Need to find a data repository? See the Preserve-Reuse tab.
You can also email me at laura.palumbo@rutgers.edu.
Making your research data publicly accessible is not necessarily the same thing as making it open access.
Public access usually refers to the products of federally funded research, such as data and publications. There may be restrictions on access to these in order to protect privacy, intellectual property, or national security, for example.
"Public Access comprises the efforts of U.S. federal science agencies to increase access to unclassified scholarly publications and digital data resulting from federal research and development (R&D) funding." (US Office of Science and Technical Information)
Open access refers to digital content that is freely available online without legal restrictions. Just because something is available online does not mean that it is open access or free to use- there may be restrictions because of copyright or licensing.
Open Access means that there are "no financial, legal or technical barriers to accessing it - that is to say when anyone can read, download, copy, distribute, print, search for and search within the information, or use it in education or in any other way within the legal agreements." (Open Access Netherlands)
Metadata is simply 'data about data'. An example is a citation to an article or other information- it tells you about the thing, but it's not the thing itself. Metadata is necessary for data because it would be extremely hard to find without it.
Repositories often require specific metadata or use existing metadata schemas. This is the first place to look for metadata requirements.Some disciplines have their own norms for metadata schemas.
Disciplinary metadata may be found the Metadata Standards Catalog, a project of the Research Data Alliance. Another resource is the List of Metadata Standards by the Digital Curation Centre.
The following are two widely used metadata schemas:
Dublin Core - an all-purpose schema with 15 basic elements.
DDI Data Documentation Initiative Alliance- a commonly used metadata schema in the social sciences.
FAIR stands for Findable, Accessible, Interoperable, and Reusable. FAIR data principles were published in Scientific Data in 2016 and have been widely accepted in Europe. The emphasis is on sharing research data so that it can be used for new scientific discoveries. Most of the guidelines include both data and metadata, or data about data, that can be interpreted by computers. These are the FAIR data principles, from https://www.go-fair.org/fair-principles/
Findable
F1. (Meta)data are assigned a globally unique and persistent identifier
F2. Data are described with rich metadata (defined by R1 below)
F3. Metadata clearly and explicitly include the identifier of the data they describe
F4. (Meta)data are registered or indexed in a searchable resource
Accessible
A1. (Meta)data are retrievable by their identifier using a standardised communications protocol
A1.1 The protocol is open, free, and universally implementable
A1.2 The protocol allows for an authentication and authorisation procedure, where necessary
A2. Metadata are accessible, even when the data are no longer available
Interoperable
I2. (Meta)data use vocabularies that follow FAIR principles
I3. (Meta)data include qualified references to other (meta)data
Reusable
R1. (Meta)data are richly described with a plurality of accurate and relevant attributes
R1.1. (Meta)data are released with a clear and accessible data usage license
R1.2. (Meta)data are associated with detailed provenance
R1.3. (Meta)data meet domain-relevant community standards