INTELCOM ● Data Tools

Five browser tools for building and running the unified data standard. Each is a single HTML file with no dependencies — they work opened straight from disk and from a static host alike, and nothing you load ever leaves your machine. The two visual tools share one file, node-graph.js, which draws every tree and graph.

JSON ● Workbench

Edit, inspect and convert the records themselves.

View & edit as text or as a collapsible tree, with inline editing, add/delete/reorder and undo
Verify syntax with line and column, and validate against a JSON Schema — cross-file $ref included
Convert to and from CSV and XML
Query with JSONPath-lite, and read metrics: shape, type spread, per-field fill rates
Records tab with a schema-generated form for adding, editing and deleting entries

Reach for this when the thing you are working on is the data.

Open Workbench →

Schema ● Studio

Keep every schema coordinated with the master.

Matrix of properties against schemas, resolved through allOf and $ref, so inherited fields show up too
Edit any property in place, and push the same definition into several schemas at once
Side by side raw editors, two to four panes, with synced scrolling
Diff any two files path by path
Check for dangling $refs, duplicate $ids, fields the master would reject, and properties worth promoting into it

Reach for this when the thing you are working on is the shape.

Open Studio →

Data ● Mapper

Migrate a source system into the new standard.

Read CSV, TSV, JSON, NDJSON and SQL dumps — columns from CREATE TABLE, rows from INSERT
Map field to field, with auto-matching on names and synonyms, and a live result for row 1
Transform with dates, splits, lookups, templates, coalesce, lat/lon pairs, generated ids
Preview the output validated against the target schema, problems listed by row and path
Save mappings to a library and export them as files you can commit

Reach for this when the thing you are working on is the move.

Open Mapper →

Taxonomy ● Studio

Build the vocabularies everything is classified by.

SKOS model — prefLabel, altLabel, notation, broader, related, concept schemes
Import SKOS JSON-LD, flat or nested JSON, or CSV — including breadcrumb A > B > C columns
Visualise as tree, radial or outline, with collapsible branches
Crosswalk to other vocabularies — ETIM, UNSPSC, NAICS — with the SKOS matching predicates
Export SKOS JSON-LD, flat/nested JSON, CSV, or MDM term records

Reach for this when the thing you are working on is the vocabulary.

Open Taxonomy →

Hierarchy ● Explorer

See the shape of records that point at each other.

Any parent field — parent_id, manager_id, father_id, or a relations[] rel
Org charts, family trees, category trees, bills of materials from the same picker
Colour by any field, with a second relation drawn as dashed extra links
Focus a subtree, follow breadcrumbs, inspect the full record
Safe on bad data — cycles and orphans are detected, broken and listed, never hung on

Reach for this when the thing you are working on is the structure.

Open Hierarchy →

How they fit together

Schema Studio — settle the target shape, and keep the type schemas in step with record.schema.json.
Taxonomy Studio — settle the vocabularies those schemas classify against, and align them with outside standards.
Mapper — point each legacy source at that shape, save the mapping, run the migration.
Workbench — open the result, check it, fix what needs fixing, and maintain it from there.
Hierarchy Explorer — look at how the migrated records actually hang together, and find the records that do not.

Schemas live in mdm-v1/ — the master envelope in record.schema.json, the per-type schemas in types/, worked examples in examples/. All three tools load them by file or drag-and-drop; the Studio can also open the whole folder at once. Each tool keeps its working state in browser storage, so a reload does not lose anything, and that storage is per-origin — a local copy and a hosted copy keep separate state.