Metadata-Version: 2.0
Name: kunteksto
Version: 1.3.7
Summary: The Context tool for your data. This is your tool to enter the emerging data-centric, model-based approach to information management. 
Home-page: https://datainsights.tech/Kunteksto/
Author: Timothy W. Cook
Author-email: tim@datainsights.tech
License: UNKNOWN
Download-URL: https://github.com/DataInsightsInc/Kunteksto/archive/1.3.7.tar.gz
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
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Provides-Extra: agraph
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Kunteksto (ˈkänˌteksto) is a tool to help domain experts, data creators and data users translate their simple CSV formatted data files into the semantically enhanced formats that provide computable metadata. 
This provides a path for existing data to be used in conjuntion with the emerging *data-centric, model based* 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.


