Skip to main content

INTERSECT Scientific Data Layer (SDL)

Connecting scientific data with meaning – A flexible and semantic ecosystem for modern science.

GitHub Logo

New Platform Survey

This survey is intended to be interactive and ontology-aligned, useful for a web form or CLI questionnaire. It is broken down into logical sections, and can later be translated this into SHACL, RDFa, or form components in a UI.

🔍 Survey: Describe a Scientific Sensor Platform (SSN)

1. General Platform Information

  • Platform Name (dcterms:title)

  • Platform Identifier (URI) (auto-generated or user-defined)

  • Description (dcterms:description)

  • Operator / Responsible Agent (prov:wasAssociatedWith)

  • Geographic Location

    • Site / Facility Name
    • Latitude / Longitude
    • Elevation (optional)
    • Spatial Coverage Geometry (e.g. GeoJSON or WKT)

2. Deployment Context

  • Is this platform deployed? (Yes/No)

  • If yes:

    • Deployment start date/time (prov:startedAtTime)
    • Deployment end date/time (prov:endedAtTime) (optional)
    • Deployment location (as above)
    • Deployment Purpose / Campaign (e.g. "Soil Carbon Monitoring 2024")

3. Observed Phenomena / Features of Interest

For each:

  • Feature of Interest (e.g., "Soil Moisture", "Air Temperature") (sosa:hasFeatureOfInterest)
  • Units of Measurement (QUDT, OM, etc.)
  • Frequency of Observation
  • Sampling Strategy (random, regular, continuous)

4. Input and Output Data

Inputs:

  • Input Data Types (e.g. config files, control signals, reference standards)
  • Input Formats (CSV, JSON, XML, etc.)
  • Input Channels (e.g., USB, Serial, Network)

Outputs:

  • Output Data Types (e.g., time series, images, binary logs)
  • File Formats (CSV, HDF5, TIFF, NetCDF, proprietary)
  • Output Channels (e.g., SD card, MQTT, HTTP API)

5. System Composition

Add each ssn:System used:

For each system:

  • Name / Identifier
  • Type (Sensor, Actuator, Control System, etc.) (rdf:type)
  • Description
  • Manufacturer
  • Model Number
  • Location on Platform (if fixed)
  • Operates continuously or triggered?
  • Consumes Power? If yes, estimate (voltage/current or W)

6. Sensors

For each sensor (a subtype of ssn:System):

  • Sensor Name
  • What does it observe? (sosa:observes)
  • Output Format / Units
  • Calibration Info (if any)
  • Data Rate / Sampling Frequency
  • Linked to what system/platform? (ssn:isHostedBy)

7. Actuators

For each actuator (optional):

  • Actuator Name
  • Function / Role (e.g. valve control, pump operation)
  • Controlled Property (e.g., flow rate, temperature)
  • Input Type / Signal
  • Controlled by what system? (ssn:hasSubSystem or external agent)

8. Networking and Control

  • Does the platform include an onboard computer or controller?

  • If yes:

    • OS / Firmware version
    • Interfaces (Serial, USB, Wi-Fi, etc.)
    • Protocols supported (MQTT, HTTP, Modbus, etc.)

  • Remote access supported?

  • How is data transmitted? (Real-time, batch, offline upload)

9. Power and Environmental

  • Power source(s) (battery, solar, AC, hybrid)
  • Environmental enclosure type (IP rating if applicable)
  • Operating temperature/humidity range
  • Other constraints (e.g., mobile, mounted on UAV, waterproof)

10. Maintenance and Provenance

  • Date of last calibration
  • Maintenance interval
  • Last updated by (agent/organization)
  • Additional provenance notes (prov:wasGeneratedBy, prov:wasAttributedTo)

11. Linked Data / Ontologies

  • Do you use any standardized vocabularies?

    • QUDT, OM, ENVO, SAREF, etc.

  • Would you like to upload ontology-aligned metadata?

  • Associated Resources:

    • Datasets (dcat:Dataset)
    • Distribution endpoints (dcat:Distribution)
    • API URL or SPARQL endpoint
On this Page: