388
Reusability emphasizes that metadata and data are richly described, including a
clear data usage license, detailed provenance, and the use of domain-specific community standards.
The reader will have an easier time both in publishing and accessing FEW systems data by working with vendors and repositories that implement FAIR principles (e.g. Wilkinson et al., 2016). Implementation decisions concerning these FAIR
principles for data publication tend to focus on the choice of a repository for your
data. The Coalition for Publishing Data in the Earth and Space Sciences (COPDESS)
provides some detailed advice on best practices for implementing the FAIR principles for your research project or other data product project—including the selection
of a repository, data and metadata format, compliance with your funding agency’s
data publication requirements, and so on.
1
The Library is the ancient institution that specializes in managing the data life
cycle. Libraries still (mostly) specialize in data as the printed word, and are the classic archetype of a repository for data.
A Repository is generalized library service that curates data and that ideally
provides FAIR data management services. Libraries, journals, web portals, search
services, and agency data services may be examples of repositories, although it is a
rare repository that provides all components of FAIR data management services that
you might require. For instance, it is relatively easy in 2018 to access and catalog
data using search services, but it is still challenging to find a high-quality repository
that is willing to permanently curate your datasets at no charge, and it is rare to find
a repository that will donate consulting and expert services to help you reformat,
metadata-markup, and package your data properly to comply with FAIR principles.
Different types of repositories and data entities provide different services and
serve different roles. If you are working or studying at a university, your library’s
role is to assist you not only with search and access to information but also with the
curation of data from your research. However, many university libraries lack the
specialized capacity to do this. Journals are rapidly transitioning from publishers of
the written word into full-service knowledge and data curation services and repositories, but some are further along this path than others as of 2018. In many cases,
journals require scholars to curate their data elsewhere. If you work for a state or
federal agency, in most cases your agency has its own funding and services to curate
and provide access to data—but only to those data originated by that specific agency.
Private consultancies and data services may provide excellent data products, but
these tend to exist behind an access paywall and tend to be targeted to provide
narrow information to specific clients with deep pockets—not at the typical
researcher. Data consortia provide community standards for data and metadata format and content and may provide indexing and search services, but these consortia
rarely provide the curation services themselves. Search services (e.g., Google) have
grown sophisticated and broadly skilled in recent decades, but often fail to provide
1 The Coalition for Publishing Data in the Earth and Space Sciences (COPDESS) provides some
detailed advice on best practices for implementing the FAIR principles for your research project or
other data product project.
B. L. Ruddell
Reusability emphasizes that metadata and data are richly described, including a
clear data usage license, detailed provenance, and the use of domain-specific community standards.
The reader will have an easier time both in publishing and accessing FEW systems data by working with vendors and repositories that implement FAIR principles (e.g. Wilkinson et al., 2016). Implementation decisions concerning these FAIR
principles for data publication tend to focus on the choice of a repository for your
data. The Coalition for Publishing Data in the Earth and Space Sciences (COPDESS)
provides some detailed advice on best practices for implementing the FAIR principles for your research project or other data product project—including the selection
of a repository, data and metadata format, compliance with your funding agency’s
data publication requirements, and so on.
1
The Library is the ancient institution that specializes in managing the data life
cycle. Libraries still (mostly) specialize in data as the printed word, and are the classic archetype of a repository for data.
A Repository is generalized library service that curates data and that ideally
provides FAIR data management services. Libraries, journals, web portals, search
services, and agency data services may be examples of repositories, although it is a
rare repository that provides all components of FAIR data management services that
you might require. For instance, it is relatively easy in 2018 to access and catalog
data using search services, but it is still challenging to find a high-quality repository
that is willing to permanently curate your datasets at no charge, and it is rare to find
a repository that will donate consulting and expert services to help you reformat,
metadata-markup, and package your data properly to comply with FAIR principles.
Different types of repositories and data entities provide different services and
serve different roles. If you are working or studying at a university, your library’s
role is to assist you not only with search and access to information but also with the
curation of data from your research. However, many university libraries lack the
specialized capacity to do this. Journals are rapidly transitioning from publishers of
the written word into full-service knowledge and data curation services and repositories, but some are further along this path than others as of 2018. In many cases,
journals require scholars to curate their data elsewhere. If you work for a state or
federal agency, in most cases your agency has its own funding and services to curate
and provide access to data—but only to those data originated by that specific agency.
Private consultancies and data services may provide excellent data products, but
these tend to exist behind an access paywall and tend to be targeted to provide
narrow information to specific clients with deep pockets—not at the typical
researcher. Data consortia provide community standards for data and metadata format and content and may provide indexing and search services, but these consortia
rarely provide the curation services themselves. Search services (e.g., Google) have
grown sophisticated and broadly skilled in recent decades, but often fail to provide
1 The Coalition for Publishing Data in the Earth and Space Sciences (COPDESS) provides some
detailed advice on best practices for implementing the FAIR principles for your research project or
other data product project.
B. L. Ruddell