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A Software Framework and Datasets for the Analysis of Graph Measures on RDF Graphs

  • Matthäus ZlochEmail author
  • Maribel AcostaEmail author
  • Daniel Hienert
  • Stefan Dietze
  • Stefan Conrad
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11503)

Abstract

As the availability and the inter-connectivity of RDF datasets grow, so does the necessity to understand the structure of the data. Understanding the topology of RDF graphs can guide and inform the development of, e.g. synthetic dataset generators, sampling methods, index structures, or query optimizers. In this work, we propose two resources: (i) a software framework (Resource URL of the framework: https://doi.org/10.5281/zenodo.2109469) able to acquire, prepare, and perform a graph-based analysis on the topology of large RDF graphs, and (ii) results on a graph-based analysis of 280 datasets (Resource URL of the datasets: https://doi.org/10.5281/zenodo.1214433) from the LOD Cloud with values for 28 graph measures computed with the framework. We present a preliminary analysis based on the proposed resources and point out implications for synthetic dataset generators. Finally, we identify a set of measures, that can be used to characterize graphs in the Semantic Web.

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Authors and Affiliations

  1. 1.GESIS - Leibniz-Institute for the Social SciencesMannheimGermany
  2. 2.Institute AIFB, Karlsruhe Institute of TechnologyKarlsruheGermany
  3. 3.Institute for Computer ScienceHeinrich-Heine University DüsseldorfDüsseldorfGermany

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