I currently have developed a few websites (using Django, Flask, Symfony, etc...). I have also developed Ontologies using semantic software (PoolParty) for enterprise size companies.
I would like to use a small ontology to link data currently in the database of a small website. I do not want it connected to the semantic web. I want to keep all data in relational databases, but link the data with an ontology.
Is there a way to do this? Say if I have a simple flask or django app, is there a way to put an ontology and triplestore on top?
Related
I need your help with the following situation.
I have a local relational database that contains information about several places in a city. These places could be any kind of attraction: Museum, a cathedral, or even a square.
As an example I have information about "Square Victoria" (https://en.wikipedia.org/wiki/Victoria_Square,_Montreal)
A simple search in google gave me the wikipedia URL above. But I want to be able to do it programmatically.
For each place in the database I have also its category (square, museum, church, ....). These categories are local only and do not match any standardized categorization.
My goal is to improve this database by associating each place to its dbpedia URI.
My question is what is the best way to do that? I have some theoretical background about Semantic Web technologies but I don't have yet the practice skills to determine how to do that.
More specific questions:
Is it possible to determine the dbpedia URI using sparql only?
If it is not possible to do it with sparql only, what other technologies would I need to be able to accomplish that?
Thank you
First of all I would recommend, if you have not done it yet, to have a look at wikidata. This project is a semantic extension to wikipedia, but contrary to dbpedia, the data is not extracted from wikipedia, it is created by contributors, and therefore appears (or will appear as the project is still growing) to be more relevant.
The service offers many solutions to access data (including a Sparql endpoint), and it's main advantage is that the underlying software is mediawiki, same used for wikipedia and other Wikimedia foundation projects. The mediawiki API offers an Opensearch option that should allow you to search more efficiently that Sparql queries.
Putting everything together, I think it might be worth having a look at wikidata + wikipedia API to get pivot data to align you local database.
No direct answer but I hope that will help.
I'm trying to create a SPARQL endpoint based on Sesame. I installed Tomcat, PostgreSQL, and deployed a Sesame's web application. I created a repository based on PostgreSQL RDF store. Now i need to load a big ttl file (540M triples, file size is several GB) into a repository. Loading a big file over Workbench is not a good solution - it will take several days. What is the best non-programming solution to load the data? Are there tools like "console" to load data? For example, Virtuoso has isql tool for bulk loading...
There is no ready-made bulk loading tool available for Sesame that I am aware of - though Sesame-compatible triplestore vendors do have such tooling available as part of their specific database. Programming a bulk-upload solution is not particularly hard, but we somehow never got around to including such a tool in the Sesame core distribution.
540M triples, by the way, is probably too large for any of Sesame's default stores - the Native Store only scales to about 150M, and loading such a large dataset into the memory store is just too unwieldy (even if you had the available RAM). So you probably need to look into using a Sesame-compatible database provided by a third party. There are many choices available, both commercial and free/open-source, see this overview on the Sesame website for a list of some suggestions.
We are actually creating a website with some comunity elements. We choose django as programming language. We'd like to keep the website multilingual.
We already created some apps and website, but kept them static and singlle-language. I read about 2 approaches to create a multilingual website. The first is to keep the translations in a database. This should be the easiest way, but way to unefficient and with an ordinary performance. I also read about setting up a xml translation file, where you can store every single translation.
I'd like to know the differences in performance and the advantage or disadvantages of these approaches. Is there any efficient way in django to keep my website multi-language?
Django has good built in support for multiple languages based on GNU gettext.
Unfortunately, the support is limited to text that you know in advanced, which is good enough for your UI, but if you have users creating content in multiple languages, it will not be enough, and you'll have to deal with it yourself in the database.
I am developing a demo of semantic web-based Information System, which just uses SPARQL instead of traditional SQL to manipulate dataset. How the application can demonstrate Semantic Web benefits.
I did steps as below:
The client gets parameters from web UI.
Requests a web service.
The service generates a SPARQL command according to given parameters.
The service uses Jena/SDB API to execute the SPARQL command.
Retrieves or persists data from or to MySQL.
Parsing returned result set.
Responses a JSON object to the client.
The client uses Javascript + html to display data.
Currently, the application just has CRUD operations. Only one difference to the traditional IS, which is using SPARQL instead of SQL. It seems that cannot see obviously semantic features. I'm just thinking of two points:
To demonstrate data federating through SPARQL. From this point, can I imagine that the system can be broken down into several subsystem and work on their independent dataset but they can communicate with each other by SPARQL, which because they work on the RDF specification.
Reasoning over datasets. I use Ontologies to describe data schema, should my reasoning operation need to based on them. In my application, I try to get a RDF model, and use Pellet to do inferences. Is that corrent way?
Basically, if the application can demostrate data federating and reasoning, which can be seen as a semantic web-based application. Do I understand it right?
Hopefully, the application can combine services together automatically through semantic description. Furthermore, any other third party data sources may be communicate with the system and work immediately.
Yes ,you are right.the benefit with semantic web being you can write separate set of ontologies which will describe the domains(e.g. product,user) and then combine them using inference ,reasoning and make the data seem much more useful(r.g. product types and user preferences).
The difference being the rules for the data are now written with the data and not in the business logic layer.
Hope this helps .:)
Although i have a little bit of experience in developing dynamic websites using ASP technologies, but I am new to semantic web programming, and i intend to implement a website based on semantic web technology.I would like to develop a search engine, where a web user can query for keywords from the backend RDF triple store.I want to implement the website using Java and JSP.I have following questions:
I am currently studying Jena framework and SPARQL to start with,but
i am not sure what other technologies i need to study in order to
implement the website.
What is the difference between RDF and OWL, I have gone through a
lot of web resources but i am still confused.As per my understanding
RDF and OWL both define relationship between concepts but OWL is
more rich in terms of defining relations.
What is meant by different OWL Vocabularies like FOAF, SIOC etc.Why
do we need these vocabularies?
What exactly is the purpose of Virtuso Open Link
Software(http://ods.openlinksw.com/dataspace/dav/wiki/Main/VirtJenaProvider)
Any help would be highly appreciated.
Thanks!
I would definitely like to be kept up to date of your progress. I'm not experienced with java or jsp. I wonder if this could be done in php? I know that some work has been done in python on this kind of thing.
There are some extensions to drupal that work with these semantic web technologies and Semantic Media Wiki is good too.
Check out this and the related links at the bottom. The difference between microformats and vocabularies can be difficult to understand but I think there is a difference, say between a vocabulary like FOAF and a microformat like hCard, hCalendar or hResume. Oh, the link:
http://en.wikipedia.org/wiki/FOAF_(software)
Anyway these related terms are included.
Thanks,
Bruce
http://futurewavedesigns.com
Re: your first question - why do you want to use RDF to implement a keyword search? Keyword search isn't semantic, and there are many established frameworks and APIs for keyword search, such as Lucene.
Re: your second question, comparing RDF and OWL is comparing apples and oranges. RDF is basically for declaring data, but OWL is a layer on top of RDF that is for declaring ontologies (schemas). A more meaningful comparison would be between RDFS (RDF Schema) and OWL, which both address the ontology layer.
Example:
In RDF you might state that John Smith is a Person who hasAge "42" and is marriedTo Jill Smith.
In RDFS or OWL you would declare that Person is a class, hasAge is a property (with domain of Person and range of xsd:integer) and marriedTo is a property (with domain and range of Person).
In OWL you can also declare that marriedTo is a symmetric property (if A is marriedTo B, then B must be marriedTo A). RDF isn't this powerful, so you can't make this particular statement, so can't make inferences about symmetric properties etc.