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TITLE: FAIR Maturity Indicator MI-R1.3-7a4d616c66-IN_VV_SUBSTANCE_MOS


Ammar Ammar, ORCID:0000-0002-8399-8990

Publication Date: 2021-03-02

Last Edit: 2021-05-03

Accepted: pending

Maturity Indicator Identifier: MI-R1.3-7a4d616c66-IN_VV_SUBSTANCE_MOS

This maturity indicator falls under the FAIR principle R1.3: (meta)data meet domain-relevant community standards

The ID of this MI is composed of the following segments (separated by hyphen):

  1. Acronym for "Maturity Indicator"
  2. The FAIR principle this maturity indicator belongs to
  3. The first 10 characters truncated from the SHA-256 hash of the primary reference DOI of this maturity indicator.
  4. A short name to distinguish the maturity indicator definition file

This MI is to indicate if information on method of suspension is reported by the nano toxicity study data or not.

Maturity Indicator Name: Information on method of suspension is reported by the nano toxicity study

This maturity indicator is extracted from the following paper Title: caLIBRAte nano risk governance D5.3 document on quality criteria for Data Reference Website:

Information on method of suspension: type of used medium, preparation of stock solution, nominal concentration.

To which principle does it apply?


What is being measured?

If information on method of suspension is reported by the nano toxicity study data or not.

Why should we measure it?

Data completeness may be considered to include, amongst other kinds of data and metadata, the extent of nanomaterial characterization, both physicochemical and biological, under a specified set of experimental conditions and time points. It may also encompass the degree to which experimental details are described, as well as the availability of raw data, processed data, or derived data from the assays used for nanomaterial characterization. The caLIBRAte project determined minimum information checklists for the information that should be reported, including the one in this maturity indicator, to determine data usefulness for developing/testing computational models.

What must be provided for the measurement?

If the value is measured and reported in the data, the following field(s) should appear in JSON-LD metadata:

Field Name Alternative terms
method of suspension physicochemical_characterization,

How is the measurement executed?

The method of suspension should be provided in a machine-readable format (JSON-LD) which can be queried using open universal protocol like HTTP.

What is/are considered valid result(s)?

The presence of the field "method of suspension" in the JSON-LD metadata means the measurement is reported which is the valid result.

For which digital resource(s) is this relevant? (or 'all')

For nano toxicity related datasets.

Examples of good practices (that would score well on this assessment)

 	"@context": {
 		"bs": "",
 		"schema": "",
 		"citation": "schema:citation",
 		"name": "schema:name",
 		"url": "schema:url",
 		"variableMeasured": "schema:variableMeasured",
 		"unitText": "schema:unitText"
 	"@type": "schema:Dataset",
 	"name": "Dataset title",
 	"@id": "Dataset DOI",
 	"url": "Dataset URL",
 	"citation": "Dataset Citation/Publication",
 	"variableMeasured": [
 			"@type": "schema:PropertyValue",
 			"name": "method of suspension"