model map connect
Blog Kevin Doubleday04.11.24

Model, Map, Connect: How Fluree Builds Sustainable Knowledge Systems

Exploring Fluree's Stack through the Model, Map, Connect Formula

At Fluree, we’ve embraced the data-centric principles of data management, which ultimately de-couple applications from data. Data-Centric architectures allow data to exist independently of a singular application or silo, creating a network of “autonomous data” that can be re-used and shared across a diverse set of use cases. 

As we’ve discussed in our Data-Centric Architecture series, there are a few capabilities that must be set into place to enable autonomous and reusable data, namely: 

  • Semantic Interoperability – Universal standards to represent data in a form that can be found, accessed, and used across disparate contexts. 
  • Data-Centric Security – Policies embedded at the data tier to programmatically enforce Identity and Access Management, no matter where, how, or who has query access.
  • Digital Trust – Digital proof in the form of cryptographic signatures to verify data authenticity and origin. 
  • Data-Centric Time – A temporal dimension that time-stamps every piece of data to enable historical queries and audits. 

This kind of radical change cannot happen overnight. Oftentimes, applications and data systems sprawl in heterogeneous formats across diverse departments, and are layered with various and complex governance controls. It might seem impossible to even assemble the people, processes, and technology to embark on such a journey. 

At Fluree, we’ve found that starting small within a single domain and iterating over time yields the best return on investing in a data-centric architecture. We like to place our products into a continuum that defines and assembles knowledge from existing data within that domain: Model, Map, Connect. Think of this framework less as a hard-coded three-step process, but more as a set of interconnected modules that continuously grow alongside each other and your data systems. 


Start with a domain and model it- this could be a business application schema, business or industry ontology, or a standardized schema from 

It’s important to understand what your data is about and what concepts your business cares about. Organizations can find themselves anywhere on the spectrum of controlled vocabulary maturity; from managing taxonomies in spreadsheets to a fully-fleshed ontology management program. In any case, controlled vocabulary management is an important tool for solidifying a single source of truth for your business. In the model step, we develop the conceptual model to represent entities, attributes, and relationships within the knowledge graph.   

Fluree’s Intelligent Taxonomy Manager is a simple, powerful tool to describe business concepts and their interrelationships. Built for collaboration, ITM enables teams to define terminologies and semantic relationships to create consistent vocabularies. You can model pretty much anything and create a unique ID for each concept or piece of knowledge. Fluree ITM also comes with built-in data improvement – powered by AI, the ITM system will automatically recommend new candidate terms to improve the context and depth of your data. 


Fluree’s technology automates the classification and mapping of both structured and unstructured data into a specified semantic vocabulary, automating knowledge representation from across your data systems. 

Once you’ve modeled your domain, it’s time to discover and map existing data to your controlled vocabulary. This is the step that many organizations find the most painstaking and costly. Traditionally, getting access to relevant data and then harmonizing, classifying, and cleansing it takes an overwhelming manual effort from data engineering teams and Subject Matter Experts. The challenges and costs only increase if data quality is overlooked, leading to a portfolio of “dirty data.”

Once again, Fluree’s approach to semantic data management provides a foundation for (1) automating the manual data mapping processes and (2) creating golden records that will never become obsolete, dirty, or outdated again. 

model map connect

Structured Data

For Structured Data, Fluree Sense uses AI and ML to automatically ingest, classify, and master records from an array of disparate data sources. With more than 30 out-of-the-box connectors to common data sources (SAP, Oracle, Salesforce, and others), Fluree Sense can plug into any structured data source and handle all aspects of data discovery, cleansing, mapping, and conversion to your target data model. Fluree Sense uses subject matter expertise to reinforce its ML capabilities, which will ultimately scale to billions of records and 99% accuracy for batch or continuous jobs.

Unstructured Data

model map connect in fluree CAM

For Unstructured Data, Fluree CAM (Content AutoTagging Manager) uses NLP and various out-of-the-box ML workflows to automatically classify and tag content. Using your model managed in Fluree ITM, organizations can set up CAM workflows to integrate into any kind of unstructured data source (PDFs, Videos, Audio, Sharepoint, Zendesk, and more) and auto-classify content on the fly.

Importantly, Fluree CAM and Fluree Sense both publish out knowledge graph ready data: 

  • “FAIR” data: information that is Findable, Accessible, Interoperable, and Reusable by humans and machines.
  • Classified under your target controlled vocabulary
  • Relationships between data are semantically defined
  • In RDF format, serialized as JSON-LD 


Analyze, interpret, and securely share your data with security policies directly built-in. Connect to apps and collaborate on datasets. 

Once you’ve architected a semantic knowledge graph from your various systems by defining your controlled vocabularies and mapping existing data, it’s time to provide access to your information for various data use cases. We need to access, share, and re-use this data for analytics, regulatory reporting, and new applications. 

Fluree CAM, Sense, and ITM all integrate into Fluree Core, our knowledge graph database built for secure and trusted data collaboration. Fluree Core uses JSON-LD as the de-facto standard for transacting and querying your knowledge graph database, making it accessible for developers and analysts alike to build queries on top of consumption-ready data. 

Fluree Core was built with the three key ingredients to enable superior knowledge graph data management: 

  • Security Policies – Build, manage, and enforce data policy as data within your knowledge graph. Embedded read and write access control at the data tier opens up unlimited sharing capabilities. 
  • Digital Trust – Fluree embeds lineage and cryptographic proof of provenance as key metadata for each and every new transaction – enabling data consumers to trust and verify the information they are using came from a reliable source and has not been tampered with. 
  • Linked Data Standards – As an RDF Semantic graph database, Fluree uses universal standards for linked data, allowing for schema at query time and unlocking powerful knowledge graph capabilities.


Model, Map, and Connect are modules that will continuously evolve. Perhaps there are updates to your existing taxonomy or ontology, or an entirely new vocabulary that needs to be set into place. Perhaps you’re ready to expand or otherwise connect to new data sources to grow your knowledge graph capabilities. Perhaps there are new applications or business partners that need controlled secure access to your knowledge.

Because we’ve built a knowledge ecosystem on top of semantic standards, you can integrate any kind of new workflow to adapt to changing business needs. That’s the beauty of data-centric architectures – data exists independently of a singular application or data silo and can serve across multiple use cases. Data becomes less of a cost-center and more of an investment that grows with your business over time. 


Here’s a TL:DR version of the model map connect framework: 

  1. Identify a domain and model it with a semantic ontology. 
  2. Map existing (or new) data to your model. 
  3. Securely connect consumption patterns, applications, and business users to the data.
  4. Expand and evolve your data models, data consumers, and data sources using automation.

Want to see this in action? Review this 20-minute video taking you through each module in the Fluree stack: 

Interested in getting started? Reach out to us here!