/Mapeathor

Translator of Excel mappings into R2RML, RML or YARRRML

Primary LanguagePythonApache License 2.0Apache-2.0

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workflow

Mapeathor

Mapeathor translates your mapping rules specified in spreadsheets to a mapping language.

Mapeathor is a simple spreadsheet parser able to generate mapping rules in three mapping languages: R2RML, RML (with extension to functions from FnO) and YARRRML. It takes the mapping rules expressed in a spreadsheet and transforms them into the desired language. The spreadsheet template is designed to facilitate the mapping rules' writting, with the aim of being language independent, and thus, lowering the barrier of generating mappings for non-expert users.

workflow

Example:

First Step: Fill the xlsx template with your own information.

The template has five mandatory sheets, Prefixes, Source, Subject PredicateObjectMap and Functions. The last one can be left blank in case there are no functions. The spreadsheet can be in XLSX format or a Google Spreadsheet.

Prefixes:

prefixes

Source:

source

Subject:

subject

PredicateObjectMaps:

pom

Functions:

function

Second Step: Choose the output language that you prefer.

Here you can see the Available Languages.

Third Step: Run Mapeathor:

With python:

# Install
$ python3 -m pip install mapeathor

# How to execute it. You can use a local XLSX file or a shared Google Spreadsheet URL
$ python3 -m mapeathor -i [PATH or URL] -l [RML | R2RML | YARRRML] [-o PATH]

# Help Menu
$ python3 main.py -h

With docker:

# Clone the repository
$ git clone https://github.com/oeg-upm/Mapeathor

# Install the docker image with docker-compose
$ docker-compose up -d

# Copy the XLSX files to data repository
$ cp yourfiles ./data/

# Execute it. You can use a local XLSX file or a shared Google Spreadsheet URL
$ docker exec -it mapeathor ./run.sh [/Mapeathor/data/YOURFILE or URL ] [RML | R2RML | YARRRML] result/outputfile

# Results will appear in result folder

Publications

Iglesias-Molina, A., Chaves-Fraga, D., Priyatna, F., & Corcho, O. (2019). Towards the Definition of a Language-Independent Mapping Template for Knowledge Graph Creation. In Proceedings of the Third International Workshop on Capturing Scientific Knowledge co-located with the 10th International Conference on Knowledge Capture (K-CAP 2019) (pp. 33-36). Online version

Authors and contact