Your Knowledge Democratization Platform

metaphactory transforms your data into consumable, contextual & actionable knowledge and drives continuous decision intelligence


Improve data literacy across the enterprise

Out-of-the-box, intuitive interfaces for searching, browsing & exploring your Knowledge Graph



Capture hidden expert knowledge in your semantic knowledge model

Visual ontology modeling for domain experts & business users; Taxonomy & Dataset management



Build Knowledge Graph applications to match your enterprise requirements

Low-code approach to building custom interfaces that enable business-user interaction with the Knowledge Graph

Why metaphactory?

Flexible Knowledge Graph-driven platform delivering:

Low initial investment

Start small, iterate often & add new use cases, new data and new users on the fly


Knowledge Graph platform based on open standards


Fast time to value

Agile knowledge management & low-code platform for building applications

Risk mitigation

Ready-to-use enterprise product from proven vendor

Static products

  • Low match with needs
  • Expensive to adjust
  • Proprietary, closed system

Build your own

  • High risk
  • Long ramp-up
  • Unclear maintenance

Success stories

How does it work?


  • Visual authoring, visualization, versioning & cataloging of ontologies, vocabularies, datasets & queries
  • Data validation, provenance & lineage


  • Abstracted view
  • One-stop knowledge hub
  • Intuitive UI for knowledge discovery, exploration, analytics, authoring


  • Low-code platform
  • Powerful template engine
  • Large library of Web components
  • Easy customization


  • Unified view on distributed & heterogenous data sources: graph databases, relational databases, REST APIs, machine learning algorithms
  • Transparent SPARQL federation


  • Dynamic data-driven REST APIs based on queries
  • Role-based access control
  • Lookup & Reconciliation
  • Tableau – Web Data Connector Endpoint

Platform built on open standards

metaphactory's generic approach based on open standards offers great flexibility in different industries and supports interoperability and reusability across use cases and business functions.


RDF Data Model

Standardized Data Model

Flexible, open standard for data respresentation


Ontology Language

Ontology Language

Formal definition of your domain model which can be extended at any time




Categorization and classification of data as hierarchical structures


Rules & Constraints

Rules & Constraints

Definition of explicit cardinalities & constraints in the model for automated reasoning


Query Language

Query Language

Flexible query language to specify graph-shaped information needs


Linked Data Platform

Linked Data Platform

Open standards to support FAIR data incl. data publishing


Dataset descriptions

Dataset descriptions

Dataset descriptions based on open W3C standards to make the data discoverable, accessible & traceable

Dublin Core

Data cataloging standards

Data cataloging standards

Standardized metadata elements that offer expanded cataloging information

Web components

Web Components

Web Components

Extensive set of rich components for search, visualization, exploration & authoring


HTML Templates

HTML Templates

Low-code application building using flexible templating engine


Microservice Packaging

Microservice Packaging

Stateless, scale-out design that supports flexible environments




Dynamic publishing of queries as REST APIs

metaphactory features in a nutshell


  • Search components featuring auto-completion and semantic disambiguation
  • Interactive search system based on a user-friendly graphical interface for expressive query construction
  • Support for full-text search indices to score and rank results for responsive auto-suggestion
  • Filters and facets for interactive and iterative query refinement and exploration
  • Clipboarding functionalities to organize knowledge and support sharing of both searches and search results
  • Search functionality utilizing controlled and structured vocabularies for synonym search and search across narrower terms in a category
  • Ability to search by synonyms and preferred labels
  • Inclusion of sub-terms in search results when searching for broader categories
  • Ability to reuse search results or sets in further search queries or combine them with new search queries


  • Rich set of components for interactive visualization and exploration of large knowledge graphs, including: interactive graphs, carousels, interactive tables, maps, charts, tree renderings and timelines
  • Visualization of data along different contextual dimensions, e.g., spatial and temporal dimensions
  • Browsing, filtering and sorting options available for all components
  • Ontology visualization
  • Multilingual interfaces

Discovery & Exploration

  • Visualization of complex relations in interactive graphs
  • Pathfinding - Search for paths between nodes & interactively explore relations in a graph
  • Integration of rich snippets of information (Knowledge Panels) allowing for contextualized, in-page exploration of knowledge graph resources
  • Auto-layouts including manual refinement options and snap grids
  • Ability to create interactive diagrams and add them to reports or custom applications
  • Functionality to export diagrams into image and vector formats for scalable prints


  • Collaborative creation and editing of data using customizable, flexible semantic forms
  • Visual instance authoring interface allowing end users to create, edit and connect instance data entities using the interactive graph component
  • Composite inputs for semantic forms allowing for the inline creation of new entities
  • Rich editing components for special data types
  • Auto-suggestion and validation against the knowledge graph
  • Capturing of provenance information

End-user Knowledge Management

  • Semantic Clipboard allowing end users to create personalized information collections where they can store and organize named sets of knowledge graph items for reuse
  • Ability to drag and drop resources from the clipboard into search interfaces or visual graphs for reuse
  • Ability to save, download and share diagrams with other users

Data Access Services

Middleware Services

  • Query as a Service
    • Ability to template queries and expose them during runtime as dynamic and parameterisable REST APIs for 3rd party application integration (e.g., Workflow Pipeline, Knime, R, etc.) with configurable output formats (JSON, CSV, RDF)
    • Controlled access to published query results using access permissions, data hiding, and encapsulation
  • Tableau endpoint & further integration points for BI tools like Spotfire
  • Label service - ubiquitous access to human readable labels for knowledge graph resources
  • Description service - provides contextual information for a knowledge graph entity when exploring and searching data, e.g., for disambiguation purpose
  • Lookup service - provides an abstraction layer over keyword indices
  • Role-based access – all service endpoints are protected by the role-based access model and single sign-on (OAuth2, OpenId Connect, SAML2, LDAP)

Model-driven Application Building

  • Powerful template engine to render knowledge graph instances pertaining to the same class/type in the ontology in a unified way
  • Rich set of built-in W3C Web Components using HTML 5 syntax for composing templates, application pages and dashboards declaratively
  • Web-based HTML editor with syntax highlighting
  • Interactive and multilingual applications are built on the fly (declaratively), without the need to change the source code
  • No-code wizards supporting application engineers in the application building process by allowing them to identify and visually select classes, relations and attributes from the ontology that are required to capture the end-users’ information intent
  • Individual elements in the resulting application can be customized by templating and parameterizing them through the powerful handlebars templating language
  • Customized user views depending on user roles and access permissions and ability to customize dashboards to a customer’s corporate look-and-feel

Management of Knowledge Graph Assets

  • Ontology Modeling & Management
    • Visual ontology editor based on a visual language and which delivers a user-friendly environment for ontology exploration, visualization, editing and documentation. The visual language translates to core elements of OWL and SHACL and results in an ontology based on open modeling and validation language W3C standards
    • Ontology cataloging for search, versioning (Git) and metadata curation
  • SKOS Vocabulary Management
    • Form-based creation and editing of SKOS vocabularies to capture business-relevant term lists and hierarchies (hypernyms and hyponyms) incl. management of multilingual synonyms and symbols
    • Performant tree visualization of and search across term hierarchies
    • Vocabulary cataloging for search, versioning (Git) and metadata curation
  • Tight integration between ontologies and vocabularies to support linking classes in the ontology editor to controlled vocabularies
  • Data cataloging capabilities
    • Creation, management or import of existing dataset metadata at integration time, making such context metadata an integral part of the connected knowledge graph
    • Support for DCAT and Dublin Core
    • Exposure of dataset context information in end-user oriented search interfaces, knowledge panels, and custom dashboards

Data & Query Engineering

  • One comprehensive solution for connecting, discovering and managing data across physical and virtual data repositories (or named graphs)
  • Support for data ingestion
  • Standard connectors for a variety of data formats
  • Low level data profiling, i.e., inspection of data types, data partitioning, statistics
  • Centralized management of namespaces and prefixes
  • SPARQL Query Editor: Contextualization, syntax highlighting, and auto-completion
  • Query Catalog: Ability to save and restore queries

Data Quality

  • SHACL-based Rule Engine: Support for native SHACL rules to establish technical conformity of data
  • Integration with database native SHACL validation engines
  • Ability to define rules based on SPARQL queries to run checks and validations against custom business logic
  • Charts displaying high-level, visual aggregations are used to quickly assess current data quality status and trends over time, including previous data quality reports
  • Detailed violation reports allow for inspecting and drilling down to individual violations, e.g., to identify the knowledge graph resources violating a rule

Get started today!

Product news

Product resources

Our product is available for on-premise installation and as an on-demand, cloud-based solution, e.g., on AWS Marketplace.

Contact us to request a quote and one of our account managers will be in touch to define the best product configuration for you.