F1. (meta)data are assigned a globally unique and eternally persistent identifier
There are many resources created by the ARDC on the topic of metadata. See also:
The ARDC has information on persistent identifiers on three different levels:
- Persistent identifiers: awareness level
- Persistent identifiers: working level
- Persistent identifiers: expert level
It is also a provider of services for minting persistent identifiers of many different kinds (depending on the nature of the data being identified):
- Digital Object Identifier (DOI) System for research data
- Handle minting Service (Identify My Data)
- International Geo Sample Numbers (IGSN)
Complementary to the assignment of persistent identifiers is their proper citation:
F2. data are described with rich metadata
There are several areas complementary to the description of rich metadata:
- Metadata guide
- Digital Object Identifier (DOI) System for research data
- Storing metadata
- Research data for journal editors
- Within 23 (research data) things:
See Geospatial data and metadata for a domain specific discussion of metadata.
F3. (meta)data are registered or indexed in a searchable resource
The ARDC provides one of many different searchable indexes of (meta)data:
- Research Data Australia
- Research grants and projects: ANDS Discovery service for Australian funded grants and projects
See also these complementary resources:
- Publishing data
- Metadata guide
- Persistent identifiers: expert level
- Data reuse
- Data discovery and access
- Storing metadata
- Geospatial data and metadata
- Thing 4 - Data Discovery
- Data sharing considerations for Human Research Ethics Committees (HRECs)
F4. metadata specify the data identifier
Complementary to the inclusion of the data identifier in the metadata is:
Thing 8 includes an example data record from the CSIRO that demonstrates this principle. Note that metadata can be stored in many places, and that this principle might apply to object-level metadata stored within a data file as well.
Additional resources on Findability
The following resources contain detail relevant to or are complementary to ensuring findability:
- 23 (research data) things
- Data storage
- Data reuse
- Data capture
- Defining a data collection
- Citation and identifiers
- Publishing data
- Data and journals
- Curation continuum
- Data policies and journals (Research Data for Journal Editors Guide)
- Creating a data management framework (incorporating the capability maturity model)
- Research data management in practice: outlines the roles and responsibilities of institutions and researchers
- Australian Research Council (ARC) applications - filling in the data management section