Music and Audio Information Search System Kiavash Bahreini

Music and Audio Information Search System Kiavash Bahreini – 055251

Outline n n n n Introduction Semantic Web What is Ontology? Domains and ranges Ontology Languages (OWL) Search on the Web Object-oriented Modeling Paradigm Adaptable Inference Capabilities Background The Music Ontology and OWL Protégé JBuilder 2006 Jena 2. 3 Ontology API

Outline (cont) n n n RDQL Java Server Pages Algernon Tomcat Microsoft SQL Server n Music and Audio system use case, implementation and execution n n n Execution of program in Browser Running queries in Algernon Running queries in SQL Server 2005 Some source codes for classes in Music and Audio ontology Comparison of Semantic Search and Regular Search Conclusion References

Introduction n Internet changed the music industry. At first, sharing systems like Napster allowed people to share any song they had on their computer with millions other people. n Communities like this ontology started to appear. n The Music Ontology is an attempt to link all the information about musical Artists, Albums and Tracks together: from Music. Brainz to my ontology.

Introduction (Cont) n The goal is to express all relations between musical information to help people finding anything about music and musicians. It is based around the use of machine readable information provided by any web site or web service on the Web.

Semantic Web n Common framework n Allows data n Sharing n Reuse n Across domains n Application n Enterprise n Community boundaries n Based on Resource Description Framework (RDF) n XML for syntax n URIs for naming.

What is Ontology? n At the heart of all Semantic Web applications is the use of ontologies. A commonly agreed definition of an ontology is: ‘An ontology is an explicit and formal specification of a conceptualisation of a domain of interest.

Domains and ranges

Ontology Languages (OWL) n OWL Lite n OWL DL n OWL Full

Search on the Web n Seeking information on the Web is widely used and will become more important as the Web grows. Nowadays, search engines browse through the Web seeking given terms within web pages or text documents without using ontologies. n Traditional search engines such as Yahoo are based on full-text search. These search engines are seeking documents, which contain certain terms.

Object-oriented Modeling Paradigm n In the past decade the object-oriented paradigm has become prevalent for conceptual modeling. n Object-oriented models can easily be visualized, thus making understanding conceptual models much simpler. Hence, any successful ontology modeling approach should follow the object-oriented modeling paradigm.

Adaptable Inference Capabilities n Inference mechanisms for deduction of information not explicitly asserted is an important characteristic of ontology-based systems. However, systems with very general inference capabilities often do not take into account other needs, such as scalability and concurrency. n For example, in the RDFS and OWL ontology languages it is possible to make some classes the domain or the range of some property. This statement can be interpreted as an axiom saying that for any property instance in the ontology, the source and target instances can be inferred to be members of the domain and target concepts, respectively.

Background n The Music Ontology is an effort of Zit. Gist LLC. to express musical relationships between artists, albums and tracks. n I used OWL and to query that same information using the RDQL query language for RDF and OWL. n The Music Ontology is mainly influenced by the Music. Brainz community music metadatabase. Most of the properties of this ontology reflect the relationships described in that database. Most of the relationship descriptions written in this document have been taken on the Music. Brainz Wiki

The Music Ontology and OWL n The Music Ontology is an application of the Ontology Web Language (OWL) because the subject area I am describing – music: albums, artists, audio file formats, encoding audio files, genre, instrument, key, note, official, resource, rhythm etc has so many competing requirements. n By using OWL, the Music Ontology gains a powerful extensibility mechanism, allowing Music-Ontologybased descriptions to be mixed with claims made in any other OWL and RDF vocabulary

Protégé n Protégé is n an ontology editor n knowledge-base editor n an open-source, Java tool n provides extensible architecture to create customized knowledge-based applications. n Developed by Stanford University, USA

Music and Audio Ontology n Provides information on n n n n Album Artist Audio. File. Type Encoding Instrument Key Live Note Official Resource Rhythm Signal Soundtrack Spokenword Track Type (Classes)

Music and Audio Ontology Object Properties) n Provides information on n arranged n covered n djmix_of n duration n image n linkto_wikipedia n medley_of n member_of n performed n similar_to n track. Num n translation_of (Data Type and

Music and Audio Ontology (General structure)

JBuilder 2006 n The system is written in JBuilder 2006. JBuilder is and IDE (Integrated Development Tools) for developing new application, web etc software based on Java Language. All of the packages and classes for using OWL and running queries are imported into this IDE.

Jena 2. 3 Ontology API n Jena 2. 3 Ontology API is a Java framework for building Semantic Web applications. Use RDF models in your Java applications with the Jena Semantic Web Framework.

RDQL n RDQL is a query language for RDF in Jena models. The idea is to provide a dataoriented query model so that there is a more declarative approach to complement the finegrained, procedural Jena API. n It is "data-oriented" in that it only queries the information held in the models; there is no inference being done. Of course, the Jena model may be 'smart' in that it provides the impression that certain triples exist by creating them on-demand.

Java Server Pages n Java. Server Pages (JSP) technology allows web developers and designers to rapidly develop and easily maintain information-rich, dynamic web pages that leverage existing business systems. As part of the Java family, the JSP technology enables rapid development of web-based applications that are platform independent. n In theory, Java. Server Pages technology separates the user interface from content generation, enabling designers to change the overall page layout without altering the underlying dynamic content.

Algernon n Algernon is a rule-based inference system, implemented in Java and interfaced with Protégé and it is developed by Micheal Hewett. It allows executing queries within the Protégé GUI. n It performs forward and backward rulebased processing of knowledge bases, and efficiently stores and retrieves information in ontologies and knowledge bases. It has an ability to call external Java methods and an internal LISP subsystem.

Tomcat n Tomcat is the official reference implementation of the Java Servlet 2. 2 and Java. Server Pages 1. 1 technologies. Developed under the Apache license in an open and participatory environment, it is intended to be a collaboration of the best-of-breed developers from around the world. n Tomcat is a servlet container and Java. Server Pages(tm) implementation. It may be used stand alone, or in conjunction with several popular web servers: n Apache, version 1. 3 or later n Microsoft Internet Information Server, version 4. 0 or later n Microsoft Personal Web Server, version 4. 0 or later n Netscape Enterprise Server, version 3. 0 or later

Microsoft SQL Server n Microsoft SQL Server 2005 is a database and data analysis platform for large-scale online transaction processing (OLTP), data warehousing, and e-commerce applications. n The Database Engine is the core service for storing, processing, and securing data. The Database Engine provides controlled access and rapid transaction processing to meet the requirements of the most demanding data consuming applications within your enterprise. The Database Engine also provides rich support for sustaining high availability.

Music and Audio system use case, implementation and execution

Music and Audio system use case, implementation and execution n Execution of program in Browser JBuilder 2006 Computation Engine User interface JSP Pages Jena 2. 3 OWL API Inference Engine RDQL Serarch Query Protege 3. 2 OWL File Ontology & Knowledge Base

Music and Audio system use case, implementation and execution n Execution of program in Browser

Music and Audio system use case, implementation and execution n Running queries in Algernon n 1) Find all artist names that their age=45, nationality="Turkish", country "Turkey", and number. Of. Albums=50: ((: BIND ? age 45) (: BIND ? nationality "Turkish") (: BIND ? country "Turkey") (: BIND ? number. Of. Albums 50) (: INSTANCE Artist ? a. Name) (age ? a. Name ? age) (nationality ? a. Name ? nationality) (country ? a. Name ? country) (number. Of. Albums ? a. Name ? number. Of. Albums) (: FAIL (: neq ? age)) (: FAIL (: neq ? nationality)) (: FAIL (: neq ? country)) (: FAIL (: neq ? number. Of. Albums)))

Music and Audio system use case, implementation and execution n Running queries in Algernon n 2) Find all Web. Sites Address for artists: ((: BIND ? has. Resource "N/A") (: INSTANCE Resource ? Atrist. Website. Address) (has. Resource ? Atrist. Website. Address ? has. Resource) (: FAIL (: neq ? has. Resource ? my. Link)))

Music and Audio system use case, implementation and execution n Running queries in Algernon n 3) Find all album names which are not linkto_wikipedia site: ((: BIND ? linkto_wikipedia "N/A") (: INSTANCE Album ? album. Name) (linkto_wikipedia ? album. Name ? linkto_wikipedia) (: FAIL (: neq ? linkto_wikipedia)))

Music and Audio system use case, implementation and execution n Running queries in SQL Server 2005 n 1) Find all artist names that their age=45, nationality="Turkish", country "Turkey", and number. Of. Albums=50: SELECT DISTINCT [name], [age], [nationality], [country], [number. Of. Albums] FROM dbo. tbl. Artist WHERE [age]=45 AND [nationality]='Turkish' AND [country]='Turkey' AND [number. Of. Albums]=50 GO

Music and Audio system use case, implementation and execution n Running queries in SQL Server 2005 n 2) Find all Web. Sites Address for artists: SELECT [id], [name], [has. Resource] FROM dbo. tbl. Resource WHERE [has. Resource]='N/A' GO

Music and Audio system use case, implementation and execution n Running queries in Algernon n 3) Find all album names which are not linkto_wikipedia site: SELECT [id], [name], [linkto_wikipedia] FROM dbo. tbl. Album WHERE [linkto_wikipedia]='N/A' GO

Music and Audio system use case, implementation and execution n Some source codes for classes in Music and Audio ontology: <owl: Class rdf: ID="Album"> <rdfs: comment rdf: datatype="http: //www. w 3. org/2001/XMLSchema#strin g" >Album - This is a generic term defining a package of tracks. This applies to compact disks, vinyls, CD singles, EPs, etc. </rdfs: comment> <rdfs: sub. Class. Of> <owl: Class rdf: about="#My. Classes"/> </rdfs: sub. Class. Of> <owl: Restriction> <owl: max. Cardinality rdf: datatype="http: //www. w 3. org/2001/XMLSchema#int" >1</owl: max. Cardinality> <owl: on. Property> <owl: Datatype. Property rdf: ID="album. Name"/> </owl: on. Property> </owl: Restriction> </rdfs: sub. Class. Of> </owl: Class>

Comparison of Semantic Search and Regular Search n In relational database management systems (RDBMS), there is n n no class relationship. It means sub classes cannot inherit all properties from their super classes and also there is no instantiation. Extra work will be required to define class relations and all properties separately. In semantic databases there are domains and ranges which can apply for each property but in an RDBMS it is impossible. There is no object property for these systems. In relational database Vastly coding implementation for returning data is need. There is no way for using and importing ontologies, and for returning objects data types.

Comparison of Semantic Search and Regular Search n By using OWL, the Music Ontology gains a powerful extensibility mechanism, allowing Music-Ontology-based descriptions to be mixed with claims made in any other OWL or RDF vocabularies. I can re-use other ontologies to describe different relationship between classes. n OWL provides the Music Ontology with a way to mix together different descriptive vocabularies in a consistent way. Vocabularies can be created by different communities and groups as appropriate and mixed together as required, without needing any centralized agreement. n On the other hand, many existing SW tools are still fileoriented and also mine. This limits the size of ontologies that can be processed, as the whole ontology must be read into main memory. Further, the multi-user support and transactions are typically not present, so the whole infrastructure realizing these requirements must be created from scratch but my project is web based and it is able support multi-user transactions.

Conclusion n The Music Ontology is an application of the Ontology Web Language (OWL) because the subject area are – music: artists, albums and tracks etc -- has so many competing requirements that a standalone format would not capture them or would lead to trying to describe these requirements in a number of incompatible formats. By using OWL, the Music Ontology gains a powerful extensibility mechanism, allowing Music-Ontology-based descriptions to be mixed with claims made in any other OWL vocabulary. n OWL provides the Music Ontology with a way to mix together different descriptive vocabularies in a consistent way. Vocabularies can be created by different communities and groups as appropriate and mixed together as required, without needing any centralized agreement. n In summary then, OWL is self-documenting in ways which enable the creation and combination of vocabularies in a devolved manner. This is particularly important for an ontology which describes communities, since online communities connect into many other domains of interest, which it would be impossible (as well as suboptimal) for a single group to describe adequately in non-geological time.

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