CTDL Profile of ASN-DL (CTDL-ASN) Handbook

Creative Commons License

How the CTDL-ASN Profile Works

In order to describe competency frameworks in as interoperable a manner as possible, Credential Engine will build on an existing description language called Achievement Standards Network Description Language (ASN-DL) that was developed by the U.S. National Science Foundation (NSF) between 1999-2013 for the description of logically related sets of knowledge, skill and ability assertions. The ASN-DL is designed using the W3C's Resource Description Framework (RDF) for describing Linked Data on the open Web. The CTDL-ASN Profile adopts in full the set of properties and classes defined in the ASN-DL and will be judiciously extending that set through property and class refinements as well as the addition of new properties and classes defined in CE's own Credential Transparency Description Language (CTDL).

CTDL-ASN Profile Specification

Basic ASN Architecture

The ASN Description Language (ASN-DL) is made up of two fundamental entities: (1) the Standards Document—a competency framework as a whole, and (2) the Statement—the individual assertions of knowledge, skill, and abilities of which a Standards Document is comprised. These two entities—documents and statements—are modeled in terms of an entity-relationship model (ER) and embodied as a directed graph using W3C's Resource Description Language (RDF). An extensible set of structural and semantic relationships between the ASN's primary competency framework entities—the standards document entity and its atomic statement entities—have been defined.

The following diagram illustrates the use of the Standards Document and Statement entities using an example encoding of a competency in the Degree Qualification Profile (DPQ).

Note that each entity has been assigned a unique identifier in the form of a Uniform Resource Identifier (URI) using the HTTP protocol. This means that each resource is a "first class citizen" on the open Web and can be openly referenced and linked too.

The diagram above illustrates what is called an ASN Taxon Path which is defined as a single traversal of a branch of a competency framework--here from the root (i.e., the standards document description) to a leaf (i.e., a statement at some arbitrary level in the branch hierarchy). Just as the atomizing of the text de-contextualizes the standard document's member statements for unique identification, description, and reference, the notion of the ASN Taxon Path re-contextualizes those statements. This re-contextualization is fundamental to human comprehension of the competencies since many atomic statements, standing alone, convey insufficient meaning.

For the purpose of illustrating the notion of the ASN entities and relationships, the descriptive properties of the ASN Taxon Path members have been kept to a minimum. In fact, metadata describing additional attributes of a competency (e.g., skills embodied, proficiency levels, etc.) are possible. Documentation of the properties and classes of the CTDL-ASN Application Profile are available.

Cross-Jurisdiction Mapping

Because every ASN Standards Document resource and every ASN Statement resource is identified by URI, competency frameworks and their individual competencies can be mapped to each other regardless of where the Frameworks are located on the open Web, the following figure asserts an exact match relationship between a competency in a Brandman University competency framework and a competency in the Degree Qualification Profile (DQP).

The ASN-DL offers a range of properties to express different degrees of similarity between competencies; additional mapping properties can be defined in the CTDL-ASN Profile as needs arise.

Extending Granularity of a CTDL-ASN Taxon Path

For some uses of a particular ASN-modeled competency framework, the level of granularity of leaf competencies in the canonical version may not be sufficiently granular. For example, a specific competency may aggregate several skills that some 3rd party creator of assessment instruments may wish to handle separately. The ASN-DL model makes it possible to increase the granularity of expression of a competency by distinguishing between canonical (original) competencies as promulgated by the authors of the framework and non-canonical (derived) statements added by 3rd parties. Derived 3rd party ASN statements “refine” original statements by making more specific granular assertions. Since derived statements are treated as first-class entities in the ASN, they are assigned URIs in the same manner as original statements and clearly identified as “derived”. Of course, derived statements can be easily eliminated, not display, or treated in some manner as simple annotations by services consuming the standards documents.

As a result of this extensibility, any 3rd party may create more granular statements without authorization in its own 3rd party namespace and relate those statements to the canonical (original) statements while identifying such competencies as "derived". Of course, since 3rd party statements are in different namespaces than the canonical version, 3rd party provenance is machine identifiable. The following figure illustrates this 3rd party "annotation" process.

Expressing "Strength of Fit" (degrees of similarity)

Frequently, it is useful to map from one resource to another to express the level of useful similarity between the two nodes. Such mappings may be from one competency framework node to another node in the same or another framework (i.e., competency-to-competency), or to map from a learning resource to a competency node (i.e., learning resource-to-competency). In ASN, the utility of that mapping is a function of its "strength of fit". The ASN ontology provides an array of properties that express this strength of fit relationship in competency-to-competency mappings (called "alignments" in ASN) and learning resource-to-competency mappings (called "correlations" in ASN).

The table below includes brief descriptions of the current competency-to-competency mapping predicates. For the full description of both the competency-to-competency mapping properties and the learning resource-to-competency mapping properties, see CTDL-ASN Profile.




Align To

A target competency to which the described competency is aligned. Note: An "alignment" is a general assertion of some degree of unidentified equivalency between the two resources being aligned. (Inverse of Aligned From)

Align From

A target competency to which the described competency is aligned. Note: An "alignment" is a general assertion of some degree of unidentified equivalency between the two resources being aligned. (Inverse of Aligned To)

Broad Alignment

The target competency covers all of the relevant concepts in the competency being described as well as relevant concepts not found in the competency being described.

Exact Alignment

The relevant concepts in both the described and target competencies are coextensive.

Major Alignment

Major overlap of relevant concepts between the described and target competencies.

Minor Alignment

Minor overlap of relevant concepts between the described and target competencies.

Narrow Alignment

The competency being described covers all of the relevant concepts in the target competency as well as relevant concepts not found in the target competency.

Prerequisite Alignment

The target competency is a prerequisite to the competency being described.