Semantic Web

How to store ontologies in a relational database?

The Semantic Web brings closer to realization the possibility of semantically organized data repositories, or ontologies, throughout the Internet that can be used for intelligent information searching both by humans and computational agents. Ontologies are important to application integration solutions. However, while today there is an un-precedented wealth of information available on the Web, to fully realize the power of ontologies and to enable efficient and flexible information gathering, persistent storage of ontologies and its subsequent retrieval is of paramount importance. Therefore, storing ontologies in a relational database is one way to get around this problem.

Using RDF(S) without XML.

RDF can be written in some ways: A RDF triple could be represented through a RDF graph, through FOL expressions like P(X,Y), or - most common used for web development - through XML. There are some good RDF/XML parsers for the most common web development languages like Perl or Python. But is there another way of writing RDF, which is supported by a parser for programming/script languages?

Which semantic web technology tools are preferred/best for ontology development and reasoning?

How do we choose ontology editors and reasoners to develop ontologies for the semantic web? To date, there are a certain number of ontology editors and reasoners available but which ones to use is still a question to be addressed. Choosing the best from the available tools facilitates work and also enhances efficiency.

rdf resource declaration

Data in the file is not written in the same order in which I need to process them. So my question is, whether should be all properties of one resource declared at one place (in one description tag) and thus whole file processed at once and only then created rdf. Or whether it is possible to add properties to previously declared resource anywhere in document during data processing?


Make Databases accessible for the Semantic Web

Besides (re)creating data manually, automatic generation or extraction of information already there is a possibility. One more specific possibility are databases which already contain huge amount of highly structured data (for example content management systems or the so called deep web). But how can we make this data part of the semantic web?

What's a proper programming language for Semantic Web reasoning?

As I already mentioned, the internet is one big database. But how much is the information worth? Obviously not all the information on the internet is true and not all information is worth to be taken into consideration by solving problems. As I see it, the Semantic Web is still in its child shoes. New technologies and ideas come up, each and every day. The progress of structuring date using W3C recommendations has just begun. That allows to make more and more data being read- and understoodable by machines. But in the end, intelligent software (e.g. agents) has to do some kind of reasoning to solve their given problems. The software has to decide on its own, which information is worth to be taken into consideration and which information isn't. Moreover, the software has to decide how to use the given data. Logic Programming is one way to go. Lot's of (semantic web related) artificial intelligent and search problems could be solved by Logic Programming technologies such as Answer Set Programming (ASP). The simpleness and elegancy of ASP may perfectly fit to Semantic Web tasks, such as information collection and interpretation from standardized Semantic Web knowledge bases or intelligent software design. Does there already exist some languages that fulfills this description? Does there exist logic programming languages that are able to be used with modern Semantic Web technologies, such as XML, RDF and OWL? Yes it does.....


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