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https://github.com/emir-munoz/rosa
RDF and Ontology conStraints Analyzer
https://github.com/emir-munoz/rosa
Last synced: 13 days ago
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RDF and Ontology conStraints Analyzer
- Host: GitHub
- URL: https://github.com/emir-munoz/rosa
- Owner: emir-munoz
- Created: 2015-12-17T18:37:07.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2019-03-31T13:04:33.000Z (almost 6 years ago)
- Last Synced: 2024-11-10T14:13:10.363Z (2 months ago)
- Language: Java
- Homepage: http://emunoz.org/ROSA
- Size: 638 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Welcome to ROSA
ROSA is an **R**DF and **O**ntology con**S**traints **A**nalyzer implemented in Java 8. ROSA aims to mine cardinality bounds from RDF knowledge graphs.
## Pre-requisites
- Java 8
- [Eclipse RDF4J](http://rdf4j.org/) version 2.0M3
- [Apache Jena Fuseki](http://jena.apache.org/) version 2
## ROSA source code management
If you are interested in extending or working directly with the code, you can also check out the master branch from Git.
```bash
git clone https://github.com/emir-munoz/ROSA.git
```
## Compiling from sources
To generate a fat `.jar` with all dependencies,
```bash
mvn clean package -DskipTests
```
## Running project
To execute ROSA on top of Spark using multiple threads in a local machine
**NOTE:** Before start the discovery process, please ensure you have your RDF knowledge graph file in disk or loaded in an Apache Jena Fuseki 2 instance.
### Usage
```bash
[INFO ] 2016-07-18 10:54:56.832 [main] (RosaMain) - [ROSA - RDF and Ontology Constraints Analyser (2016)]
Usage: [options]
Options:
--card
Extraction for cardinality constraints
Default: false
-c, --context
Context of constraints (class or empty)
-e, --endpoint
SPARQL endpoint
-f, --file
Path to RDF file (*.nt, *.nq, *.gz)
-h, --help
Displays this nice help message
Default: false
-m, --method
Outlier detection method
-t, --tval
Deviation factor
-v, --version
Version of the application
Default: false
```
### Discovery of Cardinality Bounds
```bash
$ java -Xmx2g -jar target/ROSA-0.1.0-jar-with-dependencies.jar ` \
--card \
-e [RDF_FILE] \
-c [RDFS/OWL_CLASS] \
-m [OUTLIER_METHOD] \
-t [FACTOR]
```
where:
- `[RDF_FILE]` is the RDF file to analyse,
- `[RDFS/OWL_CLASS]` is the URI of a class used as context,
- `[OUTLIER_METHOD]` is the name of the outlier detection method to use, and
- `[FACTOR]` is a value required by the outlier detection methods.
For example,
```bash
$ java -Xmx2g -jar target/ROSA-0.1.0-jar-with-dependencies.jar --card -e http://localhost:3030/oaei-restaurant1/sparql -c http://www.okkam.org/ontology_restaurant1.owl#Restaurant -m BOXPLOT -t 1.5
```
## Example output
```bash
[INFO ] 2016-07-16 23:32:34.269 [main] (RosaMain) - [ROSA - RDF and Ontology Constraints Analyser (2016)]
[INFO ] 2016-07-16 23:32:34.294 [main] (DiscoveryCardSparql) - Starting discovery of cardinality constraints from RDF data
[INFO ] 2016-07-16 23:32:34.295 [main] (DiscoveryCardSparql) - Context is limited to class 'http://www.okkam.org/ontology_restaurant1.owl#Restaurant'
[INFO ] 2016-07-16 23:32:34.301 [main] (RDFUtil) - Connecting to SPARQL endpoint http://data.neuralnoise.com:3030/oaei-restaurant1/sparql
[INFO ] 2016-07-16 23:32:35.627 [main] (DiscoveryCardSparql) - Querying dataset to get total number of subjects ...
[INFO ] 2016-07-16 23:32:36.303 [main] (DiscoveryCardSparql) - 113 different subjects found in dataset
[INFO ] 2016-07-16 23:32:36.304 [main] (DiscoveryCardSparql) - Querying dataset to get list of predicates ...
[INFO ] 2016-07-16 23:32:36.370 [main] (DiscoveryCardSparql) - 5 predicates found in dataset
[INFO ] 2016-07-16 23:32:36.499 [main] (MemoryUtils) - Used memory: 7.3MB Max available memory: 3,641.0MB
[INFO ] 2016-07-16 23:32:36.500 [main] (DiscoveryCardSparql) - Elapsed time=2113ms
[INFO ] 2016-07-16 23:32:36.500 [main] (DiscoveryCardSparql) - Querying dataset to get cardinality counts of predicate
[INFO ] 2016-07-16 23:32:36.683 [main] (DiscoveryCardSparql) - 113 cardinalities found for
[INFO ] 2016-07-16 23:32:36.693 [main] (NumericOutlierDetector) - Running BOXPLOT outlier detection
[WARN ] 2016-07-16 23:32:36.696 [main] (NumericOutlierDetector) - OutlierRes:{lowerBound=1.0, upperBound=1.0}
[INFO ] 2016-07-16 23:32:36.698 [main] (DiscoveryCardSparql) - predicate=http://www.okkam.org/ontology_restaurant1.owl#has_address has 0 outliers
...
[INFO ] 2016-07-16 23:32:37.345 [main] (DiscoveryCardSparql) - card({},)=(1,1)
[INFO ] 2016-07-16 23:32:37.349 [main] (DiscoveryCardSparql) - card({},)=(1,1)
[INFO ] 2016-07-16 23:32:37.350 [main] (DiscoveryCardSparql) - card({},)=(1,1)
[INFO ] 2016-07-16 23:32:37.359 [main] (DiscoveryCardSparql) - card({},)=(1,1)
[INFO ] 2016-07-16 23:32:37.405 [main] (DiscoveryCardSparql) - card({},)=(1,1)
[INFO ] 2016-07-16 23:32:37.429 [main] (MemoryUtils) - Used memory: 4.8MB Max available memory: 3,641.0MB
[INFO ] 2016-07-16 23:32:37.429 [main] (DiscoveryCardSparql) - Elapsed time=929ms
```
The application takes 929ms and outputs the following cardinality bounds:
- `card({},)=(1,1)`
- `card({},)=(1,1)`
- `card({},)=(1,1)`
- `card({},)=(1,1)`
- `card({},)=(1,1)`
In this specific case, no inconsistencies are found due to the synthetic nature of the dataset. Found inconsistencies in DBpedia dataset are discussed in the paper.
## Contact
[Emir Munoz](http://emunoz.org)
> July 18, 2016