Analysis and Visualization of Biological Publication Data

Bachelorarbeit von Maren Lang

Abstract:

The content of today’s World Wide Web is semantically not well structured. Every-thing is built for people and the data is therefore machine-readable but not machine- understandable. The semantic Web provides a solution for this problem through a new form of content structure. One technology for developing the Semantic Web is the Resource Description Framework (RDF).

RDF is a language for representing information about resources in the World Wide Web and is particularly intended for representing metadata about Web resources. Therefore RDF provides ‘interoperability’ between applications that exchange machine-understandable information on the Web. In this work, existing biological publication data which is stored in an object-relational database, is transformed into data represented in RDF. With the newly created RDF model it is possible to make a new way of queries, not only key word searching, but also queries with semantic sense. The additional advantage oft his representation is that it can be described not only in triples or XML structure but also in directed graphs.

The World Wide Web provides documents that are built for human usage. There are formats like HTML, SVG and other extensions like Javascript or Javaapplets which are made for representing information. The content is semantically not well structured. These documents are structured for their presentation and are meant for people rather than computer which process data and information automatically. Everything is built for people and the data therefore is machine-readable but not machine-understandable. The Semantic Web provides a solution for this problem through a new form of structuring the content of the Web. It is not a separate Web but an extension of the existing one. There is, beside the documents of the Web, well defined additional information, which the computer is able to exploit automatically. This will give search engines more selective results as answer to the user enquired queries.

Current search engines normally provide a big quantity of results to which the user has not or hardly referred initially. Their criteria of assigning a document to the set of relevant documents are the occurrences of one or several keywords. The results could be more precise if additional information which concerns the question would be considered. For example if somebody searches a document of mister Miller, the search engine could take into account, that one searches an article which has an author named Miller and not to select all articles where the word Miller appears. Adding logic to the Web also means to use rules to make inferences, choose courses and ask questions, which is the task before the Semantic Web community at the moment. One technology for developing the Semantic Web is the eXtensible Markup Language (XML). XML allows users to add arbitrary structure to their documents but says nothing about what the structures means. But the Semantic Web will enable machines to comprehend semantic documents and data, not human speech and writings. Meaning is expressed by the Resource Description Framework (RDF) which provides the basic building blocks for supporting the Semantic Web.

Table of Contents:

1.	Introduction	3
1.1	Semantic Web	3
1.2	RDF	3
1.2.1	Schema	5
1.2.2	RDF Support in Oracle RDBMS	5
A.	Queries under Oracle	6
1.3	Visualisation of RDF	6
1.3	Goal of this work	6
2.	Implementation	8
2.1	Part I: PL/SQL package for use of Oracle RDF	8
2.1.1	Short instructions for the utilisation of the package RDF TABLE	10
A.	Overview RDF TABLE	10
2.1.2	Details of Implementation	12
A.	The RDF table	12
B.	The model belonging to a table	13
C.	Inserting triples	14
D.	A table for rules	16
E.	Rulebases	19
F.	The rules index	20
G.	Queries	21
2.2	Part II: Connection to the PL/SQL package with Perl	22
2.2.1	Perl package rdfmaker	22
A.	Predefined Queries	24
2.2.2	Details of implementation	24
A.	Connection to a database	24
B.	SQL statements in Perl	25
C.	Converting results to triple format	25
D.	Converting results to XML format	26
E.	An example: Searching coauthors and their publications One example for a query	26
2.3	Part III: GUI written as Java application	27
2.3.1	Instructions for the usage of RdfGui	27
2.3.2	Details of implementation	28
A.	Description of the implemented classes	28
B.	Graphical display of results	29
3.	Conclusions	31
A.	Schema	36
B.	Query	36
B.1	Query: searching for keywords of pub1	36
B.1.0.1	triples format	36
B.1.0.2	xml format	38
4.	References	43

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