Build a Learning Map

How does this work?
Authenticated users can assemble nodes from the Competency Index into Learning Maps, which represent logical sequences of competencies for use in defining formal curriculum structures or as personalized pathways created by instructors or learners as records of progress.

To build a Learning Map, select arrows at left to expand nodes of the Competency Index and view any child nodes below them. Select a node's Add to Map >> link to place it in sequence within the Learning Map at right. Continue adding nodes in the sequence that best suits your purpose for the map, then enter a unique name and select Save.

Click the up or down arrows at right of the node listing to modify the sequence, then select Save to update.

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Learning Maps Listing

Learning Map: Competencies for Catalogers

What's This?
Authenticated users can assemble nodes from the Competency Index into Learning Maps, which represent logical sequences of competencies for use in defining formal curriculum structures or as personalized pathways created by instructors or learners as records of progress.
Considers the paradigm shift necessary to catalog to an expanded audience (the Web) as well as technical details involved.

Understands that Linked Data (2006) extended the notion of a web of documents (the Web) to a notion of a web of finer-grained data (the Linked Data cloud).

69 resources

Knows Tim Berners-Lee's principles of Linked Data: use URIs to name things, use HTTP URIs that can be resolved to useful information, and create links to URIs of other things.

0 resources

Knows that Uniform Resource Identifiers, or URIs (1994), include Uniform Resource Locators (URLs, which locate web pages) as well as location-independent identifiers for physical, conceptual, or web r

18 resources

Understands that a "real-world" thing may need to be named with a URI distinct from the URI for information about that thing.

8 resources

Knows the subject-predicate-object component structure of a triple.

46 resources

Understands the difference between literals and non-literal resources.

14 resources

Understands the use of datatypes and language tags with literals.

15 resources

Knows graphic conventions for depicting RDF-based models.

10 resources

Distinguishes the RDF abstract data model and concrete serializations of RDF data.

41 resources

Recognizes that owl:sameAs, while popular as a mapping property, has strong formal semantics that can entail unintended inferences.

13 resources

Identifies resource attributes and relationships between domain entities as candidates for RDF properties.

9 resources

Uses RDF Schema to express semantic relationships within a vocabulary.

53 resources

Coins namespace URIs, as needed, for any new properties and classes required.

14 resources

Knows Simple Knowledge Organization System, or SKOS (2009), an RDF vocabulary for expressing concepts that are labeled in natural languages, organized into informal hierarchies, and aggregated into co

24 resources

Knows SKOS eXtension for Labels, or SKOS-XL (2009), a small set of additional properties for describing and linking lexical labels as instances of the class Label.

4 resources

Managing identifiers (URI)

19 resources

Creating RDF data

44 resources

Cleaning and reconciling RDF data

17 resources

Mapping and enriching RDF data

32 resources

Knows the SPARQL 1.1 Update language for updating, creating, and removing RDF graphs in a Graph Store

32 resources

Understands the difference between SQL query language (which operates on database tables) and SPARQL (which operates on RDF graphs).

43 resources