Metadata-Version: 2.4
Name: InteroperabilityEnabler
Version: 0.1.0
Summary: Interoperability Enabler
Home-page: https://github.com/Sedimark/InteroperabilityEnabler
Author: Shahin ABDOUL SOUKOUR
Author-email: abdoul-shahin.abdoul-soukour@inria.fr
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: python-dateutil
Requires-Dist: pytz
Requires-Dist: six
Requires-Dist: tzdata
Requires-Dist: xlrd
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: provides-extra
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

## What is it?

Interoperability Enabler (IE) component is designed to facilitate seamless integration and interaction among various artefacts within the SEDIMARK ecosystem, including data, AI models, and service offerings.


## Key Feature

- Data Formatter - Convert data from various formats into the SEDIMARK internal processing format (pandas DataFrames)
- Data Quality Annotation - Enable adding any kind of quality annotations to data inside pandas DataFrames
- Data Mapper – Convert data from pandas DataFrames into NGSI-LD json
- Data Extractor – Extract relevant data from a pandas DataFrame
- Data Merger – Restore metadata to a pandas DataFrame
- Metadata Restorer – Merge two DataFrames by matching column names

## Installation

The source code can be found on GitHub at https://github.com/Sedimark/InteroperabilityEnabler.

To install the package, you can use pip:

```bash
pip install InteroperabilityEnabler
```

## Acknowledgement

This software has been developed by the [Inria](https://www.inria.fr/fr) under the [SEDIMARK(SEcure Decentralised Intelligent Data MARKetplace)](https://sedimark.eu/) project. 
SEDIMARK is funded by the European Union under the Horizon Europe framework programme [grant no. 101070074]. 
