One row per framework in the cybedtools corpus. Counts
(organizing_unit_count, element_count_strict,
element_count_with_examples, example_count,
elements_per_organizing_unit_strict,
elements_per_organizing_unit_with_examples) are computed from the
staged combined N-Triples graph at package-build time via
data-raw/build-framework-summary.R. Display name, framework type
(workforce vs pedagogy), and license are hand-curated because they
originate outside the JSON-LD graph.
Format
A tibble with 8 rows and 11 columns.
- framework_slug
Character. Stable slug used as the URI tail (e.g.,
"nice-v2","sfia-9").- framework_name
Character. Short display name suitable for tables and prose.
- framework_type
Character. Content-focus classification, one of
"workforce"or"pedagogy". Independent of the structuralcybed:Rolevscybed:OrganizingUnitdistinction.- jurisdiction
Character. One of
"US","EU", or"global".- organizing_unit_count
Integer. Distinct top-level enumerated units bound to the framework via
cybed:partOf. For NICE / DCWF / ECSF this is work roles or work profiles; for SFIA, skills; for Cyber.org K-12, grade-band x sub-concept cells; for CSTA, level-concept buckets; for CSEC2017, Knowledge Areas; for DigComp 2.2, competence areas. Cross-framework comparison viacybed:OrganizingUnit.- element_count_strict
Integer. Distinct framework-as-specified elements (parents plus
cybed:Subpointchildren). Excludescybed:Exampleinstances. Use this column for headline density comparisons across frameworks.- element_count_with_examples
Integer. Distinct elements including
cybed:Exampleinstances (Cyber.org K-12 and CSTA Clarification-statement scaffolding). For frameworks without Examples this equalselement_count_strict.- example_count
Integer. Distinct
cybed:Exampleinstances. Non-zero for Cyber.org K-12 and CSTA only; zero for the other six frameworks.- elements_per_organizing_unit_strict
Numeric.
element_count_strict / organizing_unit_count, rounded to one decimal. The headline density figure used in the README.- elements_per_organizing_unit_with_examples
Numeric.
element_count_with_examples / organizing_unit_count, rounded to one decimal. Used in the cross-framework-analysis vignette to show how Examples inflate Cyber.org K-12 and CSTA's apparent specification density.- license
Character. Distribution license as published by the framework owner.
Source
Computed from the eight-framework combined graph produced by
scripts/025-export-ntriples.R. See
data-raw/build-framework-summary.R.
Details
Two element-count columns are surfaced: element_count_strict counts
parents plus parsed Subpoints (framework-as-specified content);
element_count_with_examples additionally counts the Cyber.org K-12
and CSTA Clarification-statement Examples (pedagogical scaffolding,
not enumerable sub-standards). For frameworks that emit no Examples
(NICE, DCWF, ECSF, SFIA, CSEC2017, DigComp 2.2) the two columns are
equal. The README headline "density spread" finding uses the strict
count for cross-framework parity; the cross-framework-analysis vignette
shows both columns side-by-side and discusses the encoding heterogeneity
that drives the difference.
The framework_type column denotes content focus (workforce
competencies vs educational standards), not the structural distinction
that drives cybed:Role assertion. SFIA carries framework_type == "workforce" because it specifies workforce skills, but its parent
units assert cybed:OrganizingUnit only (not cybed:Role) because
SFIA enumerates skills rather than work roles. For structural
questions, query cybed:Role and cybed:OrganizingUnit directly.
Examples
framework_summary
#> # A tibble: 8 × 11
#> framework_slug framework_name framework_type jurisdiction
#> <chr> <chr> <chr> <chr>
#> 1 nice-v2 NICE v2 workforce US
#> 2 dcwf-v5.1 DCWF v5.1 workforce US
#> 3 ecsf-v1 ECSF v1 workforce EU
#> 4 sfia-9 SFIA 9 workforce global
#> 5 cyberorg-k12-v1.0 Cyber.org K-12 v1.0 pedagogy US
#> 6 csta-2017 CSTA K-12 CS (Rev 2017) pedagogy US
#> 7 csec2017-v1 ACM/IEEE CSEC2017 pedagogy global
#> 8 digcomp-2.2 DigComp 2.2 pedagogy EU
#> # ℹ 7 more variables: organizing_unit_count <int>, element_count_strict <int>,
#> # element_count_with_examples <int>, example_count <int>,
#> # elements_per_organizing_unit_strict <dbl>,
#> # elements_per_organizing_unit_with_examples <dbl>, license <chr>
subset(framework_summary, framework_type == "workforce")
#> # A tibble: 4 × 11
#> framework_slug framework_name framework_type jurisdiction
#> <chr> <chr> <chr> <chr>
#> 1 nice-v2 NICE v2 workforce US
#> 2 dcwf-v5.1 DCWF v5.1 workforce US
#> 3 ecsf-v1 ECSF v1 workforce EU
#> 4 sfia-9 SFIA 9 workforce global
#> # ℹ 7 more variables: organizing_unit_count <int>, element_count_strict <int>,
#> # element_count_with_examples <int>, example_count <int>,
#> # elements_per_organizing_unit_strict <dbl>,
#> # elements_per_organizing_unit_with_examples <dbl>, license <chr>