Metadata-Version: 2.1
Name: kunteksto
Version: 2.1.0
Summary: The tool to translate your CSV data files into RDF, XML and JSON with full semantics and syntactic validation.
Home-page: https://datainsights.tech/
Author: Timothy W. Cook
Author-email: tim@datainsights.tech
License: UNKNOWN
Download-URL: https://github.com/DataInsightsInc/Kunteksto/archive/2.1.0.tar.gz
Description: # Kunteksto
        
        =======================================================
        
        **Kunteksto** is a tool for helping domain experts, data creators and data users translate their simple CSV formatted data files into semantically enhanced formats. This provides a path for existing data to be used in conjunction with the emerging *data-centric, model first* approach in analysis, general artificial intelligence and decision support systems. This approach opens the door for the change to a *data-centric* world as opposed to the *application-centric* one we have now. This new approach enables automatic interoperability avoiding the data quality issues created through data cleaning and massaging. 
        
        The importance of this capability and improved data quality is discussed in foundational S3Model https://datainsights.tech/S3Model documentation and references. However, detailed understanding of S3Model is not required to understand and use the power of Kunteksto. Addtional information on the data-centric movement can be found in the References below. 
        
        What is 'Context' for your data?
        
        It is the combination of ontological, temporal and spatial semantics that describes the deeper meaning of your data allowing you to share 'information' instead of just 'data'.
        
        # Installation
        
        See the instructions in the documentation or online at https://datainsights.tech/Kunteksto/index.html
        
        # References
        
        The limits of deep learning https://blog.keras.io/the-limitations-of-deep-learning.html 
        
        The future of deep learning https://blog.keras.io/the-future-of-deep-learning.html
        
        
        # Development
        
        - Install Anaconda (Python 3.7+)
        - Open a terminal.
        - Clone the repository.
        - Create the development virtual environment: $ conda env create -f Kunteksto/dev_environment.yml
        - Activate the environment according to the instructions displayed in the terminal.
        - Change to the Kunteksto directory: $ cd Kunteksto/kunteksto
        - Run the Kunteksto dev server: $ ./kunteksto.sh
        - In a browser go to: http://127.0.0.1:7659/ 
        
        When making changes and testing locally you should;
        build the package: $ python3 setup.py sdist bdist_wheel
        Then perform a local install: $ pip install e .
        
        
Keywords: context rdf xml machine learning data-centric semantic interoperability semantics
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Customer Service
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Legal Industry
Classifier: Intended Audience :: Manufacturing
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Religion
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: System Administrators
Classifier: Intended Audience :: Telecommunications Industry
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.7
Description-Content-Type: text/markdown
