It should be noted that this is the partial answer, as the sub-questions on maintainability in Chapter 5 do not exhaustively cover all possible aspects of the ontology maintainability. The ontology maintainability was achieved primarily by designing the simple, small, and reusable ontology utilizing the best practices. Starting with the small ontology and gradually expanding it reduces the risk of accumulating unnecessary information in the ontology. In addition, the number of the CIs was reduced by utilizing the collective CI pattern for elements that pose little risk to the primary operation of the
SOI and therefore do not require to be distinguished as individuals based on the serial number.
During the project definition phase, it was noted that the domain experts cannot always provide useful requirements alone, so the input of ontology-building developer, in this case the author, was required to incorporate constraints. The involvement of developer in the design of the requirements was critical in concretizing the competency questions applicable to the ontology, and also in prioritizing which requirements can be implemented within the schedule. Ontology development differs from object-oriented programming in that the structure of the class and the relationships between the ontology classes differ from the structure of the corresponding domain of the object-oriented program. Therefore, the developers and the domain experts may require training before they can work with the challenges of real-world ontology modelling, even if they have previous experience in conceptual modelling.
In conclusion, the CMDB architecture could consist of small and independent graph databases stored on RDF4J servers and maintained locally near the SOI, as shown in Figure 34. Federated SPARQL queries consolidate data so that only the relevant information is downloaded and data at rest remains in the local CMDB graph databases.
RDF4J Desktop and FedX provide transparent federation for the multiple SPARQL endpoints by automatically selecting relevant sources, submitting expression templates to these sources for evaluation, and merging individual results.
Figure 34. The proposed CMDB architecture.
Federation With FedX
In summary from the above discussion, it can be concluded that the future development of the ontology and the database application can be divided into two tasks. Firstly, the quality of the ontology can be improved by testing and utilizing it with real-world data.
For this purpose, the actual graph database server providing the SPARQL endpoint services and the web-based client interface for the database management and query execution should be installed and deployed in the data centre. Secondly, the next stage of development could include the development of quality metrics such as Ontology Quality Evaluation Framework (OQuaRE) [20] to support the development of the next generation ontology. This thesis examined the ontology mainly from the perspective of maintainability, but subsequent iterations could utilize the metrics that capture issues related to structural, functional adequacy, reliability, performance efficiency, compatibility, portability, and quality of use.
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Rio parser uploads Turtle file to RDF4J NativeStore
public static void main(String[] args) {
// Define the constants
File dataDir = new File("C:/Users/Default
User.Lenovo/Documents/yamk/YAMK/THESIS/datadir");
String filename = "C:/Users/Default
User.Lenovo/Documents/yamk/YAMK/THESIS/Onto-CMDB.ttl";
// Define RDF4J NativeStore database String indexes = "spoc,posc,cosp";
Repository db = new SailRepository(new NativeStore(dataDir, indexes));
InputStream input = null;
model = Rio.parse(input, "", RDFFormat.TURTLE);
} catch (RDFParseException | UnsupportedRDFormatException | IOException e) {
try (RepositoryConnection conn = db.getConnection()) {
// Add the model to database conn.add(model);
}
catch (RDF4JException e) { }
finally {
// shut down the database db.shutDown();
} } }
The feature unit test cases
@Test
public void testIfhasSWIDandProductTitle() throws Exception { try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "ASK { :CISCO_IOS_12_4 :hasSWID :Cisco_IOS . :Cisco_IOS :ProductTitle \"Cisco IOS
\"^^xsd:string } \n";
BooleanQuery booleanQuery =
conn.prepareBooleanQuery(QueryLanguage.SPARQL,query);
assert(booleanQuery.evaluate());
conn.close();
db.shutDown();
} }
@Test
public void testIfhasPhysicalElement() throws Exception { try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : <http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "ASK { :CISCO1841_002 :hasPhysicalElement :Cisco_1841_chassis . } \n";
BooleanQuery booleanQuery =
conn.prepareBooleanQuery(QueryLanguage.SPARQL,query);
assert(booleanQuery.evaluate());
conn.close();
db.shutDown();
} }
@Test
public void testIfhasLocation() throws Exception { try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : <http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "ASK { :CISCO1841_001 :hasLocation :M1_Riihimaki } \n";
BooleanQuery booleanQuery =
conn.prepareBooleanQuery(QueryLanguage.SPARQL,query);
assert(booleanQuery.evaluate());
conn.close();
db.shutDown();
} }
The schema unit test cases
import com.opencsv.CSVWriter;
public Writer fileWriter;
@Test
public void testCountofClasses() throws Exception { try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : <http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "SELECT DISTINCT (strafter(str(?s), \"#\") as ?fragment) WHERE {?s a owl:Class} \n";
TupleQuery tupleQuery =
conn.prepareTupleQuery(QueryLanguage.SPARQL,query);
String[] header = {"Classes"};
fileWriter = new FileWriter("C:/TEMP/test.csv", false);
CSVWriter csvWriter = new CSVWriter(fileWriter, ',', CSVWriter.NO_QUOTE_CHARACTER, CSVWriter.NO_ESCAPE_CHARACTER, CSVWriter.DEFAULT_LINE_END);
csvWriter.writeNext(header);
try (TupleQueryResult res = tupleQuery.evaluate()) {
csvWriter.writeNext(new String[]
{solution.getValue("fragment").toString()});
@Test
public void testReadCSVFile() throws Exception {
BufferedReader csvReader = new BufferedReader(new
FileReader("C:/TEMP/test.csv"));
System.out.println(Arrays.toString(data));
}
public void testCountofProduct() throws Exception { try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : <http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "SELECT ?s WHERE {?s rdf:type :Product } \n";
TupleQuery tupleQuery =
conn.prepareTupleQuery(QueryLanguage.SPARQL,query);
try (TupleQueryResult res = tupleQuery.evaluate()) { int count = 0;
@Test
public void testCountofFRU() throws Exception {
try (RepositoryConnection conn = db.getConnection()) {
String query = "PREFIX : <http://www.semanticweb.org/defaultuser/
ontologies/2020/7/Onto-CMDB#> \n"
+ "SELECT * WHERE {?s ?y :MEM1800-64CF} \n";
TupleQuery tupleQuery = conn.prepareTupleQuery(QueryLanguage.SPARQL,query);
try (TupleQueryResult res = tupleQuery.evaluate()) {
int count = 0;
while (res.hasNext()) {
BindingSet solution = res.next();
System.out.println("?s = " + solution.getValue("s"));
count++;
}
assertEquals(2, count);
} finally {
conn.close();
db.shutDown();
} } }