Introduction and Installation¶
Purpose¶
Kunteksto (ˈkänˌteksto) [1] is a tool to translate simple CSV formatted data files into computable, semantically enhanced knowledge representations. As a foundation for crowdsourced, automated knowledge base construction; it provides a path for existing data sets to be used in conjunction with the emerging graph data, model first approach in analysis, general artificial intelligence (AGI), and decision support systems. This approach opens the door for the change to a more data-centric approach as opposed to the current application-centric approach. This new path enables automatic, machine processable interoperability avoiding the data quality issues created through data migration, data cleaning and data massaging. See Machine Learning & AI
The importance of how this simplifies query and analysis capabilities and improves data quality is discussed in foundational S3Model documentation and references. However, detailed understanding of S3Model is not required to understand and use the power of Kunteksto.
Target Audience¶
The Kunteksto design philosophy is based on the ability for domain experts from any field, with very little programming ability to quickly annotate data extracts to improve the usability of the data. Data engineers and data scientists can also benefit from Kunteksto in the same ways as domain experts.
Installation¶
Cross-Platform on Anaconda¶
Anaconda is the preferred environment for a tool like Kunteksto because it integrates easily with systems for domain experts, data engineers, and data scientists.
- Download and install Anaconda Python 3.7+ for your platform.
- More detailed Anaconda instructions are here if you prefer.
Note
Anaconda now offers to install the VS Code editor. Unless you already have a preferred text editor, this is a good choice.
- Open a terminal window and create a conda environment. On Windows it is best to open an Anaconda Prompt terminal from the Anaconda menu:
conda create -p Kunteksto python=3 pycurl ujson
- Change to the directory
cd Kunteksto
- Activate the environment according to the instructions shown by Anaconda in the terminal window.
Windows
activate <path/to/directory>
or Linux/MacOSX
source activate <path/to/directory>
- Windows users may need to manually install the pycurl library using this command:
conda install pycurl
trying will not damage anything but it may fail or just report that pycurl is the current version.
- install Kunteksto
pip install kunteksto
These quick steps create a virtual environment in the subdirectory Kunteksto. Notice this directory has a capital K.
Once the environment is created, conda displays how to activate the environment. When you have activated the environment you then install the Kunteksto application in the environment. After installation the will be a new subdirectory called kunteksto (small k). This is called the Kunteksto directory throughout this tutorial.
Change to the Kunteksto directory:
cd kunteksto
The next step is to do the Tutorial/Demo
Update to a New Version¶
When you want to upgrade to a new version of Kunteksto you can use the line below in your terminal where you have activated the virtual environment.
pip install kunteksto --upgrade --no-cache-dir
What are all the files for?¶
Depending on how and where you installed Kunteksto you will see a varying number of files and subdirectories. Many of them may be part of the Anaconda environment, so we do not cover those.
Referenced from the kunteksto directory created at install time:
Files¶
- README.md
- A brief explanation of Kunteksto’s purpose and links to background information.
- LICENSE.txt
- A copy of the copyright notice and license.
- kunteksto.conf
- This file is the required configuration file for Kunteksto.
Directories¶
- example_data
- This directory contains information and sample data files for the tutorials. There is also an example of the completed Demo database, model, and data in the archive Demo_with_semantics.zip.
- catalogs
- This directory is where Kunteksto places XML catalog files used in the data validation process.
- s3model
- Support files required for operation.
- s3model.owl - the core S3Model ontology.
- s3model_3_1_0.xsd - the reference model schema version 3.1.0
- s3model_3_1_0.rdf - the extracted semantics from the reference model schema version 3.1.0
- s3model_3_1_0.xsl - a stylesheet providing visualization in a browser of the reference model schema version 3.1.0
- dm-description.xsl - a stylesheet that provides for visualization in a browser of any S3Model data model.
Footnotes
[1] | S3Model is called the Esperanto of information management. Kunteksto is the Esperanto translation of the word Context. See Wikipedia for more information about the Esperanto language. |