Open science, research, access, data, etc.

Library glossary Identifiers, classifiers, and other codes Citations Repository notes Open science, research, access, data, etc. Metadata models and standards Online (library) search related OpenURL notes OCLC Pica notes Library-related service notes Knowledge representation / Semantic annotation / structured data / linked data on the web Library - unsorted

✎ This article/section is a stub — some half-sorted notes, not necessarily checked, not necessarily correct. Feel free to ignore, or tell me about it.

Open Data

https://en.wikipedia.org/wiki/Open_data

Principles and ideas

FAIR

✎ This article/section is a stub — some half-sorted notes, not necessarily checked, not necessarily correct. Feel free to ignore, or tell me about it.

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:

• https://www.fairdatapoint.org/

• https://en.wikipedia.org/wiki/FAIR_data

• https://www.ands.org.au/working-with-data/fairdata

• "To be findable, accessible, interoperable and reusable: language data and technology infrastructure for supporting the FAIR data approach " [1]

• https://www.force11.org/fairprinciples

DOAJ

Directory of Open Access Journals

https://doaj.org/about/

OJS

PKP's Open Journal Systems is software that basically helps you set up an open access journal of your own.

https://www.tudelft.nl/library/library-voor-onderzoekers/library-voor-onderzoekers/publiceren-verspreiden/je-publicatiestrategie-creeren/creeer-een-open-access-tijdschrift

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

https://api.core.ac.uk/docs/v3

• Dataset download