Ten multiple choice questions that are intended to test one's knowledge after reading and viewing the materials in Module 1: Introduction and Application Scenarios.
Keywords: Mashup, SPARQL, Graph, Triple, HTTP URIs, RDF, XML, Web of Data, Semantic Web, Linked Data Principles, Linked Data
Publisher: EUCLID Project
Time required: P10M
Educational use: assessment
Educational audience: student
Interactivity type: active
- Articulates differences between the RDF abstract data model and the XML and relational models.
- Knows the subject-predicate-object component structure of a triple.
- Understands blank nodes and their uses.
- Understands the difference between literals and non-literal resources.
- Understands the use of datatypes and language tags with literals.
- Correctly uses sub-property relationships in support of inference.
- Demonstrates a working knowledge of the forms and uses of SPARQL result sets (SELECT, CONSTRUCT, DESCRIBE, and ASK).
- Understands that a SPARQL query matches an RDF graph against a pattern of triples with fixed and variable values.
- Understands the basic syntax of a SPARQL query.
- Differentiates hierarchical document models (eg, XML) and graph models (RDF).
- Knows that anything can be named with Uniform Resource Identifiers (URIs), such as agents, places, events, artifacts, and concepts.
- Knows the primary organizations related to Linked Data standardization.
- Knows the SPARQL 1.1 Update language for updating, creating, and removing RDF graphs in a Graph Store
- Understands the difference between SQL query language (which operates on database tables) and SPARQL (which operates on RDF graphs).
- Understands RDF serializations as interchangeable encodings of a given set of triples (RDF graph).
- Understands the role of formally declared domains and ranges for inferencing.
- Uses the SELECT clause to identify the variables to appear in a table of query results.