The document discusses the rapid rise of knowledge graphs and the utility of JSON-LD and SHACL in their construction and data validation. JSON-LD simplifies adding, retrieving, and deleting objects in knowledge graphs, while SHACL provides a way to enforce data integrity and impose constraints. The combination of these technologies makes knowledge graphs more accessible and manageable for developers.

1. JSON-LD and SHACL
for Knowledge Graphs
Dr. Jans Aasman
(allegrograph.com)

2. Contents
• Knowledge Graphs are getting popular very fast, are you
building a Knowledge Graph already?
• JSON-LD will help you add and delete objects to a
Knowledge Graph as easy as MongoDB
• SHACL will help you validate your data in the Knowledge
Graph.

3. Knowledge Graphs on the rise
• Line one

4. All the big ones in the US heavily investing in it
• Good luck trying to find a definition on the web that is not ideology or
vendor based or very application specific

5. Many technologies make a
Semantic Knowledge Graph

6. Documents: JSON, JSON-LD Graphs: RDF, Quads, Properties
Storage: Triple Attributes, Security Filters, Compression, Indexing, Full-text
Transactions: “Real” ACID, 2 Phase Commit
Management: Security, Multi-Master Replication, Backup/Restore, Warm Failover
Stored Procs:
JavaScript
Lisp
Prolog
SPARQL
Magic Predicates
Reasoning:
RDFS++
OWL2-RL
Prolog
Probabilistic
NLP:
Taxonomies
Entity Extract
Text Classify
Sentiment
Machine
Learning
ETL:
RDBMS
CSV
TEXT
NoSQL
Events:
Geospatial
Temporal
Social
REST GUI: GRUFF/AGWebView
Java Python Lisp
Built-In Integrations
Cloud:
Amazon AWS
Microsoft Azure
Data Science:
Anaconda
R Studio
Knowledge:
Linked Open Data
Editors:
Ontology, Taxonomy
NoSQL:
Cloudera, MongoDB,
Solr
Containers:
Docker, VMWare
Massively Parallel - Federation and Sharding
OSS Clients
SPARQL Prolog
Don’t worry, it is all easily accessible in
AllegroGraph Architecture

7. Successful Knowledge Graphs built on
• SKOS Taxonomies & OWL Ontologies
• RDF based Semantic Graph Technologies:
• Based on the uniqueness principle: one Thing, one URL
• If you don’t have that, you don’t have anything
• Property graphs destined to reinvent semantics
• But:
• Your User Experience and Application developers don’t want to learn
that entire stack

8. Challenge # 1 for UI and application developers:
How do you make it easy to
• Add data to a knowledge graph
• Retrieve data from a knowledge graph
• Validate your data

9. Solution:
• Knowledge Graphs are getting popular very fast, are you
building a Knowledge Graph already?
• JSON-LD will help you add, retrieve and delete objects to a
Knowledge Graph as easy as MongoDB
• SHACL will help you validate your data in the Knowledge
Graph.

10. JSON Won
• Messaging:
• the lingua franca for messaging and data exchange
• Configuration:
• JSON is replacing XML for configuration of nearly
anything
• Document and key/value store:
• JSON is the main data format stored in Document Stores
(Couchbase, Mongo, etc…)

11. JSON – the good
• Simple standard:
• Json.org spec is 5 pages, XML spec on W3C = 60 pages J
• only a few datatypes and with arrays!
• you can make your own complex data types if you want
• Easy to read and parse by humans and machines
• Easy to store in document stores
• Easy to program: support in every programming language

12. JSON (and JSON stores) – the bad
• No standards Schema (but close!)
• How do I know that the data I received is good, how do I know that
the data I’m going to send to my document store is good?
• No Semantics for attributes
• What does that attribute mean?
• Not set up for linking data
• How do I express linkage between JSON objects?
• No joins or graph search in document stores
• There simply is no concept of a relations between objects
• Client side joins or awkward procedures in javascript in the DB

13. JSON-LD = 100 % JSON +
• Add basic schema support to JSON: (but SHACL more complete)
• Add semantics to JSON objects: what does this attribute mean
• Designed to link JSON objects together
• Enables joins and graph search in document stores

14. Learn from JSON-LD.ORG

15. Google for
allegrograph python tutorial jsonld

16. It is everywhere: let’s look at this product

17. Search for @context in the source

18. JSON alone would lead to confusion, JSON-LD and
SCHEMA.ORG to the rescue
NO Meaning
WITH Meaning

20. Demo JSON-LD in Python
• Based on crunch base data from early 2000 till 2014
• Core objects: Investments, acquisitions, investors, companies
• For developers: how can you implement basic CRUD with AllegroGraph
JSONLD
• You can add and retrieve Python dictionaries directly
• Like many other document databases
• Objects are indexed with triples but can also be stored as blobs
• You can retrieve parts of objects in a SPARQL queries
• And you can retrieve as dictionaries.

21. And now SHACL

22. Semantic graphs allow you to be very ‘wild’
with your data
• Triples can be added without any schema definition
• Sometimes too flexible for the enterprise
• So the most asked question the last two years:
• Ummm, do you guys support SHACL validation?

23. SHACL seems to be replacing OWL
• Easier to read
• Less complicated
• OWL can still be derived automatically from SHACL
• Great tutorials on the web.

24. title
• Line one

25. SHACL
• Is data modeling language developed by a W3C Working Group.
• describes the “shapes” of the data so that applications can take better advantage
of that data.
• describes which properties go with which classes (like OWL)
• defines constraints on data with standardized models instead of procedural code.
• Has several built-in types of constraints such as cardinality
(minCount/maxCount), value type and allowed values, but it is also possible to
define more complex kinds of constraints for almost arbitrary validation conditions
• SHACL validation tools can verify whether your data fulfills the constraints
described by your data model, similar to how XML Schema or JSON Schema are
being used.
Derived from https://www.topquadrant.com/technology/shacl/tutorial/

26. Call SHACL validate from the command line

27. Deep integration with SPARQL

28. Conclusion: JSON-LD and SHACL
for Knowledge Graphs
• Make life easier for User Experience and Application
Developers that need to work with Knowledge Graphs.
• JSON-LD hides complexity of semantics and graphs
• SHACL easy way to validate new data.

29. Thank you