- From: Mcgibbney, Lewis J (398M) <Lewis.J.Mcgibbney@jpl.nasa.gov>
- Date: Tue, 9 Dec 2014 17:21:55 +0000
- To: "Debattista, Jeremy" <Jeremy.Debattista@iais-extern.fraunhofer.de>, "Public DWBP WG" <public-dwbp-wg@w3.org>
- Message-ID: <D0AC6F9B.A17A%lewis.j.mcgibbney@jpl.nasa.gov>
Hi Jeremy, I checked out your codebase and sent you a pull request for adding documentation to your README.md. https://github.com/EIS-Bonn/Luzzu/pull/5 Thanks for linking your code here, really nice to see cross-pollination of efforts. Lewis Dr. Lewis John McGibbney PhD, B.Sc., MAGU Engineering Applications Software Engineer Level 2 Computer Science for Data Intensive Systems Group 398M Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena, California 91109-8099 Mail Stop : 158-256C Tel: (+1) (818)-393-7402 Cell: (+1) (626)-487-3476 Fax: (+1) (818)-393-1190 Email: lewis.j.mcgibbney@jpl.nasa.gov [cid:2B7FA160-5423-4FF7-80B7-330BE0935683] Dare Mighty Things From: <Debattista>, Jeremy <Jeremy.Debattista@iais-extern.fraunhofer.de<mailto:Jeremy.Debattista@iais-extern.fraunhofer.de>> Date: Tuesday, December 9, 2014 at 8:18 AM To: Public DWBP WG <public-dwbp-wg@w3.org<mailto:public-dwbp-wg@w3.org>> Subject: [ANN] Luzzu - A Linked Data Quality Assessment Framework release 1.0 Resent-From: <public-dwbp-wg@w3.org<mailto:public-dwbp-wg@w3.org>> Resent-Date: Tuesday, December 9, 2014 at 8:19 AM 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>
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Received on Tuesday, 9 December 2014 17:23:06 UTC