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# OntoUML/UFO Catalog Python Library
<p align="center"><img src="https://raw.githubusercontent.com/OntoUML/ontouml-models-lib/main/resources/ontouml-models-lib-logo.png" width="500"></p>
<!-- TOC -->
* [OntoUML/UFO Catalog Python Library](#ontoumlufo-catalog-python-library)
* [Overview](#overview)
* [About the OntoUML/UFO Catalog](#about-the-ontoumlufo-catalog)
* [Features](#features)
* [Installation](#installation)
* [The Library's Classes](#the-librarys-classes)
* [Examples](#examples)
* [Example 1: Working with the Catalog Class](#example-1-working-with-the-catalog-class)
* [Example 2: Working with the Model Class](#example-2-working-with-the-model-class)
* [Example 3: Working with the Query Class](#example-3-working-with-the-query-class)
* [How to Contribute](#how-to-contribute)
* [Reporting Issues](#reporting-issues)
* [Code Contributions](#code-contributions)
* [Test Contributions](#test-contributions)
* [General Guidelines](#general-guidelines)
* [License](#license)
* [Author](#author)
<!-- TOC -->
## Overview
This Python library provides tools for manipulating and querying ontology models within the OntoUML/UFO framework. It is designed to work with concepts and models that adhere to the standards and practices outlined in the OntoUML/UFO Catalog. The library supports operations on models stored in machine-readable formats such as JSON and Turtle, and enables the execution of SPARQL queries on these models.
## About the OntoUML/UFO Catalog
The [FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research](https://github.com/OntoUML/ontouml-models), also known as **OntoUML/UFO Catalog**, is a structured and open-source repository containing a collection of OntoUML and UFO ontology models. The catalog is designed to support empirical research in OntoUML and UFO, as well as the broader field of conceptual modeling. It provides a diverse range of models created by modelers with varying expertise, covering multiple domains and purposes. These models are available in machine-readable formats such as JSON and Turtle, which facilitate automated processing and querying. Each model in the catalog is accessible via a permanent identifier, ensuring long-term availability and reference.
The catalog organizes its content into a well-defined structure, storing models and their metadata in linked data formats. This structure allows for the integration of the models into a knowledge graph, enabling advanced querying and analysis using SPARQL. The OntoUML/UFO Catalog is built to be collaborative and accessible, allowing users to contribute to and leverage a comprehensive resource for conceptual modeling research. For more details, please visit the official OntoUML/UFO Catalog repository: [OntoUML/UFO Catalog](https://github.com/OntoUML/ontouml-models).
## Features
- **Catalog Management:** Load, manage, and query collections of ontology models.
- **Model Interaction:** Interact with individual ontology models, including querying and metadata management.
- **SPARQL Query Execution:** Execute SPARQL queries on RDF graphs representing ontology models.
- **Metadata Handling:** Support for metadata schemas used in the OntoUML/UFO Catalog, ensuring consistency and compliance with the catalog's structure.
## Installation
To install the library, use pip:
```bash
pip install ontouml-models-lib
```
## The Library's Classes
The `Catalog`, `Model`, and `Query` classes are core components of the OntoUML/UFO Catalog Python library, designed to enable manipulation and querying of ontology models. The `Catalog` class is used to manage collections of ontology models, allowing users to load, query, and interact with multiple models as a cohesive unit. The `Model` class represents an individual ontology model, providing methods for querying its RDF graph and accessing metadata. The `Query` class encapsulates SPARQL queries, enabling their execution on RDF graphs within the OntoUML/UFO framework.
These classes are essential when working with the OntoUML/UFO Catalog, which is a repository of high-quality, curated ontology models. Users can utilize the `Catalog` class to manage entire collections of models, the `Model` class to interact with individual models, and the `Query` class to run specific queries on the data. This design ensures that users can efficiently organize, access, and analyze ontology models in a standardized way.
### Examples
#### Example 1: Working with the Catalog Class
```python
from ontouml_models_lib import Catalog
## Load a catalog from a specified path
catalog = Catalog('/path/to/catalog')
## List all models in the catalog
models = catalog.list_models()
print(models)
## Perform a query across all models in the catalog
query = Query('/path/to/query.sparql')
results = catalog.execute_query(query)
print(results)
```
#### Example 2: Working with the Model Class
```python
from ontouml_models_lib import Model, Query
## Load an individual ontology model
model = Model('/path/to/ontology_model_folder')
## Print the title of the model
print(model.title)
## Execute a SPARQL query on the model
query = Query('/path/to/query.sparql')
results = model.execute_query(query)
print(results)
```
#### Example 3: Working with the Query Class
```python
from ontouml_models_lib import Query
## Load a SPARQL query from a file
query = Query('/path/to/query.sparql')
## Access the query content
print(query.query_content)
## Compute the hash of the query (useful for caching results)
print(query.hash)
```
## How to Contribute
We welcome and appreciate contributions from the community! Whether you want to report a bug, suggest a new feature, or improve our codebase, your input is valuable.
### Reporting Issues
- If you find a bug or wish to suggest a feature, please [open a new issue](https://github.com/OntoUML/ontouml-models-lib/issues/new).
- If you notice any discrepancies in the documentation created with the aid of AI, feel free to [report them by opening an issue](https://github.com/OntoUML/ontouml-models-lib/issues/new).
### Code Contributions
1. Fork the project repository and create a new feature branch for your work: `git checkout -b feature/YourFeatureName`.
2. Make and commit your changes with descriptive commit messages.
3. Push your work back up to your fork: `git push origin feature/YourFeatureName`.
4. Submit a pull request to propose merging your feature branch into the main project repository.
### Test Contributions
- Enhance the project's reliability by adding new tests or improving existing ones.
### General Guidelines
- Ensure your code follows our coding standards.
- Update the documentation as necessary.
- Make sure your contributions do not introduce new issues.
We appreciate your time and expertise in contributing to this project!
## License
This library is licensed under the [Creative Commons Attribution-ShareAlike 4.0 International Public License](https://creativecommons.org/licenses/by-sa/4.0/). Please note that the models included in the OntoUML/UFO Catalog may have their own licenses, as specified in their metadata.
## Author
The ontouml-models-lib library is developed and maintained by:
- Pedro Paulo Favato Barcelos [[GitHub](https://github.com/pedropaulofb)] [[LinkedIn](https://www.linkedin.com/in/pedro-paulo-favato-barcelos/)]
Feel free to reach out using the provided links. For inquiries, contributions, or to report any issues, you can [open a new issue](https://github.com/OntoUML/ontouml-models-lib/issues/new) on this repository.
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"description": "[](https://doi.org/10.5281/zenodo.10211480)\n[](https://www.repostatus.org/#active)\n\n\n\n\n\n\n\n\n\n\n[](https://github.com/pre-commit/pre-commit)\n\n\n[//]: # ([](https://results.pre-commit.ci/latest/github/OntoUML/ontouml-models-lib/main))\n[//]: # ()\n[//]: # ([](https://www.bestpractices.dev/projects/8328))\n[//]: # ()\n\n# OntoUML/UFO Catalog Python Library\n\n<p align=\"center\"><img src=\"https://raw.githubusercontent.com/OntoUML/ontouml-models-lib/main/resources/ontouml-models-lib-logo.png\" width=\"500\"></p>\n\n<!-- TOC -->\n* [OntoUML/UFO Catalog Python Library](#ontoumlufo-catalog-python-library)\n * [Overview](#overview)\n * [About the OntoUML/UFO Catalog](#about-the-ontoumlufo-catalog)\n * [Features](#features)\n * [Installation](#installation)\n * [The Library's Classes](#the-librarys-classes)\n * [Examples](#examples)\n * [Example 1: Working with the Catalog Class](#example-1-working-with-the-catalog-class)\n * [Example 2: Working with the Model Class](#example-2-working-with-the-model-class)\n * [Example 3: Working with the Query Class](#example-3-working-with-the-query-class)\n * [How to Contribute](#how-to-contribute)\n * [Reporting Issues](#reporting-issues)\n * [Code Contributions](#code-contributions)\n * [Test Contributions](#test-contributions)\n * [General Guidelines](#general-guidelines)\n * [License](#license)\n * [Author](#author)\n<!-- TOC -->\n\n## Overview\n\nThis Python library provides tools for manipulating and querying ontology models within the OntoUML/UFO framework. It is designed to work with concepts and models that adhere to the standards and practices outlined in the OntoUML/UFO Catalog. The library supports operations on models stored in machine-readable formats such as JSON and Turtle, and enables the execution of SPARQL queries on these models.\n\n## About the OntoUML/UFO Catalog\n\nThe [FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research](https://github.com/OntoUML/ontouml-models), also known as **OntoUML/UFO Catalog**, is a structured and open-source repository containing a collection of OntoUML and UFO ontology models. The catalog is designed to support empirical research in OntoUML and UFO, as well as the broader field of conceptual modeling. It provides a diverse range of models created by modelers with varying expertise, covering multiple domains and purposes. These models are available in machine-readable formats such as JSON and Turtle, which facilitate automated processing and querying. Each model in the catalog is accessible via a permanent identifier, ensuring long-term availability and reference.\n\nThe catalog organizes its content into a well-defined structure, storing models and their metadata in linked data formats. This structure allows for the integration of the models into a knowledge graph, enabling advanced querying and analysis using SPARQL. The OntoUML/UFO Catalog is built to be collaborative and accessible, allowing users to contribute to and leverage a comprehensive resource for conceptual modeling research. For more details, please visit the official OntoUML/UFO Catalog repository: [OntoUML/UFO Catalog](https://github.com/OntoUML/ontouml-models).\n\n\n## Features\n\n- **Catalog Management:** Load, manage, and query collections of ontology models.\n- **Model Interaction:** Interact with individual ontology models, including querying and metadata management.\n- **SPARQL Query Execution:** Execute SPARQL queries on RDF graphs representing ontology models.\n- **Metadata Handling:** Support for metadata schemas used in the OntoUML/UFO Catalog, ensuring consistency and compliance with the catalog's structure.\n\n## Installation\n\nTo install the library, use pip:\n\n```bash\npip install ontouml-models-lib\n```\n\n## The Library's Classes\n\nThe `Catalog`, `Model`, and `Query` classes are core components of the OntoUML/UFO Catalog Python library, designed to enable manipulation and querying of ontology models. The `Catalog` class is used to manage collections of ontology models, allowing users to load, query, and interact with multiple models as a cohesive unit. The `Model` class represents an individual ontology model, providing methods for querying its RDF graph and accessing metadata. The `Query` class encapsulates SPARQL queries, enabling their execution on RDF graphs within the OntoUML/UFO framework.\n\nThese classes are essential when working with the OntoUML/UFO Catalog, which is a repository of high-quality, curated ontology models. Users can utilize the `Catalog` class to manage entire collections of models, the `Model` class to interact with individual models, and the `Query` class to run specific queries on the data. This design ensures that users can efficiently organize, access, and analyze ontology models in a standardized way.\n\n### Examples\n\n#### Example 1: Working with the Catalog Class\n\n```python\nfrom ontouml_models_lib import Catalog\n\n## Load a catalog from a specified path\ncatalog = Catalog('/path/to/catalog')\n\n## List all models in the catalog\nmodels = catalog.list_models()\nprint(models)\n\n## Perform a query across all models in the catalog\nquery = Query('/path/to/query.sparql')\nresults = catalog.execute_query(query)\nprint(results)\n```\n\n#### Example 2: Working with the Model Class\n\n```python\nfrom ontouml_models_lib import Model, Query\n\n## Load an individual ontology model\nmodel = Model('/path/to/ontology_model_folder')\n\n## Print the title of the model\nprint(model.title)\n\n## Execute a SPARQL query on the model\nquery = Query('/path/to/query.sparql')\nresults = model.execute_query(query)\nprint(results)\n```\n\n#### Example 3: Working with the Query Class\n\n```python\nfrom ontouml_models_lib import Query\n\n## Load a SPARQL query from a file\nquery = Query('/path/to/query.sparql')\n\n## Access the query content\nprint(query.query_content)\n\n## Compute the hash of the query (useful for caching results)\nprint(query.hash)\n```\n\n\n\n## How to Contribute\n\nWe welcome and appreciate contributions from the community! Whether you want to report a bug, suggest a new feature, or improve our codebase, your input is valuable.\n\n### Reporting Issues\n\n- If you find a bug or wish to suggest a feature, please [open a new issue](https://github.com/OntoUML/ontouml-models-lib/issues/new).\n- If you notice any discrepancies in the documentation created with the aid of AI, feel free to [report them by opening an issue](https://github.com/OntoUML/ontouml-models-lib/issues/new).\n\n### Code Contributions\n\n1. Fork the project repository and create a new feature branch for your work: `git checkout -b feature/YourFeatureName`.\n2. Make and commit your changes with descriptive commit messages.\n3. Push your work back up to your fork: `git push origin feature/YourFeatureName`.\n4. 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