TopBraid Technology Overview | TopQuadrant, Inc.

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TopBraid Technology Overview

TopBraid products package a stack of technologies as a complete solution for services and applications that operate on Linked Data aka Knowledge Graphs. The technologies build on:

  • RDF, the standards-based graph data model
  • SPARQL, the query language for RDF
  • SHACL, the data shapes language for RDF data validation and reasoning
  • GraphQL, the query language for APIs and data selection

Combined, they offer extremely powerful tools for specifying business rules, describing user interfaces, providing web services and more.

Applications and Services
Data Processing Pipelines
UI Services and Components
SPARQL Web Pages (SWP), SWA, GraphQL
Data Validation, Inference, Data Mapping
SHACL Engine, Machine Learning
Query Engine
Model: Classes, Properties
Change Management
Teamworks Framework (TopBraid EDG only)
Data Layer: Graph Database, Data Source Adapters
  • You may have heard the term “knowledge graph” from Google or Microsoft. These companies use knowledge graphs for smart search. Knowledge graphs provide an equally powerful platform for enterprise data integration and reuse.

    Here are some characteristics of knowledge graphs. They are:

    • Flexible – graphs are the most flexible formal data structures (making it simple to map other data formats to graphs) that capture explicit relationships between items so that you can easily connect new data items as they are added and traverse the links to understand the connections.
    • Evolvable – able to accommodate diverse data and metadata that adjusts and grows over time, much like living things do.
    • Semantic – the meaning of the data is stored alongside the data in the graph, in the form of the ontologies or semantic models. This makes knowledge graphs self-descriptive, a single place to find the data and understand what it’s about.
    • Intelligent – the semantics of data are explicit and include formalisms for supporting inferencing and data validation. As a self-descriptive data model, knowledge graphs enable data validation and can offer recommendations for how data may need to be adjusted to meet data model requirements. They also enable drawing conclusions and new information from the available data.

    These qualities make knowledge graphs an ideal and, arguably, the only viable foundation for bridging and connecting enterprise metadata silos. As an additional benefit, every resource in TopBraid knowledge graph has a globally unique dereferenced web identifier – a URI. Thus, can be reliably referred to and accessed from any application.

  • The foundation of TopBraid platform is RDF, which also serves as the base infrastructure of the Semantic Web and Linked Data. The platform implements W3C standards including RDF, RDFS, SHACL, SPARQL and OWL and provides the following capabilities:

    • Data Layer uses RDF to store and access information. TopBraid platform includes both an RDF-native and RDBMS-based database system for storing triples. Since most information today is stored in other formats, TopBraid dynamically accesses diverse data sources as if they were in RDF. This is possible because RDF data model is highly canonical and can represent any other data model including relational, XML, spreadsheet data, etc. The platform includes adapters for all popular data sources.
    • Change Management layer maintains a history of all changes in the data.
    • Query Engine provides SPARQL and GraphQL access to information.
    • Models of information are represented using standard languages for semantic models – RDFS, SHACL and OWL. These languages are built on RDF. This means that models are stored and can be queried the same way as data.
    • Constraints, Query Templates, Functions and Rules can be represented using SHACL or SPIN, and often use SPARQL or JavaScript under the hood. Both SHACL and SPIN provide mechanisms to attach behavior (rules and constraints) to classes in the model. They also enable parameterized query templates that can be provisioned as web services. Users cab create new custom SPARQL elements as functions. Rules and extensions are defined in a completely declarative manner, entirely in RDF. This means that anything that is defined with SHACL or SPIN can be shared and discovered in the same infrastructure that also holds the data.
    • Inference and Data Mapping are represented in either SHACL or SPIN, provided through forward and backward chaining rules engines and declarative languages such as SPINMap for defining mappings between models.
    • Data Processing Pipelines are supported using SPARQLMotion, a declarative language with a visual notation and a corresponding engine. SPARQLMotion scripts consist of simple steps such as loading data, running transformations and then exporting the results. The result of one step may be passed as input to the next step, enabling extensive data transformation, alignment and integration capabilities. SPARQLMotion is aimed at modelers and business analysts who want to use high level graphical tools. SPARQLMotion can be used to define (web) services, and to create new SPARQL functions, which can then be used as part of other SPARQL-based features.
    • Templates and User Interface Components, as everything in the platform, are implemented using RDF. SPARQL Web Pages make it possible to define user interfaces by annotating semantic models with appropriate visualizations. SWP makes it easy to encapsulate HTML snippets into reusable components. TopBraid provides SWP Application Component Library (SWA) with pre-built trees, forms, grids components as well as more sophisticated visualizations. SWP can also be used to define web services, for example to produce JSON.

  • TopBraid Technologies are packaged the following products:

    • TopBraid Live – as an application server that runs TopBraid EDG and TopBraid Explorer. This means that the entire technology stack is part of TopBraid EDG and Explorer.
    • Graphzelle – the first graph database with integrated support for W3C Standards RDF, SHACL and SPARQL (for data validation, inferencing and query) and GraphQL (for query and APIs). Graphzelle technology stack currently does not include Change Management and Data Processing Pipelines layers.

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