Merge pull request #70 from DerwenAI/update

Update

README.md

@@ -2,11 +2,15 @@
 
 The **kglab** library provides a simple abstraction layer in Python
 for building knowledge graphs.
+
 Welcome to *graph-based data science*:
 <https://derwen.ai/docs/kgl/>
 
-> **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**.
+> **SPECIAL REQUEST**: Which features would you like in an
+> open source Python library for building knowledge graphs?  
+> Please add your suggestions through this survey:  
+> https://forms.gle/FMHgtmxHYWocprMn6  
+> This will help us prioritize the roadmap for **kglab**.
 
 
 ## Getting Started
@@ -97,7 +101,7 @@ Citations are helpful for the continued development and maintenance of this libr
 ## Kudos
 
 Many thanks to our contributors:
-[@ceteri]((https://github.com/ceteri),
+[@ceteri](https://github.com/ceteri),
 [@jake-aft](https://github.com/jake-aft),
 [@dmoore247](https://github.com/dmoore247),
 plus general support from [Derwen, Inc.](https://github.com/DerwenAI)

docs/concepts.md

@@ -5,17 +5,15 @@
 This material is a work in progress, at "rough draft" stage.
 
 
-## Organization of learning materials
-
-<img src="../assets/learning.png" width="600" />
+## Class Abstractions
 
 The primary abstractions used in **kglab** are based on a small set of
 Python classes.
 These class definitions can be subclassed and extended to handle
 specific use cases as needed.
 
 
-## Knowledge Graph
+### Knowledge Graph
 
 [`kglab.KnowledgeGraph`](../ref/#knowledgegraph-class)
 
@@ -29,20 +27,30 @@ also handle *property graph*
   * *validation*
 
 
-## Measure
+### Measure
 
 [`kglab.Measure`](../ref/#measure-class)
 
   * *topology*
   * *statistics*
 
 
-## Subgraph
+### Subgraph
 
 [`kglab.Subgraph`](../ref/#subgraph-class)
 
   * *label encoding*
   * *visualization*
   * *graph algorithms*
   * *probabilistic graph inference*
-  * *embedding*
+  * *embedding*
+
+
+## Open Source Integration
+
+<a href="../assets/landscape.png" target="_blank"><img src="../assets/landscape.png" width="650" /></a>
+
+
+## Learning Materials
+
+<a href="../assets/learning.png" target="_blank"><img src="../assets/learning.png" width="650" /></a>