be.ugent.rml:rmlmapper
Advanced tools
The RMLMapper executes RML rules to generate high quality Linked Data from multiple originally (semi-)structured data sources.
The RMLMapper executes RML rules to generate Linked Data. It is a Java library, which is available via the command line (API docs online). The RMLMapper loads all data in memory, so be aware when working with big datasets.
Want to get started quickly? Check out Releases on where to find the latest CLI build as a jar, and see Usage on how to use the commandline interface!
@ can be used to select the current object.))The standalone jar file (that has a commandline interface) for every release can be found on the release's page on GitHub. You can find the latest release here. This is the recommended way to get started with RMLMapper. Do you want to build from source yourself? Check Build.
The RMLMapper is built using Maven.
As it is also tested against Oracle (check here for details),
it needs a specific set-up to run all tests.
That's why we recommend to build without testing: mvn install -DskipTests=true.
If you want, you can install with tests, and just skip the Oracle tests: mvn test -Dtest=!Mapper_OracleDB_Test.
A standalone jar can be found in /target.
Two jars are found in /target: a slim jar without bundled dependencies, and a standalone jar (suffixed with -all.jar) with all dependencies bundled.
Building with profile no-buildnumber disables using and updating buildNumber.properties (and uses 0 as build number), e.g.:
mvn clean package -P no-buildnumber
outputs for example target/rmlmapper-<version>-r0.jar
The following options are most common.
-m, --mapping <arg>: one or more mapping file paths and/or strings (multiple values are concatenated).-o, --output <arg>: path to output file-s,--serialization <arg>: serialization format (nquads (default), trig, trix, jsonld, hdt)All options can be found when executing java -jar rmlmapper.jar --help,
that output is found below.
usage: java -jar mapper.jar <options>
options:
-b,--base-iri <arg> Base IRI used to expand relative IRIs
in generated terms in the output.
-c,--configfile <arg> path to configuration file
-d,--duplicates remove duplicates in the HDT,
N-Triples, or N-Quads output
--disable-automatic-eof-marker Setting this option assumes input
data has a kind of End-of-File
marker. Don't use unless you're
absolutely sure what you're doing!
-dsn,--r2rml-jdbcDSN <arg> DSN of the database when using R2RML
rules
-e,--metadatafile <arg> path to output metadata file
-f,--functionfile <arg> one or more function file paths
(dynamic functions with relative
paths are found relative to the cwd)
-h,--help show help info
-l,--metadataDetailLevel <arg> generate metadata on given detail
level (dataset - triple - term)
-m,--mappingfile <arg> one or more mapping file paths and/or
strings (multiple values are
concatenated). r2rml is converted to
rml if needed using the r2rml
arguments.RDF Format is determined
based on extension.
-o,--outputfile <arg> path to output file (default: stdout)
-p,--r2rml-password <arg> password of the database when using
R2RML rules
-psd,--privatesecuritydata <arg> one or more private security files
containing all private security
information such as usernames,
passwords, certificates, etc.
-s,--serialization <arg> serialization format (nquads
(default), turtle, trig, trix,
jsonld, hdt)
--strict Enable strict mode. In strict mode,
the mapper will fail on invalid IRIs
instead of skipping them.
-t,--triplesmaps <arg> IRIs of the triplesmaps that should
be executed in order, split by ','
(default is all triplesmaps)
-u,--r2rml-username <arg> username of the database when using
R2RML rules
-v,--verbose show more details in debugging output
The W3C Web of Things Security Ontology
is used to describe how Web APIs authentication should be performed
but does not include the necessary credentials to access the Web API.
These credentials can be supplied using the -psd <PATH> CLI argument.
The PATH argument must point to one or more private security files
which contain the necessary credentials to access the Web API.
An example can be found in the test cases src/test/resources/web-of-things.
An example of how you can use the RMLMapper as an external library can be found at ./src/test/java/be/ugent/rml/readme/ReadmeTest.java
We publish our Docker images automatically on Dockerhub for every release. You can find our images here: rmlio/rmlmapper-java.
You can use Docker to run the RMLMapper by following these steps:
docker build -t rmlmapper ..docker run --rm -v $(pwd):/data rmlmapper -m mapping.ttl.The same parameters are available as via the CLI.
The RMLMapper is executed in the /data folder in the Docker container.
There are three ways to include (new) functions within the RML Mapper
Registration of functions is done using a Turtle file, which you can find in src/main/resources/functions.ttl
Create a Turtle file that describe the functions that need to be included and add the jar which contains those functions.
Note: the java or jar-files are found relative to the cwd. You can change the functions.ttl path (or use multiple functions.ttl paths) using a commandline-option (
-f).
For example the snippets below dynamically link an fno:Function to a library, provided by a jar-file (CustomFunctions.jar). The example links a function that parses the latitude (50.2) out of the following string "POINT (50.2 5.3)".
functions.ttl contains the description of the function in Turtle:
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix doap: <http://usefulinc.com/ns/doap#> .
@prefix fno: <https://w3id.org/function/ontology#> .
@prefix fnoi: <https://w3id.org/function/vocabulary/implementation#> .
@prefix fnom: <https://w3id.org/function/vocabulary/mapping#> .
@prefix grel: <http://users.ugent.be/~bjdmeest/function/grel.ttl#> .
@prefix grelm: <http://fno.io/grel/rmlmapping#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
grel:parsePointLat a fno:Function ;
fno:name "parsePointLat" ;
rdfs:label "parsePointLat" ;
dcterms:description "Parse the latitude from a point." ;
fno:expects ( grel:valueParam ) ;
fno:returns ( grel:stringOut ) .
grelm:javaString
a fnoi:JavaClass ;
doap:download-page "CustomFunctions.jar" ;
fnoi:class-name "CustomFunctions" .
grelm:parsePointLat
a fno:Mapping ;
fno:function grel:parsePointLat ;
fno:implementation grelm:javaString ;
fno:methodMapping [ a fnom:Function ;
fnom:method-name "parsePointLat" ] .
The accompanying java file CustomFunctions.java:
public class CustomFunctions {
public static String parsePointLat(String s) {
return s.replace("POINT ", "").replace('(', ' ').replace(')', ' ').trim().split("\\s+")[0];
}
}
To dynamically include the custom function, compile the java-file and include functions.ttl with the -f option:
javac CustomFunctions.java && jar cvf CustomFunctions.jar CustomFunctions.class
java -jar mapper.jar -f functions.ttl <other options>
This overrides the dynamic loading. An example of how you can use Preload a custom function can be found at ./src/test/java/be/ugent/rml/readme/ReadmeFunctionTest.java
This is most interesting if you use RMLMapper as a library in your own project. Just add the dependency to the function library you want to use in your project.
You can also add a function library as a Maven dependency in pom.xml of RMLMapper.
You'll have to rebuild RMLMapper to use it.
Conform to how it is described in the scientific paper [1], the RMLMapper allows to automatically generate PROV-O metadata. Specifically, you need the CLI arguments below. You can specify in which output file the metadata should be stored, and up to which level metadata should be stored (dataset, triple, or term level metadata).
-e,--metadatafile <arg> path to output metadata file
-l,--metadataDetailLevel <arg> generate metadata on given detail level
(dataset - triple - term)
Run the tests via test.sh.
Right-click src/test/java directory and select "Run 'All tests'".
Some tests (Excel, ODS) are derived from other tests (CSV) using a script (./generate_spreadsheet_test_cases.sh)
Make sure you have Docker running. On Unix, others read-write permission (006) is required on /var/run/docker.sock in order to run the tests.
The tests will fail otherwise, as Testcontainers can't spin up the container.
| Dependency | License |
|---|---|
| ch.qos.logback logback-classic | Eclipse Public License 1.0 & GNU Lesser General Public License 2.1 |
| com.github.fnoio function-agent-java | MIT |
| com.github.fnoio grel-functions-java | MIT |
| com.github.fnoio idlab-functions-java | MIT |
| com.github.rdfhdt hdt-java | GNU Lesser General Public License v3.0 |
| com.github.tomakehurst:wiremock-jre8 | Apache License 2.0 |
| com.microsoft.sqlserver mssql-jdbc | MIT |
| com.mysql mysql-connector-java | GNU General Public License v2.0 |
| com.oracle.database.jdbc:ojdbc11 | Oracle Free Use Terms and Conditions |
| net.minidev json-smart | Apache License 2.0 |
| org.apache.jena fuseki-main | Apache License 2.0 |
| org.eclipse.rdf4j rdf4j-client | Eclipse Distribution License v1.0 |
| org.junit.jupiter junit-jupiter-api | Eclipse Public License v2.0 |
| org.junit.jupiter junit-jupiter-engine | Eclipse Public License v2.0 |
| org.junit.jupiter junit-jupiter-params | Eclipse Public License v2.0 |
| org.junit.vintage junit-vintage-engine | Eclipse Public License v2.0 |
| org.postgresql postgresql | BSD |
| org.testcontainers jdbc | MIT |
| org.testcontainers junit-jupiter | MIT |
| org.testcontainers mssqlserver | MIT |
| org.testcontainers mysql | MIT |
| org.testcontainers oracle-xe | MIT |
| org.testcontainers postgresql | MIT |
Do you need...
You're welcome to contact us regarding on-premise, enterprise, and internal installations, integrations, and deployments.
We have commercial support available.
We also offer consulting for all-things-RML.
All spreadsheet files are as of yet regarded as plain CSV files. No type information like Currency, Date... is used.
The RMLMapper's XML parsing implementation (javax.xml.parsers) has been chosen to support full XPath.
This implementation causes a large memory consumption (up to ten times larger than the original XML file size).
However, the RMLMapper can be easily adapted to use a different XML parsing implementation that might be better suited for a specific use case.
The processor checks whether correct language tags are not, using a regular expression. The regex has no support for languages of length 5-8, but this currently only applies to 'qaa..qtz'.
Performance depends on the serialization format (--serialization <format>)
and if duplicate removal is enabled (--duplicates).
Experimenting with various configurations may lead to better performance for
your use case.
Do you have any question related to writing RML mapping rules, the RML specification, etc., feel free to ask them here: https://github.com/kg-construct/rml-questions ! If you have found a bug or need a feature for the RMLMapper itself, you can make an issue in this repository.
Generate static files at /docs/apidocs with:
mvn javadoc:javadoc
(Requires Ultimate edition)
[1]: A. Dimou, T. De Nies, R. Verborgh, E. Mannens, P. Mechant, and R. Van de Walle, “Automated metadata generation for linked data generation and publishing workflows,” in Proceedings of the 9th Workshop on Linked Data on the Web, Montreal, Canada, 2016, pp. 1–10. PDF
FAQs
The RMLMapper executes RML rules to generate high quality Linked Data from multiple originally (semi-)structured data sources.
We found that be.ugent.rml:rmlmapper demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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