Open FAIR
E701305
Open FAIR is a risk analysis and quantification framework that provides a standardized, quantitative approach to assessing and comparing information and operational risks.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Open FAIR canonical | 1 |
| Open FAIR standard | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7894541 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Open FAIR Context triple: [The Open Group, developsStandard, Open FAIR]
-
A.
OPEN Government Data Act
The OPEN Government Data Act is a U.S. law that requires federal agencies to manage their information as open, machine-readable data by default to promote transparency, accessibility, and reuse.
-
B.
OAI
OAI is the Office of Anticorruption and Integrity, a body typically responsible for promoting transparency, preventing corruption, and ensuring ethical conduct within an organization or institution.
-
C.
FEAS
FEAS is the Faculty of Engineering and Architectural Science at Toronto Metropolitan University, encompassing programs in engineering, architecture, and related applied sciences.
-
D.
Open Knowledge Foundation
Open Knowledge Foundation is a global nonprofit organization that promotes open data and open knowledge to foster transparency, innovation, and civic engagement.
-
E.
Enhanced Open
Enhanced Open is a Wi‑Fi Alliance security standard that improves privacy on open wireless networks by encrypting data without requiring a password.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Open FAIR Target entity description: Open FAIR is a risk analysis and quantification framework that provides a standardized, quantitative approach to assessing and comparing information and operational risks.
-
A.
OPEN Government Data Act
The OPEN Government Data Act is a U.S. law that requires federal agencies to manage their information as open, machine-readable data by default to promote transparency, accessibility, and reuse.
-
B.
OAI
OAI is the Office of Anticorruption and Integrity, a body typically responsible for promoting transparency, preventing corruption, and ensuring ethical conduct within an organization or institution.
-
C.
FEAS
FEAS is the Faculty of Engineering and Architectural Science at Toronto Metropolitan University, encompassing programs in engineering, architecture, and related applied sciences.
-
D.
Open Knowledge Foundation
Open Knowledge Foundation is a global nonprofit organization that promotes open data and open knowledge to foster transparency, innovation, and civic engagement.
-
E.
Enhanced Open
Enhanced Open is a Wi‑Fi Alliance security standard that improves privacy on open wireless networks by encrypting data without requiring a password.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
information risk framework
ⓘ
risk analysis framework ⓘ risk quantification framework ⓘ |
| aimsTo |
enable comparison of different risks
ⓘ
improve consistency of risk assessments ⓘ link risk to business impact ⓘ standardize risk terminology ⓘ |
| appliesTo |
multiple industries
ⓘ
organizations of various sizes ⓘ |
| characteristic |
model-based
ⓘ
quantitative ⓘ scenario-based ⓘ technology-agnostic ⓘ |
| comparedWith | qualitative risk assessment methods ⓘ |
| defines | risk in terms of loss event frequency and loss magnitude ⓘ |
| emphasizes |
probabilistic thinking
ⓘ
separation of frequency and magnitude in risk ⓘ use of ranges instead of point estimates ⓘ |
| focusesOn |
information risk
ⓘ
operational risk ⓘ |
| hasComponent |
control analysis
ⓘ
loss event frequency model ⓘ loss magnitude model ⓘ threat event frequency model ⓘ vulnerability model ⓘ |
| hasFullName | Open Factor Analysis of Information Risk ⓘ |
| models |
control strength
ⓘ
loss event frequency ⓘ loss magnitude ⓘ probable loss exposure ⓘ threat event frequency ⓘ vulnerability ⓘ |
| output |
financially expressed risk metrics
ⓘ
quantified loss exposure ⓘ risk distributions ⓘ |
| provides |
quantitative approach to risk analysis
ⓘ
standardized approach to risk analysis ⓘ |
| supports |
decision making under uncertainty
ⓘ
risk comparison ⓘ risk quantification ⓘ |
| usedFor |
IT risk management
ⓘ
communicating risk in financial terms ⓘ comparing risk scenarios ⓘ cybersecurity risk analysis ⓘ information security risk analysis ⓘ operational risk analysis ⓘ prioritizing risk mitigation investments ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Open FAIR Description of subject: Open FAIR is a risk analysis and quantification framework that provides a standardized, quantitative approach to assessing and comparing information and operational risks.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Open FAIR