Open science, research, access, data, etc.
Open Science
Open Access
Open Data
https://en.wikipedia.org/wiki/Open_data
Open Research
Research that is more transparent in more of its parts, often with the point of making reproducability and collaboration more likely.
This often amounts to sharing both the methods and data, making a point to say more than "we did a thing, we didn't forget to pay attention to X and Y, and here are our conclusions".
https://en.wikipedia.org/wiki/Open_research
Open-notebook science
Open-notebook science - basically to make the process and developments on the way (lab notebook and/or personal notebook) public, and not just the end result.
It doesn't have to be everything, nor does it have to be raw form,
in fact both might be counterproductive because they might not be coherent enough.
The idea is more to
- help science have public record of data that would otherwise not see the light of day because the result was less interesting to publish.
- help deeper understanding of the research (both laymen and scientific), by seeing intermediate results and development of theories, methods of analysis, etc.
https://en.wikipedia.org/wiki/Open-notebook_science
Principles and ideas
FAIR
FAIR (Findable, Accessible, Interoperable and Re-usable) is a (minimal, community-agreed) set of principles and practices that make data not only open in the sense that it's out there, but also make it easy to find, and use.
It could be purely about metadata, or about data as well - this depends a bit on the type of repositories we're talking about, and the kind of organization behind it.
- Note that when it describes data, this overlaps with open access details.
Findable - ideally has rich metadata, persistent identifiers, and is searchable by those
Accessible - fetchable at all, fetchable by identifier, allows auth if necessary (also, removing data doesn't mean removal of metadata)
Interoperable - uses metadata and knowledge representation that is accessible, broadly applicable and useful for analysis and processing (verify)
- somewhat vague. Roughly "is your metadata sensible for the job, and can I read it out at all"
- the last, 'are there qualified references' is vague. Does it mean links to related resources? Browsablility by subject headers? Using codes to disambiguate things confusable in text?
Re-usable - clearly disambiguated resources?, clear license, showing origin of data(verify)
- also "domain relevant community standards", which seems vague.
The basics can be considered in terms of compliance to clear use of PIDs, clear metadata and machine readability (also for indexing), clear licensing.
Some further requirements are more open-ended, as pointed out in A Dunning (2020) "Are the FAIR Data Principles Fair?" evaluates to what degree repositories currently adhere to this
See also:
- "To be findable, accessible, interoperable and reusable: language data and technology infrastructure for supporting the FAIR data approach " [1]
Relatedly
Open practices
Organisations an initiatives
COAR
IOI
DOAJ
Directory of Open Access Journals
OJS
PKP's Open Journal Systems is software that basically helps you set up an open access journal of your own.
Services and implementations
CORE
Aggregator of open access research papers from repositories and journals.
Aimed at stakeholders like researchers, the public, academic institutions, developers, funders, companies
- APIs
- Dataset download