Validating RDF data

Contents

• 0.1  Abstract

• Chapter 1  Introduction
  • 1.1  RDF and the Web of Data
  • 1.2  RDF: The Good Parts
  • 1.3  Challenges for RDF Adoption
  • 1.4  Structure of the Book
  • 1.5  Conventions and Notation
• Chapter 2  The RDF Ecosystem
  • 2.1  RDF History
  • 2.2  RDF Data Model
  • 2.3  Shared Entites and Vocabularies
  • 2.4  Technologies Related with RDF
    • 2.4.1  SPARQL
    • 2.4.2  Inference Systems: RDF Schema and OWL
    • 2.4.3  Linked Data, JSON-LD, Microdata, and RDFa
  • 2.5  Summary
  • 2.6  Suggested Reading
• Chapter 3  Data Quality
  • 3.1  Non-RDF Schema Languages
    • 3.1.1  UML
    • 3.1.2  SQL and Relational Databases
    • 3.1.3  XML
    • 3.1.4  JSON
    • 3.1.5  CSV
  • 3.2  Understanding the RDF Validation Problem
  • 3.3  Previous RDF Validation Approaches
    • 3.3.1  Query-based Validation
    • 3.3.2  Inference-based Approaches
    • 3.3.3  Structural Languages
  • 3.4  Validation Requirements
    • 3.4.1  General Requirements
    • 3.4.2  Graph-based Requirements
    • 3.4.3  RDF Data Model Requirements
    • 3.4.4  Data-modeling-based Requirements
    • 3.4.5  Expressiveness of Schema Language
    • 3.4.6  Validation Invocation Requirements
    • 3.4.7  Usability Requirements
  • 3.5  Summary
  • 3.6  Suggested Reading
• Chapter 4  Shape Expressions
  • 4.1  Use of ShEx
  • 4.2  First Example
  • 4.3  ShEx implementations
  • 4.4  The Shape Expressions Language
    • 4.4.1  Shape Expressions Compact Syntax
    • 4.4.2  Invoking Validation
    • 4.4.3  Structure of Shape Expressions
    • 4.4.4  Start Shape Expression
  • 4.5  Node Constraints
    • 4.5.1  Node kinds
    • 4.5.2  Datatypes
    • 4.5.3  Facets on Literals
    • 4.5.4  Value Sets
  • 4.6  Shapes
    • 4.6.1  Triple Constraints
    • 4.6.2  Groupings
    • 4.6.3  Cardinalities
    • 4.6.4  Choices
    • 4.6.5  Nested Shapes
    • 4.6.6  Inverse Triple Constraints
    • 4.6.7  Repeated Properties
    • 4.6.8  Permitting other Triples
  • 4.7  References
    • 4.7.1  Shape References
    • 4.7.2  Recursion and Cyclic References
    • 4.7.3  External Shapes
    • 4.7.4  Labeled Triple Expression
    • 4.7.5  Annotations
  • 4.8  Logical Operators
    • 4.8.1  Conjunction
    • 4.8.2  Disjunction
    • 4.8.3  Negation
  • 4.9  Shape Maps
    • 4.9.1  Fixed Shape Maps
    • 4.9.2  Query Shape Maps
    • 4.9.3  Result Shape Maps
    • 4.9.4  JSON Representation
    • 4.9.5  Chaining Validation Workflows
  • 4.10  Semantic Actions
  • 4.11  ShEx and Inference
  • 4.12  Importing schemas
  • 4.13  RDF and JSON-LD Syntax
  • 4.14  Summary
  • 4.15  Suggested Reading
• Chapter 5  SHACL
  • 5.1  Simple Example
  • 5.2  SHACL Implementations
  • 5.3  Basic Definitions: Shapes Graphs, Node, and Property Shapes
  • 5.4  Importing other Shapes Graphs
  • 5.5  Validation Report
  • 5.6  Shapes
    • 5.6.1  Node shapes
    • 5.6.2  Property Shapes
    • 5.6.3  Constraint Components
    • 5.6.4  Human Friendly Messages
    • 5.6.5  Declaring Shape Severities
    • 5.6.6  Deactivating Shapes
  • 5.7  Target Declarations
    • 5.7.1  Target Node
    • 5.7.2  Target Class
    • 5.7.3  Implicit Class Target
    • 5.7.4  Target Subjects Of
    • 5.7.5  Target Objects Of
  • 5.8  Cardinality
  • 5.9  Constraints on Values
    • 5.9.1  Datatypes
    • 5.9.2  Class of Values
    • 5.9.3  Node Kinds
    • 5.9.4  Sets of Values
    • 5.9.5  Specific Value
  • 5.10  Datatype Facets
    • 5.10.1  Value Ranges
    • 5.10.2  String-based Constraints
    • 5.10.3  Language-based Constraints
  • 5.11  Logical Constraints: and, or, not, xone
    • 5.11.1  AND
    • 5.11.2  OR
    • 5.11.3  Exactly One
    • 5.11.4  Not
    • 5.11.5  Combining Logical Operators
  • 5.12  Shape-based Constraints
    • 5.12.1  Shape References and Recursion
    • 5.12.2  Qualified Value Shapes
  • 5.13  Closed Shapes
  • 5.14  Property Pair Constraints
  • 5.15  Non-validating SHACL Properties
  • 5.16  SHACL-SPARQL
    • 5.16.1  SPARQL Constraints
    • 5.16.2  SPARQL-based Constraint Components
  • 5.17  SHACL and Inference Systems
  • 5.18  SHACL Compact Syntax
  • 5.19  SHACL Rules and Advanced Features
  • 5.20  SHACL Javascript
  • 5.21  Summary
  • 5.22  Suggested Reading
• Chapter 6  Applications
  • 6.1  Describing a Linked Data Portal
    • 6.1.1  WebIndex in ShEx
    • 6.1.2  WebIndex in SHACL
  • 6.2  Describing Clinical Records—FHIR
    • 6.2.1  FHIR as Linked Data
    • 6.2.2  Consistency constraints
    • 6.2.3  FHIR/RDF Development
    • 6.2.4  Generic Properties
  • 6.3  Springer Nature SciGraph
  • 6.4  DBpedia Validation Use Cases
    • 6.4.1  Ontology-based Validation
    • 6.4.2  RDF Mappings Validation
    • 6.4.3  Validating Link Contributions with SHACL
    • 6.4.4  Ontology Validation with SHACL
  • 6.5  ShEx for ShEx
  • 6.6  SHACL in SHACL
  • 6.7  Summary
  • 6.8  Suggested Reading
• Chapter 7  Comparing ShEx and SHACL
  • 7.1  Common Features
  • 7.2  Syntactic Differences
  • 7.3  Foundation: Schema vs. Constraints
  • 7.4  Invoking Validation
  • 7.5  Modularization and Reusability
  • 7.6  Shapes, Classes, and Inference
  • 7.7  Violation Reporting and Severities
  • 7.8  Default Cardinalities
  • 7.9  Property Paths
  • 7.10  Recursion
  • 7.11  Property Pair Constraints and Uniqueness
  • 7.12  Repeated Properties
  • 7.13  Exactly One and Alternatives
  • 7.14  Treatment of Closed Shapes
  • 7.15  Stems and Stem Ranges
  • 7.16  Annotations
  • 7.17  Semantics and Complexity
  • 7.18  Extension Mechanisms
  • 7.19  Conclusions and Outlook
  • 7.20  Summary
  • 7.21  Suggested Reading
• Appendix A  WebIndex in ShEx
• Appendix B  WebIndex in SHACL
• Appendix C  ShEx in ShEx
• Appendix D  SHACL in SHACL

0.1  Abstract

RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange.

The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models.

At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints.

This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications.

Keywords: RDF, ShEx, SHACL, shape expressions, shapes constraint language, data quality, web of data, Semantic Web, linked data