This repository contains the results of a graph-based analysis of 280 data sets of the LOD Cloud 2017. http://data.gesis.org/lodcc/2017-08/ contains a browsable version of the results presented here. It containts the collection of 280 datasets, available as serialized graph-objects and a report on 28 graph measures of each of the datasets.

The analysis was prepared and performed with a software framework for the analysis of graph measures of RDF graphs.

The folder results/ contains four files

• analysis_results.csv, contains the main results of the analysis. You can find values for all measures for all datasets considered, sorted by knowledge domain and size of the datasets in terms of edges.
• analysis_statistics.csv, contains aggregated values for all measures per domain.
• correlation_analysis.csv, the Pearson correlation test to check correlations of all measures.
• vertex_centrality_uris.csv, a table of RDF resources for the values of max_degree, max_{in|out}_degree, and max_pagerank per dataset.

For the analysis to run with datasets from the LOD cloud we have prepared 280 datasets for efficient graph analysis. That means in particular that each dataset, (1) was downloaded, (2) checked and fixed for a valid media type, (3) converted into n-triples (if necessary) and merged into one file (if archived), (4) the content was hashed and set up as an edgelist, (5) and stored as compressed binary format gt.gz, ready being used by https://graph-tool.skewed.de library.

You can find all datasets on this website.

The repository of the client software that enables dataset preparation and the graph-based analysis can be found here: https://github.com/mazlo/lodcc

The folder scripts/ contains

• an R script to reproduce the results reported in the paper,
• a Juypter notebook to reproduce the results reported in the paper: https://github.com/mazlo/lod-graph-analysis/blob/master/scripts/lod-analysis-notebook.ipynb

The file contains a header row and results for all measures per dataset row-wise. We used the technical notation of the measure as column name. Examples on column names are:

• name, is the dataset name
• domain, is the knowledge domain which can be found in the LOD Cloud
• n, the number of vertices
• m, the number of edges
• avg_degree, the average degree,
• ..., etc.

Please note country-specific settings for decimal values.

The folder plots/degree-distributions contains plots that were automatically generated during the analysis on degree measures. You can find for each of the datasets considered a plot of the total degree distribution (distribution_degree.pdf file) and the in-degree distribution (distribution_in-degree.pdf file) values of all vertices. You can view all plots per datasets on the website.

The following diagram depicts the datasets included in this analysis (highlighted in color).

This is an extension of the original "Linking Open Data Cloud" diagram (see source below) and is licensed under CC-BY-SA.

Source: "Linking Open Data cloud diagram 2017, by Andrejs Abele, John P. McCrae, Paul Buitelaar, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"

Below are basic statistics about the analysed datasets. These numbers also can be found in analysis_statistics.csv

This package is licensed under the MIT License.

Please refer to the DOI for citation.