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Living Semantic Web

Does the Semantic Web behave like a living system?

Living Semantic Web > Results

The numeric results of the graph analysis are shown in Table 1. The two lines show the analysis of the network of ontologies at the DAML Ontologies Library in two different time points. This time distant measures will allow to show if the complex system nature of the Semantic Web is independent from time. The third one shows the same measures for the Copyright Ontology. This will allow to show if the Semantic Web is a complex system at different scales. All this measures can be compared with those from other complex systems networks: the results from WWW studies and human language words network.

Table 1. This table shows the compared networks, their number of nodes, the average degree , clustering factor C, average minimum path length and power-law tails exponents g

Network Nodes k C d g
DAMLOntos
(2003-4-11)
56592 4.63 0.152 4.37 -1.48
DAMLOntos
(2005-1-31)
307,231 3.83 0.092 5.07 -1.19
CopyrightOnto 971 3.71 0.071 3.99 -3.29
WWW ~200 M - 0.108 3.10 -2.10
WordsNetwork 500000 - 0.687 2.63 -1.50

From the previous data we can deduce that the Semantic Web is an Small World comparing its graph to the corresponding random graph, with the same size and average degree. The clustering factors C = 0.152 and C = 0.092 are much greater than that for the corresponding random graph C rand = 0.0000895, while the average path lengths d = 4.37 and d = 5.07 are similar to that for the corresponding random graph d rand = 7.23. For CopyrightOnto the same holds, C rand = 0.0034272 and d rand = 5.38.

On the other hand, studying the degree distributions, their scale-free nature has been detected and the power-law exponents have been calculated.

 

The final evidence is the degree distribution; it is clearly a power-law. The degree Cumulative Distribution Function (CDF) for the older DAMLOntos has linear regression with an exponent g = -1.485 with a regression error e% = 1.455. In the last study of DAMLOntos, the linear regression of this function gives an exponent g = -1.186 with a regression error e% = 0.896. The linear regression plot is shown in Figure 2.

Linear Regression

Fig. 2. Logscale degree distribution for the set of studied DAML library ontologies DAMLOntos) plus linear regressions and computed exponents for the two differentiated regions

Therefore, the graph for the portion of the Semantic Web that has been analysed shows clear evidences that the Semantic Web behaves like a Complex System. It is a small world, with a high clustering factor and a power-law degree distribution. It has also a scale-free nature, so the same properties can be observed at a different scale. In fact, as the measures shows, this is the case for different time points and differents scales. To conclude, we can deduce that the Semantic Web behaves like a Complex System and, consequently, we can say that it is one of them.

More detailed results are available from:

Measuring the Semantic Web PDF PPT

Gil, R. and García, R.
First on-Line conference on Metadata and Semantics Research, MTSR 2005
Rinton Press, 2006