Metadata builder

Prepare a GLC data package

Metadata Builder Beta

Schema 3.0.2

Getting started with GLC metadata

Make light-exposure and optical-radiation datasets easier to understand, validate, and reuse.

The Global Light Commons (GLC) standard provides a shared structure for describing studies, participants, devices, datasheets, and measurement files for light-exposure and optical-radiation research. This builder guides you through creating a complete metadata package that can accompany your dataset.

Note: Files you select while building the metadata package stay on your computer. They are processed locally in your browser and are not uploaded, transmitted, or stored by this site. Draft metadata are autosaved only in this browser on this device; selected measurement-file contents are not stored.

Why researchers use GLC

GLC metadata makes wearable light-exposure and optical-radiation datasets easier to review, combine, and reuse.

Easier collaboration Study, participant, device, and dataset information can be found in predictable places.
Validation-ready Links between files can be checked automatically to catch common mistakes.
Reusable data Future users can understand what was measured, with which device, and under what conditions.

What you’ll create

A GLC package links the key parts of a wearable light-exposure or optical-radiation dataset.

Study Participants Devices & Datasheets Dataset Files

The resulting metadata package can be validated and shared alongside your data.

How the builder works

Work through the pages in order, import existing metadata when available, then export a package for validation.

  1. Describe your study
  2. Add participants
  3. Document devices and datasheets
  4. Register dataset files
  5. Export a package

Expected time: 5–30 minutes.

Generated files and package structure

The builder generates the package descriptor, resource metadata, versioned schemas, and a short README. Add the referenced data files at the paths declared in data/datasets.json before validation. 

glc-metadata-package/
├── datapackage.json
├── README.txt
├── schemas/
│   └── 3.0.2/
│       ├── glc-dp-profile.json
│       └── … resource schemas
└── data/
    ├── study.json
    ├── participants.csv
    ├── participant_characteristics.csv  (when provided)
    ├── devices.json
    ├── device_datasheet.json
    ├── datasets.json
    └── datasets/
        └── your-measurement-files.csv    (add after export)
study.jsonWhat was the study, who contributed, and which dataset records belong to it?
participants.csvWho or what was measured?
participant_characteristics.csvWhich optional participant-level characteristics help interpret the measurements?
devices.jsonWhich devices were used and which datasheets describe them?
device_datasheet.jsonWhat sensor, calibration, channel, or spectral details are needed to interpret the device output?
datasets.jsonWhere are the measurement files, what columns do they contain, and how do they link to study, participant, and device IDs?

Useful resources

Learn more about the Global Light Commons initiative View human-readable details of the GLC datapackage structure
1

Project setup

Choose the release version and package-level settings.

Start a new package

Choose a schema version and enter the new package’s name and title.

Continue existing work

Choose the option that matches what you previously saved.

Open an existing GLC package

Select a package folder containing separate GLC metadata files.

Looks for datapackage.json and the metadata resources at the folder root or inside data/.

Resume a builder draft

Select the single glc-builder-project.json file previously saved by this builder.

2

Study

Core fields from study.schema.json. Dataset IDs will be filled from the dataset step.

Optional: import an existing study.json to pre-fill this page.

Study groups

Optional repeatable groups from study_groups. Select the dataset records that belong to each group.

Study contributors

Optional embedded contributors from contributor.schema.json. Add rows manually, or import a CSV/TSV/JSON file to fill the table.

Import replaces the contributor rows below. For CSV/TSV, use these column names: contributor_full_name, contributor_roles, contributor_email, contributor_orcid, contributor_institution_name, contributor_institution_city, contributor_institution_country. Roles can be separated with semicolons. JSON can be either contributors.json or study.json with study_contributors.

Download metadata:
Reference schemas:
3

Participants

Add participant rows for participants.csv and optional characteristics.

Participant roster

Required rows for participants.csv.

Optional: import participants.csv or participants.json. Expected fields: participant_internal_id, participant_age, participant_sex, participant_gender.

Participant characteristics

Optional long-format rows for participant_characteristics.csv.

Optional: import participant_characteristics.csv or JSON. Expected fields: participant_internal_id, participant_characteristic_name, participant_characteristic_value, participant_characteristic_unit, participant_characteristic_description.

Download metadata:
Reference schemas:
4

Devices

Add device records and the datasheets they reference.

Device inventory

Required records for devices.json.

Optional: import devices.json or a CSV/TSV device table. Expected fields: device_internal_id, device_manufacturer, device_model, device_serial_number, device_calibration_date, device_firmware_version, device_datasheet_id, device_sensors. Sensor entries can use sensor type | sensor datasheet id, separated by semicolons.

Datasheet IDs are pending cross-references: if the matching datasheet has not been added yet, leave the field blank or keep the imported ID and complete the datasheet section below.

Device datasheets

Add device or sensor datasheet records referenced by devices.

Optional: import device_datasheet.json, sensor_datasheet.json, or a CSV/TSV datasheet table. Expected fields include datasheet_id, datasheet_manufacturer, datasheet_type, datasheet_model, datasheet_calibration_interval, spectral sensitivity, calibration fields, and channels.

Download metadata:
Reference schemas:
6

Dataset record ?

One dataset record represents one participant dataset. Cross-reference fields use earlier pages.

Dataset or file group?

Use a new dataset record for a different participant or measurement context. Use a file group for each set of same-structure files, including files from different devices, locations, sampling intervals, or collection instructions within that context.

Example: wrist light data, chest light data, and a corresponding wear log can be bundled in one dataset as separate file groups when they belong to the same recording period.

Optional: import an existing datasets.json. Multiple dataset records are imported as separate participant-level records.

Dataset records ?

Each record should describe one participant or one non-participant collection context.

5a

Dataset file assistant ?

Each file group describes one set of same-structure files for this participant.

No file selected yet.

Variable terms for this file group

These terms populate the semantic-term dropdowns for variables in the active file group. other is always included.

Datetime for this file group

Use column metadata when the file contains date/time columns. If it does not, declare the collection date/time instead.

5b

Detected variables

Edit labels, units, calibration notes, semantic terms, and tick primary variables.

Select a file to detect columns.
Download metadata:
Reference schemas:
7

Export package

Download individual metadata files or a metadata package zip.

The zip includes generated metadata files and schemas. It does not include the original data files referenced by datasets.json.

Missing-value convention: optional properties with no value are omitted from exported JSON rather than written as null, an empty string, or an empty array.

The editable project backup preserves form entries, detected headers, and selected file names, but browsers do not allow it to retain access to the original measurement files.