Codes, Programs, and Departments

Since ADR-002 (Stages 3–4, October 2026) every department and college a report reads comes from institution/<id>/*.csv: programs.csv for program codes (including which are pre-majors and what they lead to), subjects.csv for course subjects, units.csv and colleges.csv for the hierarchy. program_map.qs and R/lists/program_code_maps.R are retired. The three namespaces below still mean what this page says; where it describes the old lists, read ADR-002 and the mapping review guide instead.

Three distinct code namespaces appear across Cedar’s data sources. They look similar — four-letter uppercase abbreviations — but come from different Banner systems and mean different things. Conflating them is the source of most mapping bugs.

The three namespaces

Subject codes

Used in the DESRs (course section reports) and in cedar_sections. Identify the subject area listed on a course section — the prefix in a course number like HIST 101 or GEOG 250.

Examples: HIST, GEOG, SOC, RLST, PHYC, ASTR, ENVS

Subject codes represent how courses are listed, not which department owns them. GEOG sections belong to the Geography and Environmental Studies dept (GES). PHYC and ASTR sections both belong to Physics (PHYS). There is no field in the DESRs data that says which department a section belongs to — that relationship exists only in subj_to_dept.

Program codes

Used in the academic studies report and in cedar_programs. Identify a specific academic program a student is enrolled in.

Examples: HIST, GEOG, RLST, PSY, SOC, CRWR, INTS, JRMC, COM

A program code identifies the degree or certificate a student is pursuing. Multiple program codes can belong to the same department: CRWR, ENGL, ENGS, ENGP all belong to the English department (ENGL); COM, JRMC, JOUR, CJ all belong to the Communication and Journalism department (CJ).

Department codes

Cedar’s organizational identifier for an academic department. Used in cedar_sections$department, cedar_programs$dept_code, and throughout the analysis pipeline.

Examples: HIST, GES, PHYS, ENGL, CJ, PSYC, SOCI

Department codes are not a raw Banner field — they are Cedar’s computed grouping. Some happen to match a program code (HIST, ANTH, ECON), some don’t exist as program codes at all (GES aggregates GEOG + SUST programs; no GES program exists in Banner).

Where each code appears

Source	Code type	Column(s)
DESRs / `cedar_sections`	subject	`subject`, `subject_course`
Academic studies / `cedar_programs`	program	`program_code`
`cedar_programs` (computed)	department	`dept_code`
`cedar_sections` (computed)	department	`department`

How departments are derived

For cedar_programs (program data)

At transform time, transform-to-cedar.R parses Banner program_code values into major_code, college_code, and dept_code using the catalog files in R/lists/:

program_code → major_code → major_college_to_dept / subj_to_dept / major_to_dept → dept_code
  BA-RLST-AS →   RLST     →                 RLST = RELG                         → RELG
  BA-JRMC-AS →   JRMC     →                 JRMC = CJ                           → CJ
  BA-CRWR-AS →   CRWR     →                 CRWR = ENGL                         → ENGL
  BA-GEOG-AS →   GEOG     →                 GEOG = GES                          → GES

Once cedar_programs.qs is saved, dept_code is on every row. No lookup is needed at runtime — the app reads it directly.

The same catalog also builds runtime lookup vectors used when the app needs the reverse question, “which program codes belong to this department?” For example, Dept Trends > Credit Hours uses major_to_dept to classify home majors versus outside majors.

A program with no confirmed row in programs.csv has no department: it is listed on Admin > Data & Usage > Mappings until someone decides it, never given a department named after its own code. Programs no department owns (Non-Degree, Undecided) are basis = no_unit rows.

For cedar_sections (course data)

DESRs have no department field. The subject code is the only organizational identifier on a course section. At transform time, subj_to_dept translates:

subject → subj_to_dept → department
  GEOG  →   GEOG = GES    →    GES
  RLST  →   RLST = RELG   →   RELG (courses use RLST; students use RLST program)
  PHYC  →   PHYC = PHYS   →   PHYS
  SOC   →   SOC  = SOCI   →   SOCI

This is the one lookup table that cannot be derived from the data. There is no field in DESRs or any other source that records which department owns a course section. subj_to_dept encodes institutional knowledge that exists only in this file.

Department display names

Given dept_code, the display name (e.g., “Geography and Environmental Studies” for GES) is derived at transform time and stored in cedar_lookups$dept_name_lookup.

The derivation rule: for each dept_code, find the program in cedar_programs where program_code == dept_code. That program’s program_name is the canonical department name.

This works for most departments:

HIST → program HIST → "History"
ANTH → program ANTH → "Anthropology"
ENGL → program ENGL → "English"

It breaks for five departments where no program code equals the dept code:

dept_code	reason	override needed
`GES`	aggregates GEOG + SUST; no GES program exists	`"Geography and Environmental Studies"`
`ISI`	students use program code INTS, not ISI	`"International Studies"`
`PSYC`	students use program code PSY, not PSYC	`"Psychology"`
`RELG`	students use program code RLST, not RELG	`"Religious Studies"`
`SOCI`	students use program code SOC, not SOCI	`"Sociology"`

These five, plus six optional editorial refinements (e.g., “Physics and Astronomy” instead of “Physics”), are maintained in dept_display_names in R/lists/mappings.R.

What lives where

`institution/<id>/programs.csv`

One row per program code (optionally per college): its unit, whether it is a pre-major, the program it leads_to, and why. It replaced premaj_canon, xvar_explicit, extra_p2d, ad_major_to_dept and allowed_unmapped_program_codes at ADR-002 Stage 4. See institution/unm/README.md for its columns.

`R/lists/catalog_lookups.R`

Lookup	Purpose	When used
`subj_to_dept`	subject code → dept_code	transform time and runtime helpers
`major_college_to_dept`	`major_code:college_code` → dept_code	transform time; most precise program lookup
`major_to_dept`	major_code → dept_code	transform time fallback; runtime reverse lookup
`dept_code_to_name`	dept_code → dept_name	display

`institution/<id>/` text maps (read by `R/lists/mappings.R`)

File	Map	Purpose	When used
`source_organizations.csv`	`hr_org_desc_to_dept`	HR org description → unit code	faculty data
`program_names.csv`	`major_name_to_major_code`	program name → program code	transform, when an export has no code column
`program_name_aliases.csv`	`program_name_aliases`	variant name → canonical program_name	transform

`data/cedar_lookups.qs` (built at transform time)

Lookup	Content	Used by
`dept_name_lookup`	dept_code → dept_name (31 rows)	department dropdown in UI
`dept_lookup`	HR/legacy string → dept_code	historical compatibility
`program_name_lookup`	program_name string → dept_code	legacy report ingestion

Runtime (Shiny app)

The app usually reads cedar_programs$dept_code directly from the .qs file. A small number of runtime views also load catalog lookup vectors for reverse questions, such as identifying all home-major codes for a department. These runtime vectors are validated at load time; invalid and unmapped rows are excluded from lookup vectors and surfaced as mapping issues in the Admin page.

Could we simplify further?

Short answer: yes, the current system is close to minimal — one more step is possible.

What’s already data-driven:

dept_code on cedar_programs rows — stored in the .qs, no runtime lookup
Department display names — derived from program_name where program_code == dept_code, stored in cedar_lookups.qs
Which departments appear in the dropdown — derived from unique dept_code values in cedar_programs

What still requires hand-maintained review:

subj_to_dept — irreducible, no data source provides this
programs.csv — every program code’s unit, pre-major flag and target, reviewed row by row
dept_display_names — could be reduced to the 5 required entries (removing editorial refinements like “Physics and Astronomy”)

The irreducible minimum: subj_to_dept. This is the only map that encodes information genuinely absent from all data sources. Everything else is either derived at transform time and stored in the .qs files, or could be.