Google spreadsheet for your contributions

[Ge Peng]

Dear Makx,
I have entered the proposed indicators and their maturity levels for F1
(PI/PIL_11), F2/R1 (PI/PIL_20), A1 (PI/PIL_46), and I1 (PI/PIL_85) (also
see the details below). I’ll be happy to work with the editorial team and
the WG members to further improve those indicators and their maturity
levels if needed.
With respect to describing the maturity of the FAIR Data Maturity
Assessment, one potentially way to do so is to use the following maturity
assessment categories from Peng et al. (2018), Data Science Journal:
Category Number
Description
Category 1
No assessment done.
Category 2
Self-assessment—preliminary evaluation carried out by an individual for
internal or personal use; abiding to non-disclosure agreement.
Category 3
Internal assessment—complete evaluation carried out by an individual
non-certified entity (person, group, or institution) and reviewed
internally with the assessment results (ratings and justifications)
publicly available for transparency.
Category 4
Independent assessment—Level 3 + reviewed by an independent entity, that
has expertise in the maturity model utilized for the evaluation.
Category 5
Certified assessment—Level 4 + reviewed and certified by an established
authoritative entity. Maturity update frequency is defined and implemented.
Hope it helps. Please feel free to let me know if I need to modify the way
I input my entries or there is anything else I can do to help.
Looking forward to seeing the outcomes of this team effort.
Best regards,
Ge Peng (Peng)
—————–
Maturity levels for
F1. (meta)data are assigned a globally unique and eternally persistent
identifier.
Proposed Indicator: PI_11: The state of meta(data) assigned a globally
unique and eternally persistent identifier.
Maturity Levels: PIL_11:
Level 1: No unique identifiers assigned for dataset-level metadata record
and dataset, or information unknown;
Level 2: Internal unique identifiers assigned for dataset-level metadata
record and dataset;
Level 3: Dataset assigned a globally unique, persistent identifier but not
resolvable (e.g., UUID);
Level 4: Dataset assigned a globally unique, persistent, and resolvable
identifier (e.g., DOI);
Level 5: Level 4 + capturing dataset versioning
Maturity levels for:
F2. Data are described with rich metadata (defined by R1);
R1. Meta(data) are richly described with a plurality of accurate and
relevant attributes
Proposed Indicator: PI_20: The state of metadata
Maturity Levels: PIL_20
Level 1: Dataset-level metadata not publicly available, discoverable,
and/or integrable;
Level 2: Dataset-level metadata discoverable with a landing page displaying
basic characteristics of dataset and information on data accessibility,
conforming to domain-specific metadata standards and integrable;
Level 3: Dataset-level metadata discoverable with a resolvable dataset DOI
landing page displaying complete characteristics of the dataset, capturing
or linking to descriptive data product information including data
collection and processing steps, error sources and uncertainty information,
conforming to national metadata standards;
Level 4: Level 3 + Provenance and quality descriptive information,
conforming to international metadata standards; Software package available
and linked for transparency;
Level 5: Level 3 + standard-based and interoperable provenance and quality
descriptive information; Version-controlled software package publicly
available and linked for traceability (e.g., at a GitHub) plus complete
run-time system information for reproducibility.
(Metadata entities for capturing basic and complete characteristics of
datasets will likely be domain-specific and potentially defined by
individual disciplines until a consensus can be reached universally –
across global and disciplines. Example of international metadata standards
on geographic information are ISO 19115-* and ISO 19157-*. An example of
provenance standard is W3C PROV. The current definitions do not address the
file-level metadata which may need to be included at Level 3 or higher
maturity levels.)
Maturity levels for:
A1: Meta(data) are retrievable using by their identifier using a
standardised communications protocol
Proposed Indicator: PI_46: The state of data and relevant information being
retrievable
Maturity Levels: PIL_46
Level 1: Person to person or via a private URL link (e.g., email, portable
drive, private ftp site); not publicly available; not searchable;
Level 2: Data publicly available and searchable at the dataset level using
basic domain-specific facets; Basic online services available for data
access in its original format/file(s) (e.g., FTP/HTTP(S) direct file
download);
Level 3: Extensive data services conforming to domain standards available
for data access; conforming to community search and discovery metadata
convention standards; capable of providing other domain-specified output
data format options;
Level 4: Level 3 + visualization or subsetting and aggregation capability
available; data descriptive information (e.g., data collection and/or
processing steps and error sources) including software package available
and accessible;
Level 5: Level 4 + standard-based provenance and quality descriptive
information available, accessible, and interoperable.
Maturity levels for:
I1. (meta)data use a formal, accessible, shared, and broadly applicable
language for knowledge representation
Proposed Indicator: PI_85: The state of data being portable
Maturity Levels: PIL_85
Level 1: Not machine readable;
Level 2: Domain-specific or proprietary machine readable file format;
Level 3: Standard-based, non-proprietary machine readable file format;
Level 4: Level 3 + machine independent, self-describing, and interoperable
file format;
Level 5: Level 4 + analysis ready