FA.6.T.2 | FAIR Awareness training session 1 - by Barbara Magagna

FA.6.T.1 | FAIR Awareness training session 1 - by Anne Fouilloux

FA.6.T.2 | FAIR Awareness training session 2
FA.6.T.2 | FAIR Awareness training session 2 - by Barbara Magagna

Template for defining a research project

end date of research project (YYYY-MM-DD)

identifier of the research project funder

identifier (from funder) of the research project

start date of research project (YYYY-MM-DD)

a link to the research project's website

end date of research project (YYYY, YYYY-MM, or YYYY-MM-DD)

start date of research project (YYYY, YYYY-MM, or YYYY-MM-DD)

the name of funder if no identifier exists

description of the research project (if copied, with reference URL)

URI (from funder) of the research project

Template for describing a dataset at summary level
Describing a dataset at summary level - simple

URI of research project that produced dataset

URI of repository where dataset is published

Template: Describing a dataset at summary level - simple

description of research project (if copied, with reference URL)

AIDA sentence - an English sentence that is Atomic, Independent, Declarative, and Absolute

is about - connects a thing (left) to a subject matter that this thing is about (right)

is an - connects a thing (left) to a class it belongs to (right)

Type your AIDA sentence here (ending with a full stop)

Such nanopublications use the concept of an AIDA sentence to express a (scientific) statement in an informal or semi-formal manner, which can be formally linked.

AIDA sentences are:

Atomic: a sentence describing one thought that cannot be further broken down in a practical way
Independent: a sentence that can stand on its own, without external references like "this effect" or "we"
Declarative: a complete sentence ending with a full stop that could in theory be either true or false
Absolute: a sentence describing the core of a claim ignoring the (un)certainty about its truth and ignoring how it was discovered (no "probably" or "evaluation showed that"); typically in present tense

You can find more information about AIDA sentences here.

Expressing a statement as an AIDA sentence

URI of nanopublication for related dataset

URI of nanopublication for related research project

Template: Expressing a statement as an AIDA sentence

Expressing a statement about research as an AIDA sentence

Template: Expressing a statement about research as an AIDA sentence

M4M.24.T1 | PARC M4M Training 1 - by Barbara Magagna

FA.5.T.5 | ITINERIS FAIR Awareness 5 - by Rick Overkleeft

FA.6.T.3 | FAIR Awareness training session 3
FA.6.T.3 | FAIR Awareness training session 3 - by Barbara Magagna

funder URI or name (between " ") if no URI exists

description (if copied, with reference URL)

prefix npa: <http://purl.org/nanopub/admin/>

select distinct ?pubkey ?pubkeyhash where {
graph npa:graph {
?np npa:hasValidSignatureForPublicKey ?pubkey .
?np npa:hasValidSignatureForPublicKeyHash ?pubkeyhash .
}
} order by ?pubkey

On Onsland.nl you will find in-depth information about the shared Dutch-Indonesian past. The focus is on the Second World War and decolonization. A large network of affiliated heritage institutions, museums and archives makes various sources available.

This site provides access to the digitised and digital born collections of Leiden University Libraries.
UBL-DC_REG | Leiden University Libraries Digital Collections Service

In Delpher you can search millions of historical texts for free. They come from the collections of the KB national library and almost 200 other research institutions.

Search the world's most comprehensive index of full-text books.

Scholarly success depends on intuitive discovery of ground-breaking insights and information across your library’s collections. The Primo discovery solution is investing in revolutionary technologies like conversational search to optimize outcomes for library users and staff.

The key concept in the PHT is to bring algorithms to the data where they happen to be, rather than bringing all data to a central place. The PHT is designed to give controlled access to heterogeneous data sources, while ensuring privacy protection and maximum engagement of individual patients and citizens.

The community Leiden University Libraries Digital Collections provides access to the digitised and digital born collections of Leiden University Libraries.
UBL-DC | Leiden University Libraries Digital Collections Community

Climate change poses risks to European communities, requiring robust adaptation strategies to protect ecosystems, economies and public health. However, fragmented data and limited interoperability across regions hinder coordinated action. Often, valuable insights remain inaccessible to policymakers and researchers seeking evidence-based solutions. Addressing this data-sharing challenge is essential for creating flexible and responsive adaptation frameworks. In this context, the EU-funded FAIR2Adapt project is advancing climate resilience by transforming data into actionable knowledge. By collaborating with the European Open Science Cloud (EOSC), FAIR2Adapt builds a user-friendly, interoperable data-sharing platform using FAIR Digital Objects and tools like the I-ADOPT framework. Through case studies and stakeholder engagement, FAIR2Adapt develops customised, scalable solutions for climate adaptation.
FAIR2Adapt | FAIR to Adapt to Climate Change

URI of concept or topic the sentence is about

FA.6.T.4 | FAIR Awareness training session 4
FA.6.T.4 | FAIR Awareness training session 4 - by Barbara Magagna

Allmaps makes it easier and more inspiring to curate, georeference and explore collections of digitized maps. 100,000s of maps are available through IIIF, across libraries, archives and museums worldwide. IIIF is the International Image Interoperability Framework, which is a set of open standards for delivering high-quality, attributed digital objects online at scale; see also https://w3id.org/np/RArYu3pzBwTJeZTVHoNRSGUTGPTGFoQEiUQfRrqRWyBBk

FIP.29.W.1 | CDS Summer Training Week 2024 - FAIR Implementation for Research Communities - by Alessa An Gambardella

NCBI is a division of the U.S. National Library of Medicine at the National Institutes of Health, supporting biomedical and genomic research by providing free access to data, tools, and information resources.
National Center for Biotechnology Information

A comprehensive database of organism names and classifications that is designed to support the International Nucleotide Sequence Database Collaboration (INSDC), including GenBank, EMBL, and DDBJ. It provides a curated, phylogenetic hierarchy of valid names and classifications, emphasizing systematics and nomenclature rather than detailed taxon descriptions. The taxonomy integrates phylogenetic and taxonomic knowledge from diverse sources, such as published literature, web-based databases, and input from sequence submitters and external experts.
National Center for Biotechnology Information Taxonomy

A globally unique identifier that represents a resource using Unicode characters, allowing for resource identification across various languages. Similar to a URI, an IRI identifies resources on the Internet, private networks, or offline, without necessarily implying a retrieval method. This expanded character set enables universal access and identification in multilingual contexts.

SHACL, Shapes Constraint Language, is a language for validating RDF graphs against a set of conditions.

can in some situations be considered the same as

Template for defining a community of practice aiming at implementing the FAIR principles.
Defining a FAIR implementation community

description of the community in one sentence

the identifier of the related community description

Template: Defining a FAIR implementation community

The GFF community is a grouping of people trained by GFF including GFF Fellows.

This is the group of students attending the data stewards course at the university of Torino in 2024

participated as facilitator assistant in

Declaring the participation in a 3PFF event

Template: Declaring the participation in a 3PFF event

The FAIR technical framework community did not choose which GUPRI is needed for metadata. We propose that we integrate the different technologies to facilitate this, but not make the choice for the people that want to implement the technological framework. We have not yet integrated GUPRI creation for metadata records, but will do so in the future.

The FAIR technical framework community did not choose which GUPRI is needed for datasets. We propose that we integrate the different technologies to facilitate this, but not make the choice for the people that want to implement the technological framework. We have not yet integrated GUPRI creation for datasets, but will do so in the future.

Since the persistent identifiers are not yet chosen we are unable to implement the schema that links them.

The FAIR technical framework community did not yet make the choice for an authentication and authorisation service, but we are experimenting with the Open Digital Rights Language.

Since FHIR does not use a standard vocabulary for their data, we also don't use it.

Since FHIR does not use a standard semantic model for their data, we also don't use it.

The FAIR technical framework community did not yet make the choice for usage license, but we are experimenting with the Open Digital Rights Language.

The FAIR technical framework community did not choose which provenance is needed for metadata. We propose that we integrate the different technologies to facilitate this, but not make the choice for the people that want to implement the technological framework.

The FAIR technical framework community did not choose which provenance is needed for datasets. We propose that we integrate the different technologies to facilitate this, but not make the choice for the people that want to implement the technological framework.

The most generic kind of creative work, including books, movies, photographs, software programs, etc

Such a nanopublication expresses citation relations of a given work based on the CiTO relation types.

DOI (https://doi.org/10...) or other URL of the cited article

DOI (https://doi.org/10...) or other URL of the citing article

DataCite DOIs are issued by EUDAT B2SHARE which is currently used to share and publish site level datasets (processing level 0 and 1). In future DataCite DOIs also will be issued by the eLTER Central Data Node (CDN) which is currently in development (plan for 2024). Implementation of DOIs for site records in addition to the deims.id is currently evaluated.

FAIR Supporting Resource to be developed

Template for defining an identifier service.

data policy that this resource implements

a link to a website with further information

Template: Defining an Identifier Service

URL of data policy that this resource implements

URI of the organization providing the service

at least 10 years and less than 20 years

Template for defining a registry of digital objects.

a link to the specification that this resource implements

UUID are appended to the URI of the eLTER Catalogue (Digital Asset Register, DAR). UUID is also used in DEIMS-SDR to identify the MD records for sites, locations, sensors and networks

currently used for datasets shared via B2SHARE. Issuing DOI from the eLTER Digital Asset Registry (DAR) will be implemented in 2025 onwards. Services related to access to these data are documented as service records in the DAR.

persistent identification based on UUID plus URI (namespace for deims) for research sites and observation facilities implemented in DEIMS-SDR and used to unambigously identify and register sites belonging to different research infrastructures and networks

for eLTER a community profile based on the INSPIRE required fields and requirements for EML 2.0 was definded using a local schema which is mapped to ISO19115/19139 to expose metadata. For the Digital Asset Register (DAR) also sharing of ISO19115/19139 metadate is implemented - schema on read philosophy

for eLTER a community profile based on the INSPIRE required fields and requirements for EML 2.0 was definded using a local schema which is mapped to ISO19115/19139 to expose metadata. For the Digital Asset Register (DAR) metadata are held in schema-neutral json document, which allows sharing of ISO19115/19139 metadate as a schema-on-read service through a RESTful API.

this is implemented for site datasets (processing level 0 and 1) using EUDAT B2SHARE as common repository. For the eLTER Central Data Node (CDN) this is under development and will be implemented 2025 onwards.

DEIMS-SDR is operational to document physical assets of the eLTER network (sites, platforms, locations, sensors, and networks) as well as digital assets (datasets and activities). In future implementation steps (2025 onwards) digital assets will be documented and shared using the eLTER digital asset register (DAR)

EUDAT B2FIND harvests eLTER metadata from DEIMS-SDR and the related B2SHARE repository. The effort was renewed within the implementation of the EOSC-Hub project. B2FIND is used as additional domain agnostic discovery portal.

currently under development. the eLTER Digital Asset Register will be operational by end 2023 focusing n the documentation of digital assets (datasets, models, provenance) of the eLTER RI

currently within eLTER we use a combination of web services from DEIMS-SDR, DAR, B2SHARE and DataCite to disseminate metadata covering the different assets of the RI

DEIMS-SDR contains metadata to existing data repositories and linking dataset metadata to the respective eLTER facilility

the eLTER Central Data Node (CDN) currently contains storage of time series data (OGC SOS), geospatial data (OGC WMS/WFS) as well as files. The eLTER CDN is currently still under development and will be operational by mid 2024.

the eLTER DIP (EcoSense) is a web interface to view and access information on datasets shared

DEIMS-SDR REST-API shares information on sites, locations, sensors, datasets and networks as json

direct download using https/http request for datasets shared via B2SHARE

eLTER fosters an open data policy recommending CC-0 for any eLTER metadata. control of atuhorship of metadata is behind login wall of the catalogues (DEIMS-SDR, DAR). These are currently internal systems, but will be moved to an external system in the future.

General eLTER data policy fosters open data (CC-BY). Restrictions might apply for site based data under embargo before scientific publication. commercially sensitive data will have bespoke licenses.

updates are worked out in eLTER-PPP WP3 Data Management Plan and Data Policy. Will be available by 2025

implemented for DEIMS-SDR (API) as well as eLTER DAR

will be replaced by the eLTER RI Data Specification latest by 2025

local data provision could derive from that

information on metadata creation and update is provided as part of the MD model

currently implemented within the eLTER Digital Asset Register (DAR)

eLTER FIP 2022: This is the FIP for the eLTER Community representing the choices made in 2022.

was attributed to Aegina citrea by Gasca et al. 2007 but the host was reported based on the taxonomic information available at the time. The Narcomedusan taxa with the morphology depicted in their Figure 2 has been reclassified and is currently known as Solmundaegina nematophora Lindsay, 2017. The taxon currently known as Aegina citrea as defined by Lindsay et al. 2017 has therefore not been recorded as a host to Pseudolubbockia dilatata Sars, 1909.

References
Gasca R, Suárez-Morales E, Haddock SHD. 2007. Symbiotic associations between crustaceans and gelatinous zooplankton in deep and surface waters off California. Marine Biology 151:233–42. doi:10.1007/s00227-006-0478-y

Lindsay, D.J., Grossmann, M.M., Bentlage, B., Collins, A.G., Minemizu, R., Hopcroft, R.R., Miyake, H., Hidaka-Umetsu, M. and Nishikawa, J. (2017) The perils of online biogeographic databases: A case study with the “monospecific” genus Aegina (Cnidaria, Hydrozoa, Narcomedusae). Marine Biology Research 13(5): 494-512. DOI: 10.1080/17451000.2016.1268261

Pseudolubbockia dilatata Sars G.O., 1909 (species) - parasitoid of - Solmundaegina nematophora Lindsay, 2017 (species)

Pseudolubbockia dilatata Sars G.O., 1909 (species)

Solmundaegina nematophora Lindsay, 2017 (species)

A template that captures and annotates samples, reagents, and results from HAI experiments by linking samples, experiments, and assay results. The template supports reporting results for multiple analytes per sample by duplicating the 'Virus Strain' and 'Titration Dilution Value' columns as needed for each assay result. Users can describe new experiments and biological samples or connect existing ImmPort experiments and biological samples with assay results. To ensure consistency, all experiment sample IDs in the template must be unique and not previously stored in ImmPort. This same template also appears on the web with other names like 'Hemaglutinnation Inhibition Experiment Samples'.
ImmPort Hemaglutinnation Inhibition Experiment Sample Template Version 3.36

is based on a re-identification by myself, the species authority for Solmundaegina nematophora Lindsay, 2017, based on the photographs in Figure 2 of a narcomedusa identified in Gasca et al. 2007 as "Aegina citrea" that was sampled by the ROV ‘‘Tiburon’’ during Dive 682. Depth is in meters. The animal probably originated in shallower, more northerly waters and was swept southwards while being subducted to deeper depths.

Reference
Gasca et al. 2007
https://doi.org/10.1007/s00227-006-0478-y

oceanic bathypelagic zone biome - The bathypelagic zone biome comprises the marine water column below approximately 1000 m water depth - the maximum depth to which detectable daylight penetrates in all but the clearest oligotrophic waters - and extends to about 2500 - 2700 m water depth. In the temperate Atlantic, the beginning of the bathypelagic zone biome approximates to the deep oxygen minimum and the base of the permanent thermocline.

Organism of Solmundaegina nematophora Lindsay, 2017 (species) - has habitat - oceanic bathypelagic zone biome

is based on the image of zooniverse_id "APK0006f6z" with the following environmental parameters: oxygen 4.8, temperature 13.547, salinity 32.99 with data kindly provided by Jessica Luo.

oceanic epipelagic zone biome - The oceanic epipelagic zone biome comprises regions of the marine water column that occur offshore, beyond a continental shelf. This biome extends from the surface of the ocean to a depth of ca. 200-250m. Throughout the zone the light field tends to be asymmetrical vertically, so that the direction and elevation of the sun can still be detected. The oceanic epipelagic zone biome encompasses the euphotic zone and, where and when it occurs, the seasonal thermocline.

Organism of Solmundaegina nematophora Lindsay, 2017 (species) - has habitat - oceanic epipelagic zone biome

is based on re-identification by myself of the image of zooniverse_id "APK0003o9e", which is also the image in Luo et al. 2014 Figure 3o. Environmental parameters are: oxygen 1.966, temperature 9.28, salinity 33.96.

References
Luo et al. 2014
https://doi.org/10.3354/meps10908

collected by Karen Osborn, sequenced by Bastian Bentlage, identified based on taxonomic knowledge at the time as "Aegina citrea". Specimen ID at Smithsonian D791ss5

Organism of Solmundaegina nematophora Lindsay, 2017 (species) - observed nucleotide sequence - KY007597.1

The FAIR Data Station is a metadata ingestion platform that helps to improve the quality of metadata. The station allows users to record meta-data according to minimum information standards thereby ensuring FAIR scientific data management from the start.

FIP.25.T.4 | PARC FIP Training - by Maciej Gromelski

FIP.25.T.3 | PARC Facilitator Training - by David Schott

The I-ADOPT Framework acts as a semantic broker and is based on an ontology in order to facilitate interoperability between existing variable description models. It offers core atomic components and relations between them that can be applied to define machine-interpretable variable descriptions that reuse FAIR terminology concepts.

A template to describe the interpreted results of sample dilution series (e.g., serum) used to quantitate the viral neutralizing activity of a sample. It captures titer results in a commonly used format that can be interpreted by ImmPort, facilitating the searching and display of results.
ImmPort Virus Neutralization Results Template Version 3.36

A template that organizes PCR results in a structured format for interpretation, searching, and display within ImmPort. It links samples, experiments, and results, supporting multiple analyte results per sample by duplicating essential columns such as 'Entrez Gene ID' and 'Threshold Cycles (Ct)' for each assay result. This same template also appears on the web with other names like 'QRT-PCR Results'.
ImmPort PCR Results Template Version 3.36

A legacy template that supports reporting the lab test results (but does not support defining the lab test panel which is the parent of a lab test), by capturing the Lab Panel ID, Biosample ID, Name, Result Value, and Result Unit for lab tests. The function of this template is also captured in the lab tests template. This template will continue to be supported for the foreseeable future to support backward compatibility.
ImmPort Lab Test Results Template Version 3.36

A legacy template that defines and annotates the collection of lab tests applied to a sample (but not the lab test results), by capturing the Lab Panel Name, Study ID and Protocol ID for lab tests. The function of this template is also captured in the lab tests template. This template will continue to be supported for the foreseeable future to support backward compatibility.
ImmPort Lab Test Panels Template Version 3.36

A template that captures information about the immune exposure of subjects in studies. It updates previously defined human and animal subjects with details about the exposure process and the type of evidence supporting that exposure.
ImmPort Immune Exposure Template Version 3.36

A template to describe Hemaglutinnation Inhibition (HAI) results in a structure that can be interpreted by ImmPort to facilitate searching and display of results. This same template also appears on the web with other names like 'Hemaglutinnation Inhibition Derived and Interpreted Results'.
ImmPort Hemaglutinnation Inhibition Results Template Version 3.36

A template to describe ELISPOT results in a structure that can be interpreted by ImmPort to facilitate searching and display of results. This same template also appears on the web with other names like 'ELISPOT Derived and Interpreted Results'.
ImmPort ELISPOT Results Template Version 3.36

A template to describe ELISA results in a structure that can be interpreted by ImmPort to facilitate searching and display of results. This same template also appears on the web other names like 'ELISA Derived and Interpreted Results'.
ImmPort ELISA Results Template Version 3.36

A legacy template that defines and annotates the mechanistic assays performed on samples, by describing the type of experiment, measurement technique and protocols used in the experiment. The function of this template is also captured in the experiment samples template. This template will continue to be supported for the foreseeable future to support backward compatibility.
ImmPort Experiments Template Version 3.36

A legacy template that defines and annotates the types of samples derived from study subjects and when during the study schedule the sample was derived. The function of this template is also captured in the experiment samples template. This template will continue to be supported for the foreseeable future to support backward compatibility.
ImmPort Biological Samples Template Version 3.36

A template that captures and annotates samples, reagents, and results from gene expression experiments by linking samples, experiments, and assay results. This template allows users to describe new experiments and biological samples or link existing ImmPort experiments and biological samples with assay results. It offers considerable flexibility in linking new and existing content while adhering to key guidelines: all experiment sample IDs must be unique within the template and not already stored in ImmPort. This same template also appears on the web with other names like 'Gene Expression Experiment Samples'.
ImmPort Gene Expression Experiment Sample Template Version 3.36

A template that captures and annotates samples, reagents, and results from genotyping experiments by linking samples, experiments, and assay results. This template allows users to describe new experiments and biological samples or connect existing ImmPort experiments and biological samples with assay results. It provides flexibility in linking new and existing content while adhering to important guidelines: all experiment sample IDs must be unique within the template and not already stored in ImmPort. This same template also appears on the web with other names like 'Genotyping Experiment Samples'.
ImmPort Genotyping Experiment Sample Template Version 3.36

This query returns all nanopub IDs for the given pubkey hash.

prefix npa: <http://purl.org/nanopub/admin/>
prefix npx: <http://purl.org/nanopub/x/>

select ?np where {
graph npa:graph {
?np npa:hasValidSignatureForPublicKeyHash ?_pubkeyhash .
}
}

the morphology-based taxonomic ID as Dimophyes arctica appears to be correct but the sequence is attributable to Agalma elegans so either it was contaminated or there has been a mix-up of samples.

Reference
Park, N., Yeom, J., Jeong, R. et al. Novel attempt at discrimination of a bullet-shaped siphonophore (Family Diphyidae) using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-ToF MS). Sci Rep 11, 19077 (2021).
https://doi.org/10.1038/s41598-021-98724-z

Organism of Agalma elegans (Sars, 1846) (species) - observed nucleotide sequence - MZ230467.1

This is an ontology of the FAIR Implementation Profiles (FIP) for the FAIR principles.
FAIR Implementation Profile (FIP) Ontology

FIP Question
A question communities have to address when declaring their FAIR Implementation Profiles

FIP Data-related Question
A FIP question that is relevant for the actual data (as compared to just their metadata)

FIP Metadata-related Question
A FIP question that is relevant for metadata (as compared to the data themselves)

FAIR Declaration
The statement of a community on how it addresses a FAIR-related question.

FIP Declaration
The expression of a community on how they address a FIP question

FSR Declaration
The statement of a community on the usage of a FAIR Supporting Resource.

SIP Declaration
The statement of a community on how it addresses a SIP question.

FAIR interpretation
A theoretical and practical explanation of the FAIR Principle by a recognized expert authority.

FAIR Qualifcation Criteria
A proposition on which a qualification of FAIR Supporting Resources is based.

FAIR case study
A description of a real-life situation where FAIR requirements of digital objects play a central role.

FIP No-Choice Declaration
A declaration stating that no choice has been made (yet)

FAIR Implementation Community
A FAIR Implementation Community (FIC) is a self-identified collection of people and/or organizations with the aim to implement the FAIR Principles

Cross domain community
A FAIR Implementation Communities with cross-domain coverage

Domain specific community
A FAIR Implementation Communities with domain coverage

Specific community
A FAIR Implementation Communities with specific coverage within a domain

has data steward
Specifies the data steward for a FAIR implementation community

FAIR Supporting Resource
Any resource that supports FAIR Data Stewardship. FSRs are represented as FAIR Digital Objects (using the nanopublication framework) with Globally Unique, Persistent, Resolvable Identifiers (GUPRI) that resolve to machine-readable metadata about the resource.

Available FAIR Supporting Resource
A FAIR Supporting Resource that is available for use.

A FAIR Supporting Resource that is not yet available but still needs to be developed.

FAIR-Enabling Resource
A service, a specification or a data policy that is essential to the operationalization of the FAIR Principles, i.e., puts FAIR into action. A FAIR-Enabling Resource (FER) provides a function needed to achieve some aspect of FAIR behavior and is explicitly linked to one or more FAIR principles.

FAIR Implementation Profile
A FAIR Implementation Profile (FIP) is a list of declared technology choices intended to implement each of the FAIR Guiding Principles, made as a collective decision by the members of a particular community of practice.

Available FAIR-Enabling Resource
A FAIR-enabling resource that is available for use

FAIR-Enabling Resource to be Developed
A FAIR-enabling resource that is not yet available but still needs to be developed

FAIR Data Policy
A policy that specifies and guides FAIR data practices for a community.

FAIR data stewardship plan template
A template guiding data stewardship including how FAIR Principles should be implemented. The template must be completed with project-specific information in any given instance to outline how data are to be handled in preparation for the project, during the research project, and after the project is completed.

FAIR data steward professional profile
A document stating the accumulated training qualifications and FAIR outputs authored by or contributed to, by that person. The profile may be augmented with additional statements regarding professional roles and skills.

FAIR data stewardship event
A meeting specifically designed for current or aspiring data stewards to provide a rigorous understanding of the FAIR principles from theory to their concrete implementation.

FAIR training material
Any educational resource (such as the content or its published representation in text, presentation graphics, or video) that covers FAIR topics of interest.

FAIR practice
A method description detailing the use of a specific resource or a combination of resources as applied by a community to achieve FAIR processing of information.

FAIR specification
A precise description of features, requirements, constraints and recommendations for a specific implementation of a component, system or service supporting the implementation of the FAIR principles.

Crosswalk
A specification consisting of a set of rules that define how (meta)data elements or attributes from one schema can be aligned and mapped to (meta)data elements or attributes in another schema that share the same constraints and thus share the same semantic role.

FAIR supporting service
Any online accessible software system or component that supports the implementation of the FAIR Principles.

FAIR Representation Service
A transformation service that converts non-FAIR data into a FAIR representation using machine-readable knowledge representation languages.

Web-API
An Application Programming Interface (API) for the World Wide Web that allows different software applications to communicate with each other.

Editor
A service that provides a user-friendly interface for easy editing of metadata, vocabularies or crosswalks.

Validation service
A system that automatically verifies the accuracy, completeness, or compliance of data, code or processes against predefined criteria or standards.

Provenance tracking service
A system that systematically captures, stores and manages detailed information about the origin, history, and lifecycle of digital objects creating metadata based on a provenance model.

Semantic Interoperability Profile
A Semantic Interoperability Profil (SIP) is a list of FAIR Supporting Resources chosen by a community to support semantic interoperability of (meta)data.

Digital Object Type
A digital object type is a classification of digital objects with respect to their informational functions to specify the nature of the digital object and the operations that can be performed on it.

Identifier service
A service that provides for any digital object (1) algorithms guaranteeing global uniqueness, (2) policy document that guarantees persistent and (3) resolution of the identifier to machine-actionable metadata describing the object and its location.

Metadata schema
A specification that specifies the structured representation of metadata describing attributes of data or other digital objects in terms of semantics, syntax and optionality.

Metadata-data linking schema
A specification that provides a unique, persistent, (ideally) bi-directional, machine-actionable link between metadata and the data they describe.

Registry
A service that indexes metadata and data and provides search over that index.

Communication protocol
A specification of how messages are structured and exchanged.

Authentication and authorization service
A service that mediates access to digital objects according to specifed conditions.

Metadata preservation policy
A data policy that describes the conditions under which metadata should be provided in the future.

Knowledge representation language
A language specification that enables knowledge to be processed by machines.

Structured vocabulary
A specification for a controlled list of uniquely identified and unambigous concepts with their definitions represented using web standards.

Semantic model
A specification that defines qualified relations between entities describing data or other digital objects according to the Linked Data principles. This can include semantic data models and ontologies.

Data usage license
A data policy that specifies legal restrictions on the reuse of the data.

Provenance model
A specification that specifies metadata describing the origin and lineage of data or other digital objects.

refers to principle
Connects an entity (for example a FIP declaration) to a FAIR (sub)principle it refers to

refers to question
Connects a FIP declaration to the FIP question it is addressing

declared by
Connects a FIP declaration to the community that made the declaration

declares current use of
Connects a FIP declaration to the resource that the community thereby declares to currently use

declares planned use of
Connects a FIP declaration to the resource that the community thereby declares to plan to use in the future

declares planned replacement of
Connects a FIP declaration to the resource that the community thereby declares to plan to replace in the future. The same declaration should also state a resource that the community declares to plan to use instead (with fip:declares-planned-use-of).

declares planned development of
Connects a FIP declaration to the resource that the community thereby declares to plan to develop

declared for digital object type
Connects a FIP declaration to the digital object type it applies to

declared for case study
Connects a FIP declaration to the case study it refers to.

has declaration index
Connects a FAIR Implementation Profile or a Semantic Interoperability Profile to the index of their declarations.

considerations
Considerations that led to a given FIP declaration

FIP Question F1-MD
What globally unique, persistent, resolvable identifiers do you use for metadata records?

FIP Question F1-D
What globally unique, persistent, resolvable identifiers do you use for datasets?

FIP Question F2
Which metadata schemas do you use for findability?

FIP Question F3
What is the technology that links the persistent identifiers of your data to the metadata description?

FIP Question F4-MD
In which search engines are your metadata records indexed?

FIP Question F4-D
In which search engines are your datasets indexed?

FIP Question A1.1-MD
Which standardized communication protocol do you use for metadata records?

FIP Question A1.1-D
Which standardized communication protocol do you use for datasets?

FIP Question A1.2-MD
Which authentication & authorisation technique do you use for metadata records?

FIP Question A1.2-D
Which authentication & authorisation technique do you use for datasets?

FIP Question A2
Which metadata longevity plan do you use?

FIP Question I1-MD
Which knowledge representation languages (allowing machine interoperation) do you use for metadata records?

FIP Question I1-D
Which knowledge representation languages (allowing machine interoperation) do you use for datasets?

FIP Question I2-MD
Which structured vocabularies do you use to annotate your metadata records?

FIP Question I2-D
Which structured vocabularies do you use to encode your datasets?

FIP Question I3-MD
Which models, schema(s) do you use for your metadata records?

FIP Question I3-D
Which models, schema(s) do you use for your datasets?

FIP Question R1.1-MD
Which usage license do you use for your metadata records?

FIP Question R1.1-D
Which usage license do you use for your datasets?

FIP Question R1.2-MD
Which metadata schemas do you use for describing the provenance of your metadata records?

FIP Question R1.2-D
Which metadata schemas do you use for describing the provenance of your datasets?

Nanopublications representing the FAIR Implementation Profiles (FIP) Ontology

This is the formal vocabulary (ontology) describing the FAIR principles.

FAIR principles

FAIR Principle or Sub-Principle
Either a FAIR principle or one of its sub-principles.

FAIR Principle
A FAIR principle describes an essential aspect of FAIR.

FAIR SubPrinciple
A sub-principle of a FAIR principle.

Findable

(meta)data are assigned a globally unique and persistent identifier

data are described with rich metadata (defined by R1 below)

metadata clearly and explicitly include the identifier of the data it describes

(meta)data are registered or indexed in a searchable resource

Accessible

(meta)data are retrievable by their identifier using a standardized communications protocol

the protocol is open, free, and universally implementable

the protocol allows for an authentication and authorization procedure, where necessary

metadata are accessible, even when the data are no longer available

Interoperable

(meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation

(meta)data use vocabularies that follow FAIR principles

(meta)data include qualified references to other (meta)data

Reusable

meta(data) are richly described with a plurality of accurate and relevant attributes

(meta)data are released with a clear and accessible data usage license

(meta)data are associated with detailed provenance

(meta)data meet domain-relevant community standards

Nanopublications representing the FAIR Principles

Mature community
A FAIR Implementation Community that has reached maturity

Emerging community
A FAIR Implementation Community that hasn't reached maturity yet

A well-established community interested to implement FAIR in their data and services.

An early-stage community committed to adopting and promoting FAIR principles for its data and services from the outset.

Generalist registry
A registry designed to collect, provide access to, and enable searching of data without any restrictions on the domain.

Domain-specific registry
A registry designed to collect, provide access to, and enable searching of data within a particular domain or subject area

has reasearch domain
Connects a FAIR Implementation Community with research domains

enables
Connects a FAIR Enabling Resource class with the FAIR principles it enables

metadata availability in years
Specifies how many years metadata are preserved according to the metadata preservation policy

FAIR Principles Explained Working Group

This is the formal model describing the Implementation Choices and Challenges for the FAIR principles.
FAIR Implementation Choices and Challenges Model

Choice
The kind of choice communities have to make (can be expressed as a question)

Challenge
The kind of challenge that some communities face if the lack of existing resources doesn't allow them to make a choice yet

Declaration
Something that is either a ChoiceDeclaration or a ChallengeDeclaration

Choice Declaration
The expression of a community of their choice made (corresponds to an answer to a question)

Challenge Declaration
The expression of a community of a challenge they accepted

Community
A non-empty set of people and/or organizations that form a self-declared community with the aim to implement the FAIR principles for their fields of interest

Resource
An artifact or service that can contribute to the implementation of the FAIR principles

Explanation
An explanation of a FAIR (sub)principle

explains principle
Links an explanation to the FAIR (sub)principle it explains

implementation consideration
Explains considerations for communities who are about to implement the given principle.

implementation examples
Describes examples around the implementation of the given principle.

Connects an entity (for example a choice or challenge) to a FAIR (sub)principle it refers to

related challenge
Connects a Choice to a Challenge that some communities might face before they can make the given kind of choice

refers to choice
Connects a ChoiceDeclaration to the Choice it is derived from

refers to challenge
Connects a ChallengeDeclaration to the Challenge it is derived from

Connects a Declaration to the Community that made the declaration

chosen resource
Connects ChoiceDeclaration to the Resource that was chosen through the declaration

has open challenge
Connects a ChoiceDeclaration to a ChallengeDeclaration that describes a challenge that had to be met before the choice could be made

Principle F1 states that digital resources, i.e. data and metadata, must be assigned a globally unique and persistent identifier in order to be found and resolved by computers. This is the most fundamental of the FAIR principles, as globally unique and persistent identifiers are essential elements found in all of the other FAIR principles. Globally unique means that the identifier is guaranteed to unambiguously refer to exactly one resource in the world. Therefore, it is insufficient for it to be unique only locally (e.g. unique within a single, local database). Persistence refers to the requirement that this globally unique identifier is never reused in another context, and continues to identify the same resource, even if that resource no longer exists, or moves. In practice, this often involves using a third-party to generate an identifier that has guaranteed longevity and is project/organization-independent.
Current challenges relate to ensuring the longevity of identifiers - in particular, that identifiers created by a project/community should survive the termination of the project or the dissolution of the community. Obtaining a persistent identifier, therefore, may require reliance on a third-party organization that promises longevity, and maintains these identifiers independently of the project/community. Current choices are for each community to choose, for all appropriate digital resources (i.e. data and metadata), identifier registration service(s) such as these that ensure global uniqueness and that also comply with the community-defined criteria for identifier persistence and resolvability.
A common example of a useful identifier is the Digital Object Identifier (DOI) which is guaranteed by the DOI specification to be globally unique and persistent. DOIs provide an additional service, under principle A1, of being able to direct calls to the source data to the location of that data, even if the identified data moves. This ensures that identifiers are stable and valid beyond the project that generated them. In some circumstances, again with DOIs being an example, third-party persistent identifiers may also provide support for principle A2 (that metadata exists beyond the lifespan of the data) since these identifiers may still be responsive to Web calls, and be capable of providing metadata, even if the source resource is no longer active. For a discussion on identifiers see doi:10.1371/journal.pbio.2001414 and doi:10.5281/zenodo.3267434 .

Data Documentation Initiative on FAIRsharing

W3C HCLS Dataset Description on FAIRsharing

Whereas principle F1 enables unambiguous identification of resources of interest, principle F2 speaks to the ability to discover a resource of interest through, for example, search or filtering. Digital resources must be described with rich metadata - descriptors of the content of the resource referred to by that identifier. It is hard to generally define the minimally required 'richness' of this metadata, except that the more generous it is, both for humans and computers, the more specifically findable it becomes in refined searches. While other principles speak to the specific kinds of metadata that should be included, principle F2 simply says that a digital resource that is not well-described cannot be accurately discovered. Thus, this principle encourages data providers to consider the various facets of search that might be employed by a user of their data, and to support those users in their discovery of the resource. To enable both global and local search engines to locate a resource, generic and domain-specific descriptors should be provided.
It is a challenge for each domain-specific community to define their own metadata descriptors necessary for optimizing findability. The minimal ‘richness’ of the metadata should be defined so that it serves its intended purpose and should also be guided by the requirements of the other FAIR principles. This then poses a challenge to each community to create machine-actionable templates that facilitate capturing uniform and harmonized metadata about similar data resources among all community stakeholders, and to provide a means to ensure that this metadata is updated and curated (doi:10.5281/zenodo.3267434).
Examples of metadata schemata can be found in FAIRsharing (https://fairsharing.org/standards/, doi:10.1038/s41587-019-0080-8, [McQuilton et al. Data Intell. DI-2019-0028, 2019]) and include for instance the Data Documentation Initiative (DDI) (https://doi.org/10.25504/FAIRsharing.1t5ws6), the HCLS Dataset Descriptors (https://fairsharing.org/FAIRsharing.s248mf), and many domain-specific “minimal information” models that have been invented.

Principle F3 states that any description of a digital resource must contain the identifier of that resource being described. For instance, the description of a computational workflow, should explicitly contain the identifier for that workflow in a manner that is unambiguous. This is especially important where the resource and its metadata are stored independently, but persistently linked, which is generally considered good practice in FAIR. The purpose of this principle is twofold. First, it is perhaps trivial to say that a descriptor should explicitly say what object it is describing; however, there is a second, less-obvious reason for this principle. Many digital objects (such as workflows, as mentioned above) have well-defined structures that may disallow the addition of new fields, including fields that could point to the metadata about that digital object. Therefore, if you have one of these digital objects in-hand, the only way to discover its metadata is through a search using the identifier of that digital object. Thus, by requiring that a metadata descriptor contains the identifier of the thing being described, that identifier may then successfully be used as the search term to discover its metadata record.
It is a challenge to each community to choose a machine-actionable metadata model that explicitly links a resource and its metadata.
An example of a technology that provides this link is FAIR Data Point (doi:10.1162/dint_a_00031), which is based on the Data Catalogue model (DCAT, https://www.w3.org/TR/vocab-dcat/) that provides not only unique identifiers for potentially multiple layers of metadata, but also provides a single, predictable, and searchable path through these layers of descriptors, down to the data object itself.

Principle F4 states that digital resources must be registered or indexed in a searchable resource. The searchable resource provides the infrastructure by which a metadata record (F1) can be discovered, using either the attributes in that metadata (F2) or the identifier of the data object itself (F3) (doi:10.1162/dint_a_00026).
Current challenges are numerous, significantly limiting, and largely outside of the control of the average data provider. First, there is no single-source for search that currently indexes all possible metadata fields in all domains. Second, there is no uniform way to execute a search, and thus every search tool must be accessed with tool-specific software. Finally, many search engines forbid automated searches, precluding their use by FAIR-enabled software. Various initiatives are emerging that attempt to address this, at least in part, by providing a well-defined, machine-accessible search interface over indexed metadata. Nevertheless, to our knowledge, none of these currently index all possible metadata properties, nor do they span all possible domains/communities; rather, they focus on specific metadata schemas such as schema.org, at the expense of other well-established metadata formats such as DCAT, and/or are limited to specific communities such as biotechnology, astronomy, law, or government/administration. Current choices are for each community to choose, and publicly declare, what search engine to use for their own purposes, general or field-specific, and should at a minimum provide metadata following the standard that is indexed by the search engine of choice. They should also provide a machine-readable interface definition that would allow an automated search without human intervention.
An example of a generic searchable resource that supports manual exploration is Google Dataset Search (https://toolbox.google.com/datasetsearch); however, this suffers from several of the problems mentioned above, in particular, that it indexes only certain types of metadata (schema.org) and the search cannot be automated under the Google Terms of Service, and therefore cannot be implemented within FAIR software.

The protocol (mechanism) by which a digital resource is accessed (e.g. queried) should not pose any bottleneck. It describes an access process, hence does not directly pertain to restrictions that apply to using the resource. The protocols underlying the World-Wide Web, such as HTTP, are an archetype for an open, free, and universally implementable protocol. Such protocols reduce the cost of gaining access to digital resources, because they are well defined and open and allow any individual to create their own standards-compliant implementation. That the use of the protocols is free ensures that those lacking monetary means can equitably access the resource. That it is universally implementable ensures that the technology is available to all (and not restricted, for instance, by country or a sub-community), thus encompassing both the "gratis" and "libre" meaning of "free" (https://dash.harvard.edu/handle/1/4322580).
Current challenges are to explicitly and fully document access protocols that are not open/free (for example, access only after personal contact) and make those protocols available as a clearly identified facet of the machine-readable metadata. Current choices are for communities to choose standardized communication protocols that are open, free and universally implementable.
The most common example of a compliant protocol is the HTTP protocol that underlies the majority of Web traffic. It has additional useful features, including the ability to request metadata in a preferred format, and/or to inquire as to the formats that are available. It is also widely supported by software and common programming languages.

This principle clearly demonstrates that FAIR is not equal to ‘open’. Some digital resources, such as data that have access restrictions based on ethical, legal or contractual constraints, require additional measures to be accessed. This often pertains to assuring that the access requester is indeed that requester (authentication), that the requester’s profile and credentials match the access conditions of the resource (authorization), and that the intended use matches permitted use cases (e.g. non-commercial purposes only) (see also R1.1, where there are requirements to provide explicit documentation about who may use the data, and for what purposes). At the level of technical implementation, an additional authentication and authorization procedure must be specified, if it is not already defined by the protocol (see A1.1). A requester can be a human or a machine agent. In the latter case it is probably a proxy for a human or an organization to which the authentication and authorization protocol should be applied, in which case, the machine should be expected to present the appropriate credentials. The principle requires that a FAIR resource must provide such a protocol, but the protocol itself is not further specified. In practice, an Internet of FAIR Data and Services cannot function without implementing Authentication and Authorization Infrastructure (AAI, see also https://doi.org/10.1162/dint_a_00029).
Current choices are for communities to choose protocols to use when controlling access of agents to meta(data). Preferably these should be as generic as possible and as domain specific as necessary. Attempts to harmonize AAI approaches are numerous, but not covered in this article.
Again, the most common example of a compliant protocol is the HTTP protocol. Another example is the life science AAI protocol. Brewster et al. (https://doi.org/10.1162/dint_a_00029) describe an early implementation of an ontology-based approach to this challenge.

A primary purpose of identifying a digital resource is to simultaneously provide the ability to retrieve the record of that digital resource, in some format, using some clearly-defined mechanism: hence the retrievability is a facet of FAIR Accessibility. Here, the emphasis is on 'ability': there should be no additional barrier retrieval of the record by some agent when its access protocol (A1.1) results in permitted access to that record. Note that the agent may be a machine working behind a firewall, if that agent has been permitted access. For fully mechanized access, this requires that the identifier (F1) follows a globally-accepted schema that is tied to a standardized, high-level communication protocol. The 'standardized communication protocol' is critical here. Its purpose is to provide a predictable way for an agent to access a resource, regardless of whether unrestricted access to the content of the resource is granted or not.
An example of a standardized access protocol is the Hypertext Transfer Protocol (HTTP1); however, FAIR does not preclude non-mechanized access protocols, such as a verbal request to the data holder in the case of highly sensitive data, so long as the access protocol is explicit and clearly defined. Conditions of compliance are further specified in sub-principles A1.1 and A1.2.

There is a continued focus on keeping relevant digital resources available in the future. Data may no longer be accessible either by design (e.g. a defined life-span within limited financial resources or legal requirements to destroy sensitive data) or by accident. However, given that those data may have been used and are referenced by others, it is important that consumers have, at the very least, access to high quality metadata that describes those resources sufficiently to minimally understand their nature and their provenance, even when the relevant data are not available anymore. This principle relies heavily on the ‘second purpose’ of principle F3 (the metadata record contains the identifier of the data), because in the case where the data record is no longer available, there must be a clear and precise way of discovering its historical metadata record. This aspect of accessibility is further elaborated in the Joint Declaration of Data Citation Principles (doi:10.25490/a97f-egyk).
Current choices/challenges are for communities to choose/define a persistence policy for metadata that describes data that may not always be available, choose/define machine-actionable templates for a persistence policy document for metadata, and in addition choose/define a machine-actionable scheme to reference the metadata persistence policy.
Examples of early attempts to address this critical principle relates closely to the principles of digital curation (http://www.dcc.ac.uk/) including the concept of a FAIR compliant DMP (Data Management Plan; http://www.dcc.ac.uk/resources/data-management-plans) (doi:10.1162/dint_a_00043). Many other efforts are underway to improve the long-term stewardship of reusable digital resources.

Consumers spend a disproportionate amount of time trying to make sense of the digital resources they need and designing accurate ways to combine them. This is most often due to a lack of suitably unambiguous content descriptors, or a lack of such descriptors entirely with respect to non-machine-interpretable data formats such as tables or “generic” XML. Community-defined data exchange formats work reasonably well within their original scope of a few types of data and a relatively homogeneous community, but not well beyond that. This makes interoperation and integration an expensive, often impossible task (even for humans), but also means that machines cannot easily make use of digital resources, which is the primary goal of FAIR. For example, when a machine visits two data files in which a field “temperature” is present, then it will need more contextual descriptions to distinguish between weather data in one file and body temperature measurements in another. Achieving a ‘common understanding’ of digital resources through a globally understood ‘language’ for machines is the purpose of principle I1, with emphasis on ‘knowledge’ and ‘knowledge representation’. This becomes critical when many differently formatted resources need to be visited or combined across organizations and countries and is especially challenging for interdisciplinary studies or for meta-analyses, where results from independent organizations, pertaining to the same topic, must be combined. In this context, the principle says that producers of digital resources are required to use a language (i.e., a representation of data/knowledge) that has a defined mechanism for mechanized interpretation - a machine-readable “grammar” - where, for example, the difference between an entity, as well as any relevant relationship between entities, is defined in the structure of the language itself. This allows machines to consume the information with at least a basic “understanding” of its content. It is a step towards a common understanding of digital resources by machines, which is a prerequisite for a functional Internet of FAIR Data and Services. Several technologies can be chosen for principle I1.
Communities will have to choose an available technology or decide how they will otherwise deal with multiple representations and languages. In any case, they will have to make sure that each data item that is the same in multiple resources is interpreted in exactly the same way by every agent (human and computer), and that how items across resources relate to one another can be unambiguously understood by all agents (doi:10.1162/dint_a_00040). The key consideration in this regard is that FAIR speaks to the ability of data to be reused by a generic agent, rather than a community-specific agent. This is most easily accomplished by making the knowledge available in the most widely used format(s), even if this means duplication of the information in the community-specific format.
The most widely-accepted choice to adhere to this principle, at the present time, is the Resource Description Framework (RDF) which is the W3C’s recommendation for how to represent knowledge on the Web in a machine-accessible format (https://www.w3.org/RDF/). Other choices may also be acceptable, for instance when they are already in widespread use within a given community. In that case, it would be helpful for the community to also provide a “translator” between their preferred format, and a more widely used format such as RDF.

Principle I2 uses 'vocabularies' to refer to the methods that unambiguously represent concepts that exist in a given domain. The use of shared, and formally structured (I1), sets of terms is an essential part of FAIR. Terminology systems, including flat ‘vocabularies’, hierarchical ‘thesauri’ and more granular specifications of knowledge such as data models and ontologies, play an important role in community standards. However, the vocabularies used for metadata or data also need to be findable, accessible, interoperable, and reusable in their own right so that users (including machines) can fully understand the meaning of the terms used in the metadata. This principle has been criticized as ‘circular’ but as has been made clear earlier in this article, the simple use of a “label” (e.g. “temperature”) is insufficient to enable a machine to understand both the intent of that label (Body temperature? Melting temperature?) and the contexts within which it can be properly linked - same-with-same - to other similarly-labelled data. I2, therefore, requires that the vocabulary terms used in the knowledge representation language (principle I1) can be sufficiently distinguished, by a machine, to ensure detection of ‘false agreements’ as well as ‘false disagreements’.
Current considerations are for communities to ensure that terminology systems and, for instance, the units of measure, classifications, and relationship definitions are themselves FAIR. Thesauri that are proprietary and not universally accessible should be avoided wherever possible, because machines (and indeed particular countries, regions or communities as a whole) may not have the authority to access their definitions, such that even data that is accessible after authentication via A1.2 may not be useful to an agent that has no authority to access the concept definitions used within that data.
Ontologies defined in the ‘Web Ontology Language’ (OWL) and shared via a publicly accessible registry (e.g. BioPortal for life science ontologies; https://bioportal.bioontology.org/) are examples of formally represented, accessible, mapped, and shared knowledge representations in a broadly applicable language for knowledge representation, that are also compliant with the Findability requirements of FAIR, since BioPortal provides a machine-accessible search interface.

An important aspect of FAIR is that data or metadata, generally speaking, does not exist in a silo - we must do what is necessary to ensure that the knowledge representing a resource is connected to that of other resources to create a meaningfully interlinked network of data and services. A “qualified reference” is a reference to another resource (i.e., referencing that external resource’s persistent identifier), in which the nature of the relationship is also clearly specified. For instance, when multiple versions of a metadata file are available, it may be useful to provide links to prior or next versions using a named relation such as “prior version” or “next version” (preferably using an appropriate community standard relationship that itself conforms to the FAIR principles). In the case of data, imagine a dataset that specifies the population of cities around the world. To be FAIR with respect to principle I3, the data could contain links to a resource containing city data (e.g. Wikidata: http://wikidata.org/, doi:10.1145/2187980.2188242), geographical and geospatial data, or other related domain resources that are generated by that city, so long as they are properly qualified references using meaningful, clearly-interpretable relationships. It is also important to note that many different metadata files (containers) being FAIR digital resources in themselves, can be pointing to the same ‘target’ object (a data set or a workflow for instance). We can for instance have intrinsic metadata (‘what is this’) and how was it created (provenance type metadata) as well as ‘secondary’ metadata that are for instance created (separately and later in time) by reusers of a particular digital resource. These could all be metadata containers essentially describing the same digital resource from different perspectives. This principle therefore also relates to the good practice to clearly distinguish between metadata (files/containers) and the resources they describe.
The considerations and choices made here are based on the same reasoning as the decisions made for principle I2. Vocabularies (often formal ontologies) of both concepts and relationships exist, and an appropriate relationship should either be selected from one of these, or “coined” and properly published following the FAIR Principles.
It is worth noting as an example that several “upper ontologies” such as the SemanticScience Integrated Ontology (https://bioportal.bioontology.org/ontologies/SIO) have a wide range of precisely-defined relationships that can be used as-is, or as a starting-point for a newly-minted relationship that is more specific than the one provided in the upper-ontology. The benefit of “inheriting” from higher-level relationships is that agents capable of understanding these higher level concepts, can infer at least a basic interpretation of the intent of the new relationship coined within the community, and therefore enhances interoperability.

Digital resources and their metadata must always, without exception, include a license that describes under which conditions the resource can be used, even if that is ‘unconditional’. By default, resources cannot be legally used without this clarity. Note also that a license that cannot be found by an agent, is effectively the same as no license at all. Furthermore, the license may be different for a data resource and the metadata that describes it, which has implications for the indexing of metadata v.v. findability. This is a clear public domain statement, an equivalent such as terms of use or computer protocol to digitally facilitate an operation (for instance a smart contract). Thus, the absence of a license does not indicate “open”, but rather creates legal uncertainty that will deter (in fact, in many cases legally prevent) reuse. Note also that the combination of resources with restrictive license conditions may lead to adverse effects, and ultimately preclude the use of the combined resources. In order to facilitate reuse, the license chosen should be as open as possible.
A current challenge is that there is currently no well-defined relationship(s) that can be used to distinguish a license that applies to the data being described, versus a license that applies to the metadata record itself, resulting in potential ambiguity in the interpretation of a license referred-to in the metadata record. Current choices are for communities to choose which usage license(s) or licensing requirements to reusable digital resources as well as to their metadata for its own purposes, but also consider broader reuse than originally anticipated or intended.
There are good reasons for choosing a CC0 license for data (http://sulab.org/2016/08/open-data-should-mean-cc0/) and these considerations should be assessed, alongside all other considerations, when a community decides on the license they wish to apply. It is critical, however, that a license is chosen. The community should then ensure that a qualified link to that license is contained in the metadata record.

Detailed provenance includes facets such as how the resource was generated, why it was generated, by whom, under what conditions, using what starting-data or source-resource, using what funding/resources, who owns the data, who should be given credit, and any filters or cleansing processes that have been applied post-generation. Provenance information helps people and machines assess whether a resource meets their criteria for their intended reuse, and what data manipulation procedures may be necessary in order to reuse it appropriately.
Current choices are for communities to choose a set of metadata descriptions to optimize provenance to optimally enable machine and human reusability for its own purposes. These choices, and, as argued before the richness of the provenance associated with a digital resource will strongly influence its actual reuse. Therefore, the implementation considerations for implementing according to this principle are inherently the same as described for principle F2, but now more focused on appropriateness for reuse than on findability per se.
Provenance descriptions can for instance be implemented following community specific templates according to the PROV-Template (https://provenance.ecs.soton.ac.uk/prov-template/) approach. These templates allow to predefine the structure of the intended collection of provenance information using variables which are later instantiated with appropriate data extracted from existing process output. Such templates also reduce the burden on community members to deeply understand the highly structured PROV ontology, and the well-defined data structures that emerge from its use - that is to say, PROV should not be treated as a simple vocabulary from which terms can be selected, but rather as a model that constrains how those terms must be used in relation to one another. Several early tools are under development to make the construction of FAIR metadata easier, including for instance CEDAR (https://more.metadatacenter.org/tools-training/outreach/cedar-template-model), CASTOR (https://www.castoredc.com/for-researchers/) and the knowledge models in the Data Stewardship Wizard (https://ds-wizard.org, doi:10.1162/dint_a_00043).

Where community standards or best practices for data archiving and sharing exist, they should be followed. Several disciplinary communities have defined Minimal Information Standards describing most often the minimal set of metadata items required to assess the quality of the data acquisition and processing and to facilitate reproducibility. Such standards are a good start, noting that true (interdisciplinary) reusability will generally require richer metadata. For a list of such standards, consult FAIRsharing (https://fairsharing.org/standards/, doi:10.1038/s41587-019-0080-8).
Current choices are for a community to choose which practices to use for data and metadata, taking into full consideration the relevant inter-domain interoperability requirements. Communities must then take-on the challenge of deciding which metadata elements, addressed within their community’s “boutique” standard(s), should be additionally represented using a more global standard (principles F2 and R1.2), even if this results in duplication of metadata, such that it can be used for search and interpretation by more generic, third-party agents.
An example of minimal information standards is the MIAME standard (doi:10.1038/ng1201-365), and various metadata profiles have been defined on top of specifications (e.g. various DCAT profiles).

On its surface, principle R1 appears very similar to principle F2. However, the rationale behind principle F2 is to enable effective attribute-based search and query (findability), while the focus of R1 is to enable machines and humans to assess if the discovered resource is appropriate for reuse, given a specific task. For example, not all gene expression data for a given locus are relevant to a study of the effects of heat stress. While inappropriate data may be discovered by the agent’s initial search (principle F2) for expression data about a given gene, here we address the ability to assess the discovered data based on suitability-for-purpose. This reiterates the need for providers to consider not only high-level metadata facets, that will assist in generic search, but also to consider more detailed metadata that will provide much more ‘operational’ instructions for re-use. In this setting, a wide variety of factors may be needed to determine whether a resource is suitable for inclusion in an analysis, and how to adequately process it.
The term “plurality” is used to indicate that the metadata author should be as generous as possible, not presuming who the consumer might be, and therefore provide as much metadata as possible to support the widest variety of use-cases and agent needs. The sub-principles R1.1, R1.2 and R1.3 define some critical types of attributes that contribute to R1.

The community should choose identifier registration service(s) that ensure global uniqueness for its digital resources.

The community should define identifier registration service(s) that ensure global uniqueness for its digital resources.

Nanopublications representing the FAIR Implementation Choices and Challenges Model

I hope to be able to move from the old nanopub servers to the new Nanopub Registry some time later this month.

I hope to be able to move from the old nanopub servers to the new Nanopub Registry some time late...

M4M.29.T.1 | M4M Vocabulary Training for PARC - by Panče Panov

FA.6.T.5 | FAIR Awareness training session 5
FA.6.T.5 | FAIR Awareness training session 5 - by Barbara Magagna

"misidentification of an animal that should have been identied as Vogtia serrata（ Moser, 1925） being reported as V. pentacantha（GenBank ID: AY937362）（personal observation from data in Dunn et al. 2005, unpublished sequences of V. serrata from Japan, and in situ images of the ROV-collected specimen from Monterey Bay）" reported in Lindsay et al. 2015. Corroborated by Phil Pugh on 2015-02-06

Reference
Lindsay, D.J., Grossmann, M.M., Nishikawa, J., Bentlage, B. and A.G. Collins (2015) DNA barcoding of pelagic cnidarians: current status and future prospects. Bulletin of the Plankton Society of Japan 62(1): 39–43.

Organism of Vogtia serrata (Moser, 1915) (species) - observed nucleotide sequence - AY937362.1

misidentification of an animal that should have been identied as Vogtia serrata（ Moser, 1925） being reported as V. pentacantha（GenBank ID: AY937362）（personal observation from data in Dunn et al. 2005, unpublished sequences of V. serrata from Japan, and in situ images of the ROV-collected specimen from Monterey Bay）" reported in Lindsay et al. 2015. Corroborated by Phil Pugh on 2015-02-06

Organism of Vogtia serrata (Moser, 1915) (species) - observed nucleotide sequence - AY935320.1

ITINERIS | Italian Integrated Environmental Research Infrastructures System - by (unknown)

FIP.32.T.1 | ITINERIS FIP session 1 - by Andrea Tarallo

A life cycle assessment (LCA) is a systematic analysis of a product or process's environmental impact throughout its entire life cycle. An LCA is performed in accordance with ISO guidelines and is based on compilation of an inventory of inputs and outputs and calculation of a range of mid-point and/or end-point measures of the environmental impact of the product or process.

Organism of Vogtia serrata (Moser, 1925) (species) - observed nucleotide sequence - AY935320.1

Organism of Vogtia serrata (Moser, 1925) (species) - observed nucleotide sequence - AY937362.1

A template that captures and annotates samples, reagents, and results from flow cytometry experiments by linking samples, experiments, and assay results. This template supports describing new experiments and biological samples or connecting existing ImmPort experiments and biological samples to assay results. It offers flexibility in linking new and existing ImmPort content, with key guidelines to follow: all experiment sample IDs in the template must be unique and not already stored in ImmPort. Both the biological sample and the experiment in the template can be new, or either one can already exist in ImmPort. This same template also appears on the web with other names like 'Flow Cytometry Experiment Samples'.
ImmPort Flow Cytometry Experiment Sample Template Version 3.36

A template that captures and annotates assay results for a sample by linking the sample, experiment, and interpreted results, providing a standardized format to facilitate the sharing of flow cytometry results.
ImmPort Flow Cytometry Derived Data Template Version 3.36

A template that captures and annotates the assay results for a sample by linking sample, experiment, and interpreted results together. It allows users to describe CyTOF (Mass Cytometry) results in a format to facilitate sharing of results.
ImmPort CyTOF Derived Data Template Version 3.36

A template that defines and annotates the antibody reagents assay platforms for ELISPOT experiment. This same template also appears on the web with other names like 'ELISPOT Reagent'.
ImmPort ELISPOT Reagents Template Version 3.36

A template defines and annotates control samples used in MBAA assays. It specifies that control samples, which are not assumed to be of biological origin, must always be new, while the associated experiment can be new or pre-defined. Each control sample serves as a unique key within the template. This same template also appears on the web with other names like 'Control Sample'.
ImmPort Control Samples Template Version 3.36

A template that describes a study’s essential elements, including title, goals, endpoints, criteria for participation, subject grouping (arms or cohorts), personnel, planned visits, and protocols, all within a single worksheet. It defines key aspects such as purpose, grouping, schedule of events, and references. After defining a study in ImmPort, additional details can be added using the study_design_edit template. The Basic Study Design template is organized into several sections or compound templates to comprehensively capture study design and protocol information.
ImmPort Basic Study Design Template Version 3.36

A template that captures the User Defined ID, Study ID, and Name for assessment panels, allowing panels to be new or pre-defined in any combination. The only requirement is that the Assessment Panel ID must be unique within the template.
ImmPort Assessment Panel Template Version 3.36

A template that captures essential details for assessment components, including User Defined ID, Assessment Panel ID, Subject ID, Planned Visit ID, Name, and Study Day. Assessments can be new or pre-defined, with any combination allowed, provided the Assessment Panel ID is unique within the template.
ImmPort Assessment Component Template Version 3.36

A template that defines and annotates assessment panels and their components, which represent responses or results recorded in Case Report Forms (CRFs) linked to a study. It captures essential fields, including Subject ID, Panel ID, User Defined ID, Planned Visit ID, Component Name, and Study Day, allowing users to define both panels and components in a single form. Panels can be new or pre-defined, with any combination allowed as long as the Assessment Panel ID is unique within the template.
ImmPort Assessment Template Version 3.36

A template that captures and annotates assay results from HLA typing experiments by linking samples, reagents, and results to experiments. This same template also appears on the web with other names like 'HLA Typing'.
ImmPort HLA Typing Results Template Version 3.36

A template that reports adverse events recorded for subjects in a study.
ImmPort Adverse Events Template Version 3.36

A template that captures samples, reagents, and results from image histology experiments. It links samples, experiments, and assay results, supporting the description of new or existing experiments and biological samples. Experiment sample IDs must be unique and not already stored in ImmPort.
ImmPort Image Histology Experiment Sample Template Version 3.36

A template that captures the study indicated interventions, concomitant medications, and substance use for subjects in a study.
ImmPort Intervention Template Version 3.36

A template to describe and annotate the results of CyTOF (Cytometry by Time-of-Flight) experiments, linking biological samples, experimental details, and assay outcomes in the ImmPort system. The template provides a flexible way to either document new experiments and biological samples or connect existing ones with new assay results. Each experiment sample entry must have a unique ID, ensuring that it is not already stored in ImmPort.
ImmPort CyTOF Experiment Sample Template Version 3.36

A template that defines and annotates the assay results for a sample by linking sample, experiment, and results together. More than one analyte's results per assayed sample may be reported by copying the group of columns 'Analyte', 'Number Of Spots Per Well', and 'Cell number per well Value', 'Cell number per well Unit' needed to describe each assay result. The experiment samples template allows you to describe to ImmPort new experiments and biological samples or link experiments and biological samples stored in ImmPort with assay results. All of the experiment sample IDs in the template must always be unique in the template and must not already be stored in ImmPort. The biological sample and the experiment in the template may be new or they both may be new.
ImmPort ELISPOT Experiment Sample Template Version 3.36

A template to capture and annotate the results of an ELISA (Enzyme-Linked Immunosorbent Assay) experiment, linking the biological samples, experiments, and assay results together. This template allows users to describe new experiments and biological samples or link existing ones in ImmPort with their respective assay results. Multiple analyte results can be reported for each assayed sample by duplicating the necessary columns, such as 'Analyte', 'Calculated Concentration Value', and 'Calculated Concentration Unit', to describe each result. Each experiment sample entry must have a unique ID that is not already stored in ImmPort.
ImmPort ELISA Experiment Sample Template Version 3.36

A template that captures samples, reagents, and results from KIR experiments. It links samples, experiments, and assay results, supporting the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not already stored in ImmPort. If the biological sample or experiment is new, required details must be provided, ensuring flexibility in linking new and existing content.
ImmPort KIR Experiment Template Version 3.36

A template to describe KIR typing results in a format to facilitate sharing of results. This same template also appears on the web with other names like 'KIR Typing'.
ImmPort KIR Typing Results Template Version 3.36

A template that defines and annotates the lab test panels, the lab tests and results. This template combines the functions of the legacy lab test panels and lab test results templates into a single template. The biological sample and the lab test panel can be either new or pre-defined in this template. Any combination is acceptable. The only restriction is that the biological sample is the key to template and must be unique within the template. This same template also appears on the web with other names like 'Lab Tests'.
ImmPort Clinical Lab Test Template Version 3.36

A template that describes Metabolomics Mass Spectrometry Assay results in a structure that can be interpreted by ImmPort to facilitate searching and display of results. This same template also appears on the web with other names like 'Mass Spectrometry Metabolomic Results'.
ImmPort Metabolomics Mass Spectrometry Results Template Version 3.36

A template that captures samples, reagents, and results from metabolomics mass spectrometry experiments. It links samples, experiments, and assay results, allowing for the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort. If the biological sample or experiment is new, required details must be provided, ensuring flexibility in linking new and existing content. This same template also appears on the web with other names like 'Mass Spectrometry Experiment Sample'.
ImmPort Metabolomics Mass Spectrometry Experiment Template Version 3.36

A template that captures samples, reagents, and results from proteomics mass spectrometry experiments. It links samples, experiments, and assay results, enabling the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort. If the biological sample or experiment is new, required details must be provided, ensuring flexibility in linking new and existing content. This same template also appears on the web with other names like 'Mass Spectrometry Experiment Sample'.
ImmPort Proteomics Mass Spectrometry Experiment Sample Template Version 3.36

A template that structures proteomics mass spectrometry assay results for interpretation, searching, and display within ImmPort. It links samples, experiments, and results, supporting multiple intensity results per assayed sample. This same template also appears on the web with other names like 'Mass Spectrometry Proteomic Results' and 'Proteomics Mass Spectrometry Assays Results'.
ImmPort Proteomics Mass Spectrometry Results Template Version 3.36

A template that captures samples, reagents, treatments, and results from Multiplex Bead Array Assays (MBAA) experiments. It links samples, experiments, and assay results, supporting the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort. If the biological sample or experiment is new, required details must be provided, ensuring flexibility in linking new and existing content.
ImmPort Multiplex Bead Array Assays Experiment Sample Template Version 3.36

A template that describes Multiplex Bead Array Assays (MBAA) results in a structure that can be interpreted by ImmPort to facilitate searching and display of results.
ImmPort Multiplex Bead Array Assays Results Template Version 3.36

A template that captures samples, reagents, and results from neutralizing antibody titer experiments. It links samples, experiments, and assay results, supporting multiple analyte results per sample by duplicating relevant columns such as 'Virus Strain' and 'Titration Dilution Value.' The template accommodates new experiments and biological samples or integrates assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort, with required details provided for any new biological samples or experiments.
ImmPort Neutralizing Antibody Titer Experiment Sample Template Version 3.36

A template that captures samples, reagents, and results for experiment types not characterized by other ImmPort templates. It links samples, experiments, and assay results, supporting the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort, with required details provided for any new biological samples or experiments. This template ensures flexibility when no specific experiment template is available. This same template also appears on the web with other names like 'Other' and 'Other Experiment Sample'.
ImmPort Experiment Sample Template Version 3.36

A template that captures samples, reagents, and results from QRT-PCR experiments. It links samples, experiments, and assay results, supporting multiple analyte results per sample by duplicating columns like 'Entrez Gene ID' and 'Threshold Cycles (Ct).' The template allows for the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Experiment sample IDs must be unique and not previously stored in ImmPort, with required details provided for any new biological samples or experiments.
ImmPort Quantitative PCR Experiment Sample Template Version 3.36

An optional template that enables updates to a study's design after the initial design is uploaded, including adding files, publications, or subjects. It defines and annotates study elements, such as weblinks and publications, that can be modified or added later. This same template also appears on the web with other names like 'Study Design Edit'.
ImmPort Edit Study Design Template Version 3.36

A template that captures information on public repository names and accessions, allowing one or more to be linked to an experiment sample. This same template also appears on the web with other names like 'Public Repositories'.
ImmPort Public Repository Template Version 3.36

A template that lists and annotates results associated with experiments, including assay outcomes linked to samples and experiments. Results can be in various file formats, such as PDF, Word, or Excel. This same template also appears on the web with other names like 'RNA Sequencing Transcripts Results'.
ImmPort RNA Sequencing Results Template Version 3.36

A template that defines and annotates the antibody reagents assay platforms for ELISA experiment. This same template also appears on the web with other names like 'ELISA Reagent'.
ImmPort ELISA Reagents Template Version 3.36

A template that lists and annotates protocols associated with lab tests, which may include PDF, Word, Excel, or other file types. It links protocol documents to studies, subjects, biological samples, or experiments. This same template also appears on the web with other names like 'Protocol'.

A template that defines and annotates detailed information about the mass tagged antibody reagents used in a CyTOF (Mass cytometry) experiment. This same template also appears on the web with other names like 'Mass Cytometry Reagent'.
ImmPort CyTOF Reagents Template Version 3.36

A template that captures detailed information about the reagents used in neutralizing antibody titer experiments. It defines and annotates reagents, including cell types and antibodies, particularly for experiments employing an ELISA approach. This same template also appears on the web with other names like 'Neutralizing Antibody Titer Reagent'.
ImmPort Neutralizing Antibody Titer Reagents Template Version 3.36

A template that captures detailed information about the antibody reagents used in flow cytometry experiments, defining and annotating their usage. This same template also appears on the web with other names like 'Flow Cytometry Reagent'.
ImmPort Flow Cytometry Reagents Template Version 3.36

A template that captures captures detailed information about the reagents used in RNA sequencing experiments and defines and annotates the assay platforms utilized for sequencing. This same template also appears on the web with other names like 'Sequencing Reagent'.
ImmPort RNA Sequencing Reagents Template Version 3.36

A template that defines and annotates microarrays assay platforms, capturing detailed information about the reagents used in Gene Expression and Genotyping experiments. This same template also appears on the web with other names like 'Array Reagent'.
ImmPort Array Reagents Template Version 3.36

A template that defines and annotates assay platforms for KIR typing and captures detailed information about the reagents used, which are linked to KIR experiment sample records. This same template also appears on the web with other names like 'KIR Typing System Reagents'.
ImmPort KIR Typing Reagents Template Version 3.36

A template that captures detailed information about the reagents used in a HLA typing experiment. This same template also appears on the web with other names like 'HLA Typing System Reagents'.
ImmPort HLA Typing Reagents Template Version 3.36

A template that captures detailed information about the reagents used in a HAI assays. These include the cell type used. The viral stain and concentration would be defined in the treatments.txt template. This same template also appears on the web with other names like 'HAI Reagent'.
ImmPort Hemaglutinnation Inhibition Reagents Template Version 3.36

A template that captures detailed information about the reagents used in a PCR experiment. This same template also appears on the web with other names like 'PCR Reagent'.
ImmPort PCR Reagents Template Version 3.36

A template that structures and annotates standard curves for interpretation within ImmPort, linking control sample concentrations and MFI to analyte concentrations in experiment samples. Standard curves must always be new and unique, while the associated experiment may be new or pre-defined. This template facilitates searching and display of results.
ImmPort Standard Curves Template Version 3.36

A template that defines and annotates key study subject elements, including demographics and subject-arm links within a study. This same template also appears on the web with other names like 'Subject Animals' and 'Subject Animal'.
ImmPort Animal Subjects Template Version 3.36

A template that records detailed information about human subjects from whom samples are collected for analysis. It defines and annotates key elements, including demographics and subject-arm links within a study. This same template also appears on the web with other names like 'Subject Humans' and 'Subject Human'.
ImmPort Human Subjects Template Version 3.36

A template that captures samples, reagents, treatments, and results from MBAA experiments. It defines and annotates assay platforms, including a row for each analyte assayed by the MBAA array.
ImmPort Multiplex Bead Array Assays Reagents Template Version 3.36

A template that documents in vitro modifications applied to samples, including the addition of molecules, temperature adjustments, and treatment durations. It supports three types of treatments: amount of agent, duration, and temperature. Treatments are required for experiment samples and optional for biological samples.
ImmPort Treatments Template Version 3.36

A template that captures samples, reagents, and results from RNA sequencing experiments. Links samples, experiments, and assay results, supporting the description of new experiments and biological samples or the integration of assay results with existing ImmPort content. Requires experiment sample IDs to be unique and not previously stored in ImmPort. This same template also appears on the web with other names like 'RNA Sequencing Transcripts Results Experiment Sample(s)'.
ImmPort RNA Sequencing Experiment Sample Template Version 3.36

An optional template designed to document groups of reagents used collectively in assays. It enables researchers to define and organize reagents as sets, streamlining reference and documentation processes for assay workflows. This same template also appears on the web with other names like 'Reagent Sets' and 'Reagent Set'.
ImmPort Reagents Set Template Version 3.36

A template that captures information on samples, reagents, and results from HLA typing experiments, linking samples, experiments, and assay results by defining and annotating the assay data for each sample. Supports the description of new experiments and biological samples or the integration of new assay results with existing ImmPort content. Requires experiment sample IDs to be unique and not already stored in ImmPort. This same template also appears on the web with other names like 'HLA Experiment' and 'HLA Experiment Sample(s)'.
ImmPort HLA Typing Experiment Sample Template Version 3.36

A template that captures detailed information about reagents used in experiments, such as Image Histology and Metabolomics Mass Spectrometry. It includes multiple tabs in the reagents.xlsx file to accommodate platform-specific details, addressing the varying reagent requirements across platforms. It is used to define and annotate reagents not covered by other reagent templates. This same template also appears on the web with other names like 'Other Reagents'.

This query returns all nanopub IDs for the given pubkey hash and (optionally) type.

prefix npa: <http://purl.org/nanopub/admin/>
prefix npx: <http://purl.org/nanopub/x/>

select distinct ?np where {
{ graph npa:graph {
?np npa:hasValidSignatureForPublicKeyHash ?_pubkeyhash .
?np npx:hasNanopubType ?__type_iri .
} }
union
{ graph npa:graph {
?np npa:hasValidSignatureForPublicKeyHash ?_pubkeyhash .
?np npx:invalidates ?npx .
?npx npx:hasNanopubType ?__type_iri .
} }
}

prefix npa: <http://purl.org/nanopub/admin/>
prefix npx: <http://purl.org/nanopub/x/>

select distinct ?np where {
{ graph npa:graph {
?np npa:hasValidSignatureForPublicKeyHash ?_pubkeyhash .
?np npx:hasNanopubType ?_type_iri .
} }
union
{ graph npa:graph {
?np npa:hasValidSignatureForPublicKeyHash ?_pubkeyhash .
?np npx:invalidates ?npx .
?npx npx:hasNanopubType ?_type_iri .
} }
}

M4M.29.T.2 | M4M Vocabulary Training for PARC 2 - by Dirk Devriendt

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.

SINTEF is one of Europe's largest research institutes, with multidisciplinary expertise within technology, natural sciences and social sciences. SINTEF is an independent foundation which, since 1950, has created innovation through development and research assignments for business and the public sector at home and abroad. SINTEF offers world-leading expertise in the field of materials technology. Our research covers the entire value chain, from ores and raw materials, state-of-the-art and environmentally-friendly production processes, to casting and moulding, assembly, and other advanced production processes.

A lightweight data-centric framework for semantic interoperability. DLite is a C implementation of the SINTEF Open Framework and Tools (SOFT), which is a set of concepts and tools for using data models (aka Metadata) to efficiently describe and work with scientific data.
DLite | SINTEF Open Framework and Tool DLIte

The University of Birmingham is an ambitious global top 100 university. Since our foundation in 1900 we have established a reputation for high quality fundamental research, research that addresses the challenges of our time and innovative, research-integrated teaching. The Centre for Environmental Research and Justice unites experts from many disciplines to address the escalating global issue of environmental pollution. CERJ's innovative work in regulatory and governance spaces combined with state-of-the-art scientific and data managemnet approaches is advancing the assessment of chemical pollution risks, remediation efforts, and supporting the right to a healthy environment.
UoB CERJ | University of Birmingham Centre for Environment Research and Justice

The Getty Thesaurus of Geographic Names ® (TGN), the Art & Architecture Thesaurus ® (AAT), the Union List of Artist Names ® (ULAN), the Cultural Objects Name Authority ® (CONA), and the Iconography Authority ™ (IA) are structured resources that can be used to improve access to information about art, architecture, and material culture. They are not simple 'value vocabularies,' but unique, rich knowledge bases in themselves. Through rich metadata and links, the Getty Vocabularies provide powerful conduits for knowledge creation, research, and discovery for digital art history and related disciplines.
TGN | Getty Thesaurus for Geographic Names

De Nederlandse basisclassificatie (NBC) is een van oorsprong Nederlands bibliotheek classificatie-schema speciaal ontwikkeld voor wetenschappelijke bibliotheken. Deze classificatie is eind jaren tachtig van de twintigste eeuw ontwikkeld onder leiding van de Koninklijke Bibliotheek (Nederland), in gebruik sinds 1990 en wordt sindsdien bijgewerkt. https://nl.wikipedia.org/wiki/Nederlandse_Basisclassificatie
BCL | Nederlandse Basisclassificatie = Dutch Basic Classification Codes

[nl]: De Nederlandse basisclassificatie (NBC) is een van oorsprong Nederlands bibliotheek classificatie-schema speciaal ontwikkeld voor wetenschappelijke bibliotheken. Deze classificatie is eind jaren tachtig van de twintigste eeuw ontwikkeld onder leiding van de Koninklijke Bibliotheek (Nederland), in gebruik sinds 1990 en wordt sindsdien bijgewerkt. https://nl.wikipedia.org/wiki/Nederlandse_Basisclassificatie; [en]: The Dutch Basic Classification (NBC) is an originally Dutch library classification scheme specially developed for academic libraries. This classification was developed in the late 1980s under the leadership of the Koninklijke Bibliotheek (Netherlands), in use since 1990 and has been updated since then. https://nl.wikipedia.org/wiki/Nederlandse_Basisklasse

registry for person names (not: works nor organisations) from the Dutch National Thesaurus for Author names (which also contains non-authors)
NTA | Nationale Thesaurus voor Auteursnamen ID

TOXic Process Ontology (TXPO) systematizes a wide variety of terms involving toxicity courses and processes. The first version of TXPO focuses on liver toxicity. The TXPO contains an is-a hierarchy that is organized into three layers: the top layer contains general terms, mostly derived from the Basic Formal Ontology. The intermediate layer contains biomedical terms in OBO foundry from UBERON, Cell Ontology, NCBI Taxon, ChEBI, Gene Ontology, PATO, OGG, INOH, HINO, NCIT, DOID and Relational ontology (RO). The lower layer contains toxicological terms.

Describing digital objects based on DCAT for MAC

Template: Describing digital objects based on DCAT for MAC

Severe COVID-19 Is Characterised by Perturbations in Plasma Amines Correlated with Immune Response Markers, and Linked to Inflammation and Oxidative Stress

Demo for MAC: Such a nanopublication expresses citation relations of a given article based on the CiTO relation types.
Declare associations between an article and a digital object

Template: Declare associations between an article and a digital object

DOI (https://doi.org/10...) or other URL of the cited digital object

SKOS | Simple Knowledge Organization System

URI of research output (e.g. publication)

Subjective synonymy based on morphological comparison of the type specimens of the two species names

Onthophagus mactatus Klug, 1855 (species) - ICZN subjective synonym - Onthophagus (Furconthophagus) lamelliger Gerstaecker, 1871 (species)

Onthophagus mactatus Klug, 1855 (species)

Onthophagus (Furconthophagus) lamelliger Gerstaecker, 1871 (species)

Onthophagus (Furconthophagus) lamelliger Gerstaecker, 1871 (species) - ICZN subjective synonym - Onthophagus mactatus Klug, 1855 (species)

Onthophagus (Onthophagus) talpa Fåhraeus, 1857 (species) - ICZN subjective synonym - Onthophagus mactatus Klug, 1855 (species)

Onthophagus (Onthophagus) talpa Fåhraeus, 1857 (species)

Onthophagus (Onthophagus) omostigma Orbigny, 1902 (species) - ICZN subjective synonym - Onthophagus (Onthophagus) ganalensis Gestro, 1895 (species)

Onthophagus (Onthophagus) ganalensis Gestro, 1895 (species)

Onthophagus (Onthophagus) omostigma Orbigny, 1902 (species)

The FAIR Data Point is a FAIR-compliant metadata repository solution that allows data stewards to define their own and/or reuse existing semantically-rich metadata schemas.

The specification defines the architecture, metadata structure and schema, API and validation rules for a FAIR Data Point.

The digital object identifier (DOI) system is widely used within the biomedical domain.

DCAT is recommended by W3C and DCAT is the foundation for open dataset descriptions in the European Union public sector and was adapted by the ISA programme (Interoperability solutions for public administrations) of the European Commission.

Central location for data storage and analysis for the neurodegenerative disease community.

Public landing point for the EPND platform created for the alzheimer community and other interested parties .

European node for data storage and analysis for the neurodegenerative disease community.

Widely accepted protocol of communication for web services, REST aims for fast performance, reliability, and the ability to grow.

OpenID is an open standard and decentralized authentication protocol promoted by the non-profit OpenID Foundation. It is widely accepted and used to perform authentication, i.e. identity verification of a user.

OAuth 2.0 is a widely accepted open standard for access delegation and it allows clients to access data without sharing user's credentials, it is thus a protocol for authorisation purposes.

JSON is a language-independent and open standard file format and data interchange format that uses human-readable text. It is therefore chosen due to its flexibility.

RDF is a directed graph composed of triple statements and the format of choice for the semantic web community.

OWL is the recommended language by W3C to represent ontologies and we use medical ontologies to make data semantically interoperable.

DCAT is widely used in the medical domain, and we plan to use fair data points that also rely on DCAT.

We use shacl to go from an open world concept in ontologies to a more closed world solution that guarantees interoperability between datasets.

We use the cedar workbench to reuse and create metadata json templates, then export these to the github page of the community.

SNOMED is the most used vocabulary in the medical domain.

FAIR data points take care of a lot of the the metadata needed for Findability and Reusability, and a uniform open way of Accessing the data. The FAIR data point also addresses the Interoperability of the metadata it stores, but it leaves the Interoperability aspects for the data itself to the data provider.

EPND Case study 1: This is the FIP of EPND Case study 1

FIP.32.T.1 | ITINERIS FIP session 2 - by Sander van Boom

FIP.33.T.1 | FAIR Implementation Profile Training

FIP.33.T.1 | FAIR Implementation Profile Training - by Norbert van Dijk

has description source
Denotes the source of the description that is asserted via dct:description

The service provides authorisation and authentication to FLUXNET users to access the FLUXNET database and download FLUXNET datasets
Authentication service used by FLUXNET network

AccessClinicalData@NIAID is a NIAID cloud-based, controlled access, secure data platform that enables sharing of and access to reports and data sets from NIAID COVID-19 and other sponsored clinical trials for the basic and clinical research community.

AgroPortal is an ontology repository for agronomy as well as food, plant, agriculture and biodiversity sciences. It provides ontology hosting, search, versioning, visualization, comment, and recommendation; enables semantic annotation; stores and exploits ontology alignments; and enables interoperation with the semantic web. To align with the needs of the agronomy community, AgroPortal uses SKOS vocabularies and trait dictionaries) and supported features (offering detailed metadata and advanced annotation capabilities).

PURLs are used frequently, but is not limited to it.

The assertions of a nanopublication can be considered as data.

This server is used to store nanopublications.

This server is used for sparqling nanopubs.

This server is used for creating, browsing, updating nanopublications

FA.5.T.3 | ITINERIS FAIR Awareness session 3 - by Andrea Tarallo

SnowTerm is an example of a structured reference multilingual scientific and technical vocabulary, covering the terminology of a specific knowledge domain in the polar and the mountain environment. The thematic areas, covered at present, deal with snow and ice physics, snow and ice morphology, snow and ice radiometry, remote sensing and GIS applied to cryosphere environment, sea ice, avalanches, glaciers.
SnowTerm | SnowTerm Thesaurus on Snow and Ice

artificial intelligence - field of computer science that develops and studies intelligent machines

think this is overrated: artificial intelligence

nanopublication - A small knowledge graph snippet with metadata that is to be treated as an independent (scientific) publication.

think this is overrated: nanopublication