[ANN] Luzzu - A Linked Data Quality Assessment Framework release 1.0

Dear all,

We are pleased to announce the first official release of Luzzu - A
Quality Assessment Framework for Linked Data [1], now available on
Github (https://github.com/EIS-Bonn/Luzzu).

Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is
a generic framework based on the Dataset Quality Ontology (daQ) [2,3],
allowing users to define their own quality metrics. Luzzu is an
integrated platform that:

- assesses Linked Data quality using a library of generic and
user-provided domain specific quality metrics in a scalable manner;
- provides queryable quality metadata on the assessed datasets;
- assembles detailed quality reports on assessed datasets.

Furthermore, the infrastructure:
- scales for the assessment of big datasets;
- can be easily extended by the users by creating their custom and
domain-specific pluggable metrics, either by employing a novel
declarative quality metric specification language or conventional
imperative plugins;
- employs a comprehensive ontology framework for representing and
exchanging all quality related information in the assessment workflow;
- implements quality-driven dataset ranking algorithms facilitating
use-case driven discovery and retrieval.

This is the first public release of Luzzu and we plan to make
improvements available within the next weeks but welcome your feedback.


On behalf of the Luzzu development team,

Jeremy, Christoph and Santiago


[1] http://eis-bonn.github.io/Luzzu/
[2] http://purl.org/eis/vocab/daq
[3] http://eis-bonn.github.io/Luzzu/papers/semantics2014.pdf
[4] http://eis-bonn.github.io/Luzzu/howto.html<http://eis-bonn.github.io/Luzzu/howto.html%E2%80%8B>?