Merge pull request #69 from DerwenAI/update

Update

README.md

@@ -2,10 +2,10 @@
 
 The **kglab** library provides a simple abstraction layer in Python
 for building knowledge graphs.
-Welcome to *graph-based data science*.
+Welcome to *graph-based data science*:
 <https://derwen.ai/docs/kgl/>
 
-> **SPECIAL REQUEST:**
+> **SPECIAL REQUEST**
 > Which features would you like to see the most in an open source Python library for building and using knowledge graphs? Please add suggestions to this online survey: https://forms.gle/FMHgtmxHYWocprMn6  This will help us prioritize the roadmap for **kglab**.
 
 
@@ -55,138 +55,31 @@ graph libraries in Python:
 <https://derwen.ai/docs/kgl/tutorial/>
 
 
-
-### Dependencies
-
-- [Python 3.6+](https://www.python.org/downloads/)
-- [cairocffi](https://github.com/Kozea/cairocffi)
-- [gensim](https://radimrehurek.com/gensim/)
-- [GPUtil](https://github.com/anderskm/gputil)
-- [leidenalg](https://github.com/vtraag/leidenalg)
-- [matplotlib](https://matplotlib.org/)
-- [NetworkX](https://networkx.org/)
-- [NumPy](https://numpy.org/)
-- [OWL-RL](https://github.com/RDFLib/OWL-RL)
-- [pandas](https://pandas.pydata.org/)
-- [pslpython](https://psl.linqs.org/)
-- [pySHACL](https://github.com/RDFLib/pySHACL)
-- [pyarrow](https://arrow.apache.org/)
-- [pylev](https://github.com/toastdriven/pylev)
-- [python-dateutil](https://pypi.org/project/python-dateutil/)
-- [python-igraph](https://igraph.org/python/)
-- [pyvis](https://pyvis.readthedocs.io/)
-- [RDFlib](https://rdflib.readthedocs.io/)
-- [rdflib-json](https://github.com/RDFLib/rdflib-jsonld)
-
-
 ## Build Instructions
 
 **Note: most use cases won't need to build this package locally.**
 Instead, simply install from
 [PyPi](https://pypi.python.org/pypi/kglab)
 or [Conda](https://docs.conda.io/).
 
-To set up the build environment locally:
-```
-pip install -r requirements_build.txt
-```
-
-You will also need to download
-[`ChromeDriver`](https://chromedriver.chromium.org/downloads) 
-for your version of the `Chrome` brower, saved as `chromedriver` in this directory.
-
-This project uses `typing` and [`mypy`](https://mypy.readthedocs.io/) for *type checking*.
-To run type checking:
-```
-mypy kglab/*.py
-```
-
-This project uses `unittest` and [`coverage`](https://coverage.readthedocs.io/) for *unit test* coverage. 
-Source for unit tests is in the `test.py` module.
-To run unit tests:
-```
-coverage run -m unittest discover
-```
-
-To generate a coverage report and upload it to the `codecov.io`
-reporting site (if you have the token):
-```
-coverage report
-bash <(curl -s https://codecov.io/bash) -t @.cc_token
-```
-
-Test coverage reports can be viewed at
-<https://codecov.io/gh/DerwenAI/kglab>
-
-To generate documentation pages, this project uses:
-
-  * [`MkDocs`](https://www.mkdocs.org/)
-  * [`makedocs-material`](https://squidfunk.github.io/mkdocs-material/)
-  * [`MathJax`](https://www.mathjax.org/)
-  * [`pymdown-extensions`](https://facelessuser.github.io/pymdown-extensions/)
-  * [`Jupyter`](https://jupyter.org/install)
-  * [`nbconvert`](https://nbconvert.readthedocs.io/)
-  * [`Selenium`](https://selenium-python.readthedocs.io/)
-  * [`Chrome`](https://www.google.com/chrome/)
-  * [`Flask`](https://flask.palletsprojects.com/)
-
-Source for documentation is in the `docs` subdirectory.
-To build the documentation:
-```
-./nb_md.sh
-./pkg_doc.py docs/ref.md
-mkdocs build
-```
-
-To preview the generated microsite locally:
-```
-./preview.py
-```
-
-Then browse to <http://localhost:8000> to review the generated
-documentation.
-
-To package the generated microsite for deployment on a
-Flask/WSGI server:
-```
-tar cvzf kgl.tgz site/
-```
-
-To update the [release on PyPi](https://pypi.org/project/kglab/):
-```
-./push_pypi.sh
-```
-
-
----
-
-[![kg+lab](https://github.com/DerwenAI/kglab/blob/main/docs/illo/kglab.png)](https://github.com/DerwenAI/kglab/blob/main/docs/illo/kglab.png)
-
-## Production Use Cases
-
-  * [Derwen](https://derwen.ai/) and its client projects
-
-
-## Similar Projects
-
-See also:
+To set up the build environment locally, see the 
+["Build Instructions"](https://derwen.ai/docs/kgl/build/)
+section of the online documentation.
 
-  * [zincbase](https://github.com/complexdb/zincbase)
-    * *pro:* probabilistic graph measures, complex simulation suite, leverages GPUs
-    * *con:* lacks interchange with RDF or other standard formats
-  * [KGTK](https://github.com/usc-isi-i2/kgtk)
-    * *pro:* many excellent examples, well-documented in Jupyter notebooks
-    * *con:* mostly a CLI tool, primarily based on TSV data
+![illustration of a knowledge graph, plus laboratory glassware](https://raw.githubusercontent.com/DerwenAI/kglab/main/docs/assets/logo.png)
 
 
-## Attribution
+## License and Copyright
 
 Source code for **kglab** plus its logo, documentation, and examples
 have an [MIT license](https://spdx.org/licenses/MIT.html) which is
 succinct and simplifies use in commercial applications.
 
 All materials herein are Copyright (c) 2020-2021 Derwen, Inc.
 
+
+## Attribution
+
 Please use the following BibTeX entry for citing **kglab** if you use it in your research or software.
 Citations are helpful for the continued development and maintenance of this library.
 
@@ -204,7 +97,8 @@ Citations are helpful for the continued development and maintenance of this libr
 ## Kudos
 
 Many thanks to our contributors:
+[@ceteri]((https://github.com/ceteri),
 [@jake-aft](https://github.com/jake-aft),
 [@dmoore247](https://github.com/dmoore247),
-plus general support from [Derwen, Inc.](https://derwen.ai/)
-and [The Knowledge Graph Conference](https://www.knowledgegraph.tech/).
+plus general support from [Derwen, Inc.](https://github.com/DerwenAI)
+and [The Knowledge Graph Conference](https://github.com/KGConf).

docs/author.md

@@ -55,6 +55,9 @@ KTH, NYU, GWU,
 U Maryland, Cal Poly, UT/Austin,
 U Virginia, CU Boulder.
 
+
+## Just Enough Math, Edition 2
+
 You'll find elements from most of the above woven throughout this
 [**kglab** tutorial](../tutorial/):
 data science, business context, AI applications, 
@@ -71,9 +74,12 @@ which had the elevator pitch:
 thanks to quick thinking by editor Ann Spencer – 
 turned into a popular video+notebook series,
 followed by tutorials, and then a community focused on open source.
+Seven years later the field of 
+[data science](../glossary/#data-science)
+has changed dramatically
 This time around, **kglab** starts as an open source Python library,
 with a notebook-based tutorial at its core,
 focused on a community and their business use cases.
-Perhaps someday it may spin-out a book or other learning materials.
 
-YMMV.
+The scope now is about [*graph-based data science*](../glossary/#graph-based-data-science),
+and perhaps someday this may spin-out a book or other learning materials.

docs/biblio.md

@@ -14,6 +14,7 @@ O'Reilly Media (2020)
 **Jesse Anderson**  
 Apress (2020)
 
+
 ## – B –
 
 ### bell2019
@@ -34,6 +35,7 @@ Manning (2018)
 **Eric Brewer**  
 *Computer* 45:2 (2012)
 
+
 ## – C –
 
 ### ceder2018
@@ -48,6 +50,13 @@ Manning (2018)
 **François Chollet**  
 Manning (2017)
 
+### chong2021ds
+
+[*Become a Leader in Data Science*](https://www.manning.com/books/become-a-leader-in-data-science)  
+**Jike Chong**, **Yue Cathy Chang**  
+Manning (2021)
+
+
 ## – D –
 
 ### das2020meta
@@ -61,6 +70,7 @@ Manning (2017)
 **Aaron Kalb**, **Daniel Rincon Silva**  
 LinkedIn (2020)
 
+
 ## – G –
 
 ### gosnell2020
@@ -75,6 +85,7 @@ O'Reilly Media (2020)
 **Thomas R. Gruber**  
 *Knowledge Acquisition* 5 (1993)
 
+
 ## – H –
 
 ### hellersteinsgsa17
@@ -98,6 +109,7 @@ O'Reilly Media (2020)
 **Antoine Zimmermann**  
 *arXiv* (2020)
 
+
 ## – J –
 
 ### jonas2019cloud
@@ -109,6 +121,7 @@ O'Reilly Media (2020)
 **Raluca Ada Popa**, **Ion Stoica**, **David A. Patterson**  
 *arXiv* (2019)
 
+
 ## – K –
 
 ### kreps2014
@@ -117,6 +130,7 @@ O'Reilly Media (2020)
 **Jay Kreps**  
 O'Reilly Media (2014)
 
+
 ## – L –
 
 ### ledem2013hadoop
@@ -151,11 +165,12 @@ Gradient Flow (2020)
 
 ### lorica2020rai
 
-["Responsible AI in Practice"](https://gradientflow.com/ResponsibleAI2020)
+["Responsible AI in Practice"](https://gradientflow.com/ResponsibleAI2020)  
 **Ben Lorica**, **Paco Nathan**, **Gina Blaber**, **Andrew Burt**,
 **Rumman Chowdhury**, **Yishay Carmiel**  
 Gradient Flow (2020)
 
+
 ## – N –
 
 ### nathan2014jem
@@ -176,6 +191,7 @@ Manning (2021)
 **Natalya F. Noy**, **Deborah L. McGuinness**  
 *Stanford Knowledge Systems Laboratory Technical Report KSL-01-05* (2001)
 
+
 ## – P –
 
 ### perrone2020network

docs/build.md

@@ -0,0 +1,104 @@
+# Build Instructions
+
+!!! note
+    In most cases you won't need to build this package locally.
+
+Unless you're doing development work on the **kglab** library itself,
+simply install based on the instructions in
+["Getting Started"](https://derwen.ai/docs/kgl/start/).
+
+
+## Setup
+
+To set up the build environment locally:
+```
+pip install -r requirements_build.txt
+```
+
+You will also need to download
+[`ChromeDriver`](https://chromedriver.chromium.org/downloads) 
+for your version of the `Chrome` brower, saved as `chromedriver` in this directory.
+
+
+## Type Checking
+
+This project uses `typing` and [`mypy`](https://mypy.readthedocs.io/)
+for *type checking*.
+
+To run type checking:
+```
+mypy kglab/*.py
+```
+
+
+## Test Coverage
+
+This project uses `unittest` and 
+[`coverage`](https://coverage.readthedocs.io/)
+for *unit test* coverage. 
+Source for unit tests is in the 
+[`test.py`](https://github.com/DerwenAI/kglab/blob/main/test.py)
+module.
+
+To run unit tests:
+```
+coverage run -m unittest discover
+```
+
+To generate a coverage report and (providing you have the access
+token) upload it to the `codecov.io` reporting site:
+```
+coverage report
+bash <(curl -s https://codecov.io/bash) -t @.cc_token
+```
+
+Test coverage reports can be viewed at
+<https://codecov.io/gh/DerwenAI/kglab>
+
+
+## Online Documentation
+
+To generate documentation pages, this project uses:
+
+  * [`MkDocs`](https://www.mkdocs.org/)
+  * [`makedocs-material`](https://squidfunk.github.io/mkdocs-material/)
+  * [`pymdown-extensions`](https://facelessuser.github.io/pymdown-extensions/)
+  * [`MathJax`](https://www.mathjax.org/)
+  * [`Jupyter`](https://jupyter.org/install)
+  * [`nbconvert`](https://nbconvert.readthedocs.io/)
+  * [`Selenium`](https://selenium-python.readthedocs.io/)
+  * [`Chrome`](https://www.google.com/chrome/)
+  * [`Flask`](https://flask.palletsprojects.com/)
+
+Source for the documentation is in the 
+[`docs`](https://github.com/DerwenAI/kglab/tree/main/docs)
+subdirectory.
+
+To build the documentation:
+```
+./nb_md.sh
+./pkg_doc.py docs/ref.md
+mkdocs build
+```
+
+To preview the generated microsite locally:
+```
+./preview.py
+```
+
+Then browse to <http://localhost:8000> to review the generated
+documentation.
+
+To package the generated microsite for deployment on a
+Flask/WSGI server:
+```
+tar cvzf kgl.tgz site/
+```
+
+
+## Package Release
+
+To update the [release on PyPi](https://pypi.org/project/kglab/):
+```
+./push_pypi.sh
+```