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| The SEALS Yardsticks for Ontology Management - 2010 Campaign Results |
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This page presents an overview of the results of the first SEALS evaluation campaign over ontology engineering tools (i.e., the SEALS Yardsticks for Ontology Management). A detailed analysis of all these results can be found in SEALS Deliverable D10.3. The ontology engineering evaluation campaign was organized along three scenarios that covered the conformance, interoperability and scalability of these tools. A detailed description of these evaluation scenarios and of the test data used can be found in SEALS Deliverables D10.1 and D10.2. Tools evaluatedSometimes tools use ontology management frameworks for processing ontologies, which has an effect in their conformance and interoperability. The next table shows the tools evaluated and the ontology management frameworks (i.e., APIs) that they use, including in both cases their version numbers.
Conformance resultsThe following tables present the tool conformance results for RDF(S), OWL Lite, OWL DL and OWL Full, respectively. The tables show the number of tests in each category in which the results of a test can be classified, depending on whether the original and the resultant ontologies are the same (SAME), whether they are different (DIFF), or whether the tool execution fails (FAIL).
RDF(S) Conformance results.
OWL Lite Conformance results.
OWL DL Conformance results.
OWL Full Conformance results.
Interoperability resultsThe tables show the percentage of tests in which the original and the resultant ontologies in an interchange are the same. For each cell, the row indicates the tool origin of the interchange, whereas the column indicates the tool destination of the interchange.
RDF(S) Interoperability results.
OWL Lite Interoperability results.
OWL DL Interoperability results.
OWL Full Interoperability results.
Summary of conformance and interoperability resultsIn the results we can see that all those tools that manage ontologies at the RDF level (Jena and Sesame) have no problems in processing ontologies regardless of the ontology language. Since the rest of the tools evaluated are based in OWL or in OWL 2, their conformance and interoperability is clearly better when dealing with OWL ontologies. From the results presented in chapter 3 we can see that conformance and interoperability are highly influenced by development decisions. For example, the decision of the OWL API developers (propagated to all the tools that use it for ontology management) of converting all the ontologies into OWL 2 makes the RDF(S) conformance and interoperability of these tools quite low. Since the OWL Lite language is a subset of the OWL DL one, there is a dependency between the results obtained using the test suites for OWL Lite and OWL DL. In the results we can also see that, since the OWL DL test suite is more exhaustive than the OWL Lite one, the OWL DL evaluation unveiled more problems in the tools than the OWL Lite evaluation. These problems included not only issues related to the OWL DL language, but also issues related to OWL Lite ontologies included in the OWL DL test suite. The results also show the dependency between the results of a tool and those of the ontology management framework that it uses; using a framework does not isolate a tool from having conformance or interoperability problems. Besides inheriting existing problems in the framework (if any), a tool may have more problems if it requires further ontology processing (e.g., its representation formalism is different from that of the framework or an extension of it) or if it affects the correct working of the framework. However, using ontology management frameworks may help increasing the conformance and interoperability of the tools, since developers do not have to deal with the problems of low-level ontology management. Nevertheless, as observed in the results, this also requires being aware of existing defects in these frameworks and regularly updating the tools to use their latest versions. Scalability resultsAn overview of the scalability tests, the size of the corresponding ontologies and time spent on importing and exporting the ontology is available in table
Scalability results with real-world ontologies.
Scalability results with LUBM data generator ontologies.
Summary of scalability resultsThe current scenario, in which the duration of ImportExport operation is measured, is appropriate for the analysis; however, more dimensions should be added. As an example the amount of memory can be measured. In this way the extended scenario will be more suitable for a more complete testing of scalability. With respect to the results of the scalability tests, an extended analysis of the results should be provided in order to analyze why there are problems with some ontologies, how do these problems correlate with the size of the ontologies. It would be relevant to graphically analyze the relationship between the ontology size and the duration of the ImportExport operation. |
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