for instance be run on Amazon Elastic MapReduce. Silk
MapReduce enables Silk to scale out to very big datasets by
distributing the link generation to multiple machines.
3. Silk Server can be used as an identity resolution component within
applications that consume Linked Data from the Web. Silk Server
provides an HTTP API for matching instances from an incoming stream of
RDF data while keeping track of known entities. It can be used for
instance together with a Linked Data crawler to populate a local
duplicate-free cache with data from the Web.

More information about the Silk framework, the Silk-LSL language
specification, as well as several examples that demonstrate how Silk
is used to set links between different data sources in the LOD cloud
is found at:

http://www4.wiwiss.fu-berlin.de/bizer/silk/

The Silk framework is provided under the terms of the Apache License,
Version 2.0 and can be downloaded from

http://sourceforge.net/projects/silk2/

The development of Silk was supported by Vulcan Inc. as part of its
Project Halo (www.projecthalo.com) and by the EU FP7 project LOD2 -
Creating Knowledge out of Interlinked Data (http://lod2.eu/, Ref. No.
257943).

Happy linking,

Robert Isele, Anja Jentzsch and Chris Bizer

Received on Wednesday, 2 February 2011 10:10:41 UTC