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Overview
One of the major obstacles for a wider usage of Web Data is the difficulty to obtain a clear picture of the available datasets. In order to reuse, link, revise or query a dataset published on the Web it is important to know the structure, coverage and coherence of the data.
LODStats is a statement-stream-based approach for gathering comprehensive statistics about datasets adhering to the Resource Description Framework (RDF). LODStats is based on the declarative description of statistical dataset characteristics. Its main advantages over other approaches are a smaller memory footprint and significantly better performance and scalability. We integrated LODStats into the CKAN dataset metadata registry and obtained a comprehensive picture of the current state of the Data Web.
Demo
A demo installation collecting statistics from all LOD datasets
registered on CKAN is available from:
Installation and Download
LODStats is available via
PyPI (e.g. pip install lodstats) and
GitHub (
https://github.com/AKSW/LODStats).
Installation instructions (from
PyPI):
$ virtualenv $HOME/lodstats-env
$ . $HOME/lodstats-env/bin/activate
(lodstats-env) $ pip install lodstats
Installation instructions (from source):
$ sudo apt-get install python-librdf python-virtualenv gcc python-dev python-setuptools
$ virtualenv $HOME/lodstats-env
$ . $HOME/lodstats-env/bin/activate
(lodstats-env) $ cd LODStats
(lodstats-env) $ python setup.py install
Using LODStats from the command-line:
(lodstats-env) $ lodstats --help
Usage: lodstats [options] [-m model.{rdf,nt,...}] file/URI
[...]
(lodstats-env) $ lodstats -vp some_rdf_file.nt
Further Information
- Jan Demter, Sören Auer, Michael Martin, Jens Lehmann:
LODStats – An Extensible Framework for High-performance Dataset Analytics, submitted to ESWC2012
Contact
- Jan Demter
| Dr. Sören Auer Johannisgasse 26, Zimmer 5-09 04103 Leipzig
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| Michael Martin Johannisgasse 26, Zimmer 5-20 04103 Leipzig
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| Dr. Jens Lehmann Johannisgasse 26, Zimmer 5-10 04103 Leipzig
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Information
Last Modification:
2012-03-24 00:57:48 by
Jan Demter