I was try to make an ontology even though haven't finish till now. I used protege for that. I'm used Ontology document for database knowledge representation. actually now i still confused how to linking or connecting my ontology document to database for get the data, because in ontology document i have only knowledge representation not data. if you have advice or solution please tell me, thank you so much.
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I recently came across an application which uses NEO4j as the backend. In my experience with SQL and other Key-value based databases, I have developed an understanding(which could be refined) that other databases store data and your application derives the information while with NEO4J you store the information. This means that the logic of deriving the information is already captured in the model of NEO4J. I am not able to get my head around this because now I cannot have logic that can be composed and most importantly something that can be tested with unit tests. I can sure have component level tests using embedded neo4j but then that's not the same. Can someone please help me understand the application development philosophy/methodology with NEO4J.
...other databases store data and your application derives the information while with NEO4J you store the information.
Hmmm.... Define data and define information. Mostly it goes: Data is something that requires further processing to become information (that is, something informative - something you can derived some conclusion or insights from).
Anyhow, doubt this has anything to do with Graph databases vs relational/aggregate databases. A database, as the name suggests, stores data.
This means that the logic of deriving the information is already captured in the model of NEO4J.
I'm not sure what you mean by "the logic... is already captured". Some queries are much easier with Neo+Cypher that with say SQL; like "Find all the friends of my friends that live in Berlin", but I would hardly relate this to 'logic'.
I cannot have logic that can be composed and most importantly something that can be tested with unit tests.
What do you mean by 'logic that can be composed'? And unit tests has nothing to do with this I'm afraid - there's no logic being tested if you talk about graph vs other databases.
Can someone please help me understand the application development philosophy/methodology with NEO4J.
There's really not much to it. Neo4J is a database like any other database, only that it uses a different model from relational/aggregate databases.
To highlight two of its strengths:
No joins - That's a pain point with relational/aggregate databases, especially with complex queries. Essentially, nearly all system involve a data model that is a graph (you only need one many-to-many relationship in your data model for that), and not using a graph database is a form of dimensionality reduction. The reasons relational databases prevailed for so many years is nothing short of a set of historical coincidences.
Easier DB migrations - and that's for being a schema-less data base. You ripe the same benefits with any other schema-less database.
I strongly recommend you read the 'NOSQL Overview' appendix of the free Graph Databases. It focus on a lot of these points.
I need to import SNOMED CT ontology into a graph database, in this case Neo4J but it could be another choice eventually.
However, I could not find a clear depiction of SNOMED CT underlying relational data model, in order to achieve this. Or at least, simplified SQL views that expose entity relantionship in a way that can be mapped to a graph database.
I would greatly appreciate any guidance or previous experiencies with this matter.
Directly trying to serialise the relational data model is probably going to be quite difficult and will take you further away from your goal.
It is worth noting that SNOMED data is actually available in RDF format already. So you get a graph structure for "free".
For example this project provides the data in a RDF format and putting RDF data into a graph is quite simple regardless of your choice of Titan or Neo4j.
Side Note:
A colleague of mine has actually worked on importing SNOMED data into a Grakn Graph, a semantic graph system we both work on. If you interested you can check out his work here. Grakn is a semantic graph solution which runs on top of Titan.
If you are looking for a sample on how to model the Concepts, Descriptions and Relationships into a Graph database. I have a sample project in Github that can upload the Snomed data into a Neo4j database.
https://github.com/pradeepvemulakonda/Snomed
Before you go into the implementation detail, I would suggest trying out the following Snomed data browser at
http://ontoserver.csiro.au/shrimp/
Once you get a feel of the concepts and relationships you can go through the implementation. You can use the following gist to understand how you can query the uploaded concepts and relationships in Neo4j.
https://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b#listing_category=health-care-and-science
SNOMED can be loaded into MySQL using the UMLS (unified medical language system) released by NIH. Once loaded the table MRREL contains all the relations between SNOMED nodes. If you want load it right away in Neo4j you can totally skip the MySQL step and work directly with the UMLS RRF files. The RRF documentation format is not great but the files are easy to parse tabular text.
There are in fact three tables, Concepts, Descriptions and Relationships
You'll find them described here:
https://confluence.ihtsdotools.org/display/DOCTIG/3.1.+Components
Most important are the relations between Relationships and Concepts and Descriptions and Concepts.
I have a set of football related keywords, a data set of positive sentiments words and negative sentiments words with me. My requirement is to combine these and search is social media to get some real time discussions and posts, and do some statistical analysis and reach some conclusions. This keywords and data sets are dynamically updating one. Now my question is
What is the best practice to handle the three sets of data? Using an Ontology structure or Well structured database?
Whether the data in the ontology is able to access from any programming languages? can i update or retrieve the data in Ontology using .NET or R or with any other programming language?
Thank you
Representing the related keywords as an ontology is a good idea rather than storing in a database.
SPARQL can be used to access and search the ontology to get related information
Your system will be semantically rich if its an ontology
If its a database, may be the access time may be improved but it will not be semantically rich
You may use apache jena which is a free Java API for creating an ontology.
Python also has many plugins for ontology generation.
I have been playing with Neo4J to get a feel on how easy it is to work with related data. so far I have work with the Neo4J community browser to create nodes and build relationship between them.
I have developed an ontology using protege a link!. Now, that I have a huge ontology file(.owl file). I would like to upload it to Neo4J to perform queries and find potential relationships between nodes.
I would be glad if I get any help on this.
Thanks.
Have you seen the blog post by Stefanie Wiegand?
http://blog.neo4j.org/2013/08/and-now-for-something-completely.html
There are also some other users on the Neo4j Google Group who work in ontologies / OWL, perhaps good to cross post there?
There are some more approaches:
http://michaelbloggs.blogspot.de/2013/05/importing-ttl-turtle-ontologies-in-neo4j.html
http://sujitpal.blogspot.de/2009/05/using-neo4j-to-load-and-query-owl.html
I am studying data warehouses and I have to do one final project for my studies.
I am thinking about doing a cube for a data warehouse. Where can I find a real dataset anywhere online that I could try doing a cube with?
You can refer to this page to see how to convert a part of the Northwind database to a star schema for building cubes: Northwind Star Schema.
Here's an example on Adventure Works - of course, it's prebuilt SSAS, but I guess you could look at the underlying AventureWorks DB and do the dimensional modeling yourself.
I think doing a DW on an existing popular dataset like Northwind or AdventureWorks is probably not a great idea, because so many people have done them. Even StackOverflow has had data mining done, but perhaps it would be a good candidate - I'm not sure what Brent's work actually comprised.
So if you are looking to do an original project, you might need to look further afield, if only to distinguish your work from previous work.