https://github.com/kit-data-manager/fair-digital-object-client-framework-implementation
A reference implementation for the FDO-Client Framework
https://github.com/kit-data-manager/fair-digital-object-client-framework-implementation
Last synced: 8 months ago
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A reference implementation for the FDO-Client Framework
- Host: GitHub
- URL: https://github.com/kit-data-manager/fair-digital-object-client-framework-implementation
- Owner: kit-data-manager
- Created: 2023-12-07T16:19:07.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-18T14:08:35.000Z (over 2 years ago)
- Last Synced: 2025-10-10T01:33:30.281Z (8 months ago)
- Language: Python
- Size: 19.9 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Flask-Based Web Application for a FAIR Digtial Object and graph-based Client Framework
## Overview
This web application is built using Flask and integrates various backend services for data processing and interaction with FAIR Digital Object (FDO) services, mainly a Typed PID Maker (TPM), and a graph database. It is designed for complex data and algorithm management tasks, including SPARQL querying, FDO kernel validation and evaluation, operation execution, and local data handling.
## Components
### Python Modules
- `user_interface.py`: Manages the web interface, processes user requests, and renders HTML templates.
- `sparql_service.py`: Executes and constructs SPARQL queries.
- `query_processing.py`: Restructures SPARQL query results.
- `tpm_interface.py`: Manages interactions with the TPM service and SSH connections to retrieve PID records of FDOs. Provides alternatively access to locally stored JSON records of PIDs.
- `kernel_workflow.py`: Handles data validation against predefined key-value pairs and data record keys.
- `record_mapper.py`: Maps records to requests and processes JSON-like strings.
- `ops_executor.py`: Executes operation requests via HTTP and processes responses.
### HTML Templates
- `submit_sparql.html`: For submitting terms for pre-defined SPARQL queries in the `sparql_service.py` module.
- `select_attributes.html`: For selecting operations associated with attributes based on queries.
- `select_profiles.html`: For selecting operations associated with profiles based on queries.
- `display_response.html`: For displaying operation results, including local storage directory.
### Configuration Files
- `services.json`: Configuration for the graph database and TPM.
- `tpm_keys_config_path.json`: Key mappings for operation access protocols.
### Example Operations
- `example_operations/dh_api.py`: Provides API endpoints for operations related to an exemplary application case of training data composition for ontology matching in Digital Humanities.
- `example_operations/mri_api.py`: Provides API endpoints for operations related to an exemplary application case of training data composition for image classification in Material Sciences.
## User Guide
### Setting Up
1. **Configure** the application using `services.json`, i.e., provide the endoint to the FDO graph-database, as well as the TPM instance or alternatively the local JSON records, and `tpm_keys_config_path.json`, i.e., provide the PIDs according to the Data Type Registry entries used to create the FDOs.
2. **Run** the Flask server via `user_interface.py`.
### Using the Application
1. **Submit SPARQL Queries**: Access the `submit_sparql.html` form, choose a query type, enter values, and submit.
2. **Select Profiles or Attributes**: Use the `select_profiles.html` or `select_attributes.html` templates to make selections for operations and resulting output types based on query results.
3. **View Operation Results**: Results and details of operations are displayed on `display_response.html`.
### Technical Aspects
- **Data Validation**: Validates data records against TPM keys with various checks for accessibility, up-to-dateness, checksum inetgrity, and lisence reusability for digital objects.
- **SPARQL Querying**: Executes and constructs queries for data retrieval.
- **Operation Execution**: Manages the execution of TPM-defined operations.
### Walking Example
- An example for a query selection and query request for a profile:
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- Query result listing operations, output types and number of associated FDOs for the profile:
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- Display of an operation result triggered by the previous request and displaying the number of processed data objects and the results storage folder, as well as the option to request a new query:
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- A query selection and query request for an attribute which is the output type of the previous operation result:
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- Query result listing operations and output types for the attribute:
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- An operation result of an attribute using the content of the resutls directory from the previous operation:
