The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index; 1 of the 13 sources its claims cite were checked for support.
Is Semantic Information Meaningful Data?
Open accessAbstract
There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
Floridi argues that the Standard Definition of Information (SDI) as well-formed, meaningful data gives only necessary but insufficient conditions for semantic information, because truth-values do not supervene on information and misinformation is pseudo-information rather than a type of information. He revises SDI into RSDI by adding a fourth, necessary truth-condition, aligning with the Dretske–Grice approach.
Key findings
- SDI is formulated as: σ is DOS (declarative, objective, semantic) information iff (1) σ consists of n data (d), n ≥ 1; (2) the data are well-formed; (3) the well-formed data are meaningful. Floridi holds these are necessary but not sufficient.
- The paper rejects alethic neutrality (AN) — the claim that meaningful, well-formed data qualify as information regardless of truth-value — and with it the consequences that false information (FI) is a genuine type of information, that tautologies qualify as information (TA), and that "it is true that σ" is non-redundant (TI).
- Nine proposed reasons for treating false information as a type of semantic information (FI.1–FI.9) are each argued to be unconvincing; two positive arguments are given that misinformation is pseudo-information: (a) "false" in "false information" is attributive and negative, so the compound fails the splitting test (unlike "digital information"), and (b) if false information counted as information, semantic erosion by operators like "not" would be inexplicable.
- The revised definition (RSDI) adds a fourth condition: the meaningful, well-formed data are truthful. Five areas of application are listed, including critique of deflationary theories of truth, mathematical/analytic propositions, empty names, the standard definition of knowledge, and a quantitative theory of semantic information based on truth-values and degrees of discrepancy rather than probability distributions.
Methods
- Conceptual/philosophical analysis, not empirical: the paper works within situation logic (Israel and Perry; Devlin), using the symbol σ and the term "infon" for discrete items of information irrespective of semiotic code or physical implementation.
- The argument proceeds by (i) formalising SDI and its four endorsed neutralities (typological, taxonomic, ontological, genetic), (ii) rejecting the fifth, alethic neutrality, (iii) rebutting nine reasons for counting false information as information, and (iv) supplying two constructive arguments that it is pseudo-information.
- Illustrative examples are used throughout (e.g. a dinner-guests scenario, a "false constable," the EREP CD-ROM database, Poe's raven as a unary device, hieroglyphics before the Rosetta Stone).
Limitations
- Stated by the paper: the rejection of TA (tautologies as information) is not pursued because it is "crucially connected to the interpretation of mathematical and analytic truths" and is left to another paper; arguments against AN based on deflationary theories of truth and a criticism of TI are also deferred as beyond the paper's scope.
- Stated by the paper: the analysis is deliberately restricted to declarative, objective and semantic (DOS) information; non-declarative uses of "information" (stipulations, invitations, orders, instructions, game moves, music files, digital paintings) and the mathematical/pragmatic senses tied to uncertainty, probability and decision utility are explicitly excluded.
- Evident from the text: the argument is conceptual and illustrative rather than empirical, resting on linguistic intuitions (e.g. the attributive/predicative test, the "false constable" analogy) and on the plausibility of the semantic-erosion argument, with no data or formal proof offered for the central claim.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
44 Own interpretation · 3 Not checked yet · 3 No basis given · 2 Sources not found · 1 Partly supported · accuracy not yet measured
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“None of these consequences seems ultimately defensible”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is incorrect because truth-values do not supervene on semantic information”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
- The authors state this as an assumption: Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“their rejection forces a revision of AN and hence of SDI.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“none of the reasons for interpreting misinformation as a type of semantic information is convincing”
- Also stated in: § It follows that · p. 10 · hedged
“none of the main reasons that could be adduced for interpreting false information as a type of information is convincing”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The reasons considered in the paper are the main reasons for interpreting misinformation as a type of semantic information.
- Also stated in: § It follows that · p. 10 · hedged
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“there are compelling reasons to treat it as pseudo-information”
- Also stated in: § It follows that · p. 10 · boosted
“there are compelling reasons to treat false and tautological information as pseudo-information”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § It follows that · p. 10 · boosted
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a consequence, SDI is revised to include a necessary truth-condition.”
- Also stated in: § 1. Introduction · p. 2 · plain
“It follows that SDI needs to be revised by adding a necessary truth-condition.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The rejection of FI alone is sufficient to force a revision of AN and hence of SDI.
- Also stated in: § 1. Introduction · p. 2 · plain
None of the sources cited for this claim have been checked yet.
In the paper
“The bipartite account has gained sufficient consensus to become an operational standard in fields that tend to deal with data and information as reified entities”
What the sources say
- Not matchedcites Davis and Olson (1985)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Silver and Silver (1989)
- Not matchedcites Checkland and Scholes (1990)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Meaning is not (at least not only) in the mind of the user.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information.”
- Also stated in: § 2.1. An Analysis of the Standard Definition of Information · p. 9 · plain
“insofar as SDI provides necessary conditions for σ to qualify as DOS information, it also endorses four types of neutrality: TN, TaxN, ON and GN.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § 2.1. An Analysis of the Standard Definition of Information · p. 9 · plain
- Probably not a substantial claim. 26
- It may state two separate claims as one. 8
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“There is no consensus yet on the definition of semantic information.”
- Also stated in: § 1. Introduction · p. 1 · plain
“recent surveys have shown no consensus on a single, unified definition of semantic information.¹”
What the sources say
- Partly supportedcites Floridi [2002], [2004a], [2005] sourceExperimental — accuracy not yet measured
Section 5 (p. 137) says there is no consensus on a single, unified definition of information. It mentions a proposed revision to the definition of semantic information, but does not specifically say there is no consensus on that narrower definition. (LLM, conf=0.85)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § 1. Introduction · p. 1 · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ON) no information without data representation.”
plain- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“According to SDI, alethic values are not embedded in, but supervene on semantic information:”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- The authors state this as an assumption: Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TaxN) a datum is a relational entity.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“GN) δ can have a semantics independently of any informee.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The question is whether it is rigorous enough to be applied in the context of an informationtheoretical epistemology. We shall see that this is not the case”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“FI may be coupled to some true, metainformation M that the source of FI is not fully reliable. What now counts as information is the true M, not the false FI.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Over the last three decades, most analyses have supported a definition of DOS information in terms of data + meaning.”
What the sources say
- Not matchedcites Davis and Olson (1985)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Silver and Silver (1989)
- Not matchedcites Checkland and Scholes (1990)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The standard definition of DOS information (SDI) provides necessary but insufficient conditions for the qualification of data as information.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is not the case, and hence it would be a mistake or an act of misinformation to assert, that p constitutes information about the number of natural satellites orbiting around the earth and is also a falsehood.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“misinformation (false information) has turned out to be not a type of information but rather pseudo-information.”
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
“False information is not an inferior kind of information; it just is not information.”
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
“[...] false information and mis-information are not kinds of information——any more than decoy ducks and rubber ducks are kinds of ducks.”
What the sources say
- Not matchedcites Dretske (1981), 45
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Grice (1989), 371
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is not an oxymoron, but a way of specifying that the contents in question do not conform to the situation they purport to map.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it also endorses four types of neutrality: TN, TaxN, ON and GN.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The confusion about the nature of false information seems to be generated by a misleading analogy.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the attributive use can be either positive or negative.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“S.4 is one of the earliest and most popular formulations of SDI”
What the sources say
- Not matchedcites Bateson (1973)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If false information were a genuine type of information it should pass the splitting test. It does not, so it is not.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“to exchange (receive, sell, buy, etc.) false DOS information about x, e.g. the number of moons orbiting around the earth, is to exchange (receive, sell, buy, etc.) no DOS information at all about x, only meaningful and well-formed data, that is semantic content.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we ordinarily speak of false information when what we mean is misinformation, i.e. no information at all.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if they are not truthful, they can only constitute misinformation”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“this merely shows that FI is a compound in which only the true component B qualifies as information.”
plain- Asserted: fails — The authors may not put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“More recently, the bipartite account has begun to influence the philosophy of computing and information as well”
What the sources say
- Not matchedcites Chalmers [1996]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Floridi [1999]
- Not checked — no full text of the sourcecites Franklin [1995]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In conclusion, there seem to be no good reason to treat false information as a type of information.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: Ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it follows that SDI needs to be modified, to include a fourth condition about the positive alethic nature of the data in question”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if the mathematical theorem is not correct (if p is false), it must be concluded that Q is misinformed (i.e. not informed) that p (Q does not have any information about the theorem).”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“SDI.3 only requires the δ to be provided with a semantics already.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“a false constable (attributive use) is clearly not a specific type of constable, but not a constable at all (negative use)”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DTT may be satisfactory as theories of truth-ascriptions while being inadequate as theories of truthfulness”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The authors state this as an assumption.
Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
“where objective semantic information is taken to have a declarative or factual value, i.e., it is suppose to be correctly qualifiable alethically.”
The paper relies on this without support.
The reasons considered in the paper are the main reasons for interpreting misinformation as a type of semantic information.
“none of the main reasons that could be adduced for interpreting false information as a type of information is convincing”
The authors state this as an assumption.
The rejection of FI alone is sufficient to force a revision of AN and hence of SDI.
“For the sake of simplicity, in the rest of this article only the rejection of FI will be pursued”
The paper relies on this without support.
Sources of information are usually supposed to be truth-oriented or truth-tracking by default.
“sources of information are usually supposed to be truth-oriented or truth-tracking by default”
The paper relies on this without support.
The cloth of semantic information can be, and indeed is, often undone by equally semantic means.
“We know that the cloth of semantic information can be, and indeed is, often undone by equally semantic means.”
The paper relies on this without support.
Ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.
“ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“The most articulate defense of VTNN has been offered by Floridi (2005, 2007), who gives two main arguments in support of the thesis that false ''nonnatural information'' is not really information: the argument from splitting and the argument from semantic loss .”
From INFORMATION WITHOUT TRUTH (2010) · cites this paper as Floridi 2005
The cited source says what the claim attributes to it.
In the citing paper
“The most articulate defense of VTNN has been offered by Floridi (2005, 2007), who gives two main arguments in support of the thesis that false ''nonnatural information'' is not really information: the argument from splitting and the argument from semantic loss .”
From INFORMATION WITHOUT TRUTH (2010) · cites this paper as Floridi 2005
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 2. The Standard Definition of Information · p. 3
“Chalmers [1996]”
§ References · p. 19
“Chalmers, D. J. 1997, The Conscious Mind: in Search of a Fundamental Theory (Oxford: Oxford University Press).”
Citations
Cites
Foxman, D., & Bateson, G. (1973) · The Western Political Quarterly · doi:10.2307/446833 · Cited by 7,263
Cybernetics or Control and Communication in the Animal and the Machine
Wiener, N. (2019) · The MIT Press eBooks · doi:10.7551/mitpress/11810.001.0001 · Cited by 5,085
(1989) · Cited by 4,498
The conscious mind: in search of a fundamental theory
(1996) · Choice Reviews Online · doi:10.5860/choice.34-2091 · Cited by 4,150
Soft Systems Methodology in Action
Gough, T., Checkland, P. B., & Scholes, J. (1991) · Journal of the Operational Research Society · doi:10.2307/2583669 · Cited by 3,414
Knowledge and the Flow of Information.
Alston, W. P., & DRETSKE, F. I. (1983) · The Philosophical Review · doi:10.2307/2184492 · Cited by 3,283
Computer science as empirical inquiry
Newell, A., & Simon, H. A. (1976) · Communications of the ACM · doi:10.1145/360018.360022 · Cited by 2,351
The Human Use of Human Beings: Cybernetics and Society
Miles, S. B., & Wiener, N. (1951) · Land Economics · doi:10.2307/3159747 · Cited by 1,664
Complexity, Entropy And The Physics Of Information
Zurek, W. H. (2018) · CRC Press eBooks · doi:10.1201/9780429502880 · Cited by 1,451
Management Information Systems: Conceptual Foundations, Structure, and Development
Davis, G. B. (1985) · CERN Document Server (European Organization for Nuclear Research) · Cited by 1,341
Research works printed but not linked: 2
- T. R. Colburn, 2000 , "Information, Thought, and Knowledge",Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics(Orlando FL, July 23-26, 2000), vol. X, 467 -471 .
- Shannon C. E., 1993, Collected Papers
Cited by
Sorted by citations
Items 101–200 of 376
I nternet information triangulation: Design theory and prototype evaluation
Wijnhoven, F., & Brinkhuis, M. (2014) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23203 · Cited by 14
“And despite all these efforts, it may remain complicated if not impossible for expert services or search engines to filter out all intentionally or unintentionally incorrect content (Floridi, 2005).”
BackgroundOn the Norms of Visual Argument: A Case for Normative Non-revisionism
Godden, D. (2016) · Argumentation · doi:10.1007/s10503-016-9411-9 · Cited by 14
A geometric analysis of time series leading to information encoding and a new entropy measure
Majumdar, K., & Jayachandran, S. (2017) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2017.07.006 · Cited by 14
“It is pertinent to note here that semantic information is a well studied area (Carnap and Bar-Hillel 1952), but there is no universally accepted definition for it (Floridi 2005).”
BackgroundMethodHenschke, A. (2020) · Moral Philosophy and Politics · doi:10.1515/mopp-2019-0056 · Cited by 14
Putting Information First: Luciano Floridi and the Philosophy of Information
Allo, P. (2011) · doi:10.1002/9781444396836.ch1 · Cited by 14
Deflating the deflationary view of information
Lombardi, O., Fortín, S., & López, C. (2015) · European Journal for Philosophy of Science · doi:10.1007/s13194-015-0128-7 · Cited by 13
Towards a Methodology for Knowledge Reuse Based on Semantic Repositories
Fraga, A., Lloréns, J., & Génova, G. (2018) · Information Systems Frontiers · doi:10.1007/s10796-018-9862-7 · Cited by 13
The Downward Path to Epistemic Informational Structural Realism
Beni, M. D. (2017) · Acta Analytica · doi:10.1007/s12136-017-0333-4 · Cited by 12
Does semantic information need to be truthful?
Lundgren, B. (2017) · Synthese · doi:10.1007/s11229-017-1587-5 · Cited by 15
“Ever since Luciano Floridi re-invigorated the veridicality thesis (that [semantic] information must be true, or truthful), the discussion of this issue has been expanding (see Floridi 2004, 2005; cf. Fetzer 2004; Dodig-Crnkovic 2005).”
BackgroundInfluentialWijnhoven, F. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22622 · Cited by 12
Public participatory GIS in community-based disaster risk reduction
Kemp, R. B. (2008) · tripleC Communication Capitalism & Critique Open Access Journal for a Global Sustainable Information Society · doi:10.31269/triplec.v6i2.81 · Cited by 12
Successful visual epistemic representation
Bolinska, A. (2015) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2015.09.005 · Cited by 14
Pre-cognitive Semantic Information
Vakarelov, O. (2010) · Knowledge, technology & policy/Knowledge in society/Knowledge, technology, & policy · doi:10.1007/s12130-010-9109-5 · Cited by 12
“And so do Dretske (1981); Fetzer (2004); Floridi (2003, 2010, 2004, 2005, 2007), and many others, see (Floridi 2010: 3.4) for extensive references.”
InfluentialThe role of quantum mechanics in cognition-based evolution
Marshall, P. (2023) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2023.04.007 · Cited by 11
What is a Philosophical Question?
Floridi, L. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780198833635.003.0001 · Cited by 11
Self-citationKnowledge from data in the built environment
Starkey, C., & Garvin, C. (2013) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12202 · Cited by 11
Defining the notion of ‘Information Content’ and reasoning about it in a database
Xu, K., Feng, J., & Crowe, M. K. (2008) · Knowledge and Information Systems · doi:10.1007/s10115-008-0129-3 · Cited by 11
“Information must be veridical [5, p.10], that is, must relate to a contingent truth [ 18 ] while for data there is no such requirement.”
BackgroundIs Data Labor? Two Conceptions of Work and the User-Platform Relationship
Jonker, J. D. (2024) · Business Ethics Quarterly · doi:10.1017/beq.2024.25 · Cited by 12
“While there is a diverse way in which philosophers relate the terms “ information, ” “ truth, ” “ data, ” and “ knowledge ” (e.g. Boisot and Canals 2004; Floridi 2005; Leonelli 2015; Flyverbom and Whelan 2019), what these mappings share is the understanding that data is what lies closest to the…”
Vignoli, R. G., Rabello, R., & de Almeida, C. C. (2021) · Encontros Bibli Revista Eletrônica de Biblioteconomia e Ciência da Informação · doi:10.5007/1518-2924.2021.e75576 · Cited by 10
“Nesta, os “[...] valores de verdade não sobrevêm à informação semântica” (FLORIDI, 2005, p. 351, tradução nossa), ainda que o valor de verdade deva ser considerado como aspecto a ser considerado para a dimensão semântica da informação.”
InfluentialData Science as an Interdiscipline: Historical Parallels from Information Science
Mayernik, M. S. (2023) · Data Science Journal · doi:10.5334/dsj-2023-016 · Cited by 14
Intentional Models as Essential Scientific Tools
Hochstein, E. (2013) · International Studies in the Philosophy of Science · doi:10.1080/02698595.2013.813251 · Cited by 10
Rebooting the new evidence scholarship
Welch, J. R. (2020) · The International Journal of Evidence & Proof · doi:10.1177/1365712720943329 · Cited by 10
“Floridi (2004, 2005) upholds the affirmative; Fetzer (2004), the negative.”
BackgroundINFORMATION AND KNOWLEDGE À LA FLORIDI
Adams, F. (2010) · Metaphilosophy · doi:10.1111/j.1467-9973.2010.01630.x · Cited by 10
The concepts of representation and information in explanatory theories of human behavior
Ramos, R. T. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.01034 · Cited by 10
“The study of semantic information has focused in a number of problems, most of them systematized by Floridi (2005).”
BackgroundMarchetti, G. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.913309 · Cited by 9
“Therefore, those theories of information - such as Dretske (1981), Floridi (2005), and Mingers and Standing’s (2014) – which maintain that information is fundamentally objective and exists independently of the agent that produces it, cannot adequately account for the information provided by the PAC.”
BackgroundYesmin, S. (2023) · Science & Technology Libraries · doi:10.1080/0194262x.2023.2238005 · Cited by 9
“Misinformation that is false, inaccurate (Fernandez and Alani 2018; Floridi 2005; Fox 1983; Zhang et al. 2018), without the intention of causing harm (Wardle and Derakhshan 2017); person disseminating it with the believes that it is true (Wardle and Derakhshan 2018) can misinform and misguide…”
BackgroundAn integrative framework of information as both objective and subjective
Jarrahi, M. H., Ma, Y., & Goray, C. (2021) · Journal of Information Science · doi:10.1177/01655515211014149 · Cited by 11
“For these reasons, Floridi [13] argues ‘work on the concept of information is still at that lamentable stage when disagreement affects even the way in which the problems themselves are phrased and framed’ (p.”
BackgroundContext granulation and subjective-information quantification
Pal, S. K., & Banerjee, R. (2013) · Theoretical Computer Science · doi:10.1016/j.tcs.2012.12.034 · Cited by 9
Bossler, L. F., Buchwald, A., & Spohrer, K. (2024) · Information Systems Research · doi:10.1287/isre.2022.0065 · Cited by 9
Mapping terminological variation and ideology in data protection laws
Pei, J., & Cheng, L. (2020) · Terminology International Journal of Theoretical and Applied Issues in Specialized Communication · doi:10.1075/term.00049.pei · Cited by 8
Designing the future of forensic science: mêtis and forensic intelligence
Taylor, M. L. (2023) · Australian Journal of Forensic Sciences · doi:10.1080/00450618.2023.2218429 · Cited by 8
Digital Content Reuse in Dynamic Settings: An Organizing Typology for Digital Content Users
Mitchell, B. T., & Mitchell, R. K. (2012) · Cited by 8
Information Waste on the World Wide Web and Combating the Clutter
Amrit, C., Wijnhoven, F., & Beckers, D. (2015) · University of Twente Research Information · doi:10.18151/7217266 · Cited by 8
A framework and implementation of information content reasoning in a database
Wu, X., & Feng, J. (2009) · Cited by 8
The Crescent Lab: A smart home lab for students
Burnell, L. J., Sánchez, A., Priest, J. W., et al. (2006) · Mexican International Conference on Computer Science · doi:10.1109/enc.2006.33 · Cited by 8
“Everything else is just information” Albert Einstein”
Correspondence Theory of Semantic Information
Miłkowski, M. (2021) · The British Journal for the Philosophy of Science · doi:10.1086/714804 · Cited by 10
Infrastructure network protection under uncertain impacts of weaponized disinformation campaigns
Jamalzadeh, S., Barker, K., González, A. D., Radhakrishnan, S., & Bessarabova, E. (2025) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2025.130365 · Cited by 7
Disengagement in the Digital Age: A Virtue Ethical Approach to Epistemic Sorting on Social Media
Worden, K. J. (2019) · Moral Philosophy and Politics · doi:10.1515/mopp-2018-0066 · Cited by 7
Information and Design: Book Symposium on Luciano Floridi’s the Logic of Information
Gorichanaz, T., Furner, J., Ma, L., Bawden, D., Robinson, L., Dixon, D., Herold, K. R., Søe, S. O., Martens, B. V. D. V., & Floridi, L. (2020) · Journal of Documentation · doi:10.1108/jd-10-2019-0200 · Cited by 8
Self-citationSantos-d’Amorim, K., & Miranda, M. K. F. D. O. (2021) · Redalyc (Universidad Autónoma del Estado de México) · Cited by 7
A minimum entropy criterion for distribution selection for measurement uncertainty analysis
Huang, H. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/ad1476 · Cited by 7
“In this paper, to avoid confusion, we use the term ‘information’ without an adjective to refer to ‘meaning-ful information’ or the ‘DOS information’ (DOS stands for declarative, objective, and semantic) in terms of data + meaning (Floridi 2005).”
One or Many Concepts of Information?
Sommaruga, G. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-00659-3_10 · Cited by 7
“1 (Floridi 2003b:40f) and (Floridi 2005a: ).”
BackgroundInformation Processing as an Account of Concrete Digital Computation
Fresco, N. (2012) · Philosophy & Technology · doi:10.1007/s13347-011-0061-4 · Cited by 8
“The most common informal analysis of semantic information over the last three decades characterised it in terms of data+meaning (Floridi 2005: pp. 351 – 359).”
BackgroundThe Epistemology and Ethics of Internet Information
Spence, E. H. (2009) · Physica-Verlag eBooks · doi:10.1007/978-3-7908-2148-2_35 · Cited by 7
“Following Luciano Floridi it will define information as “well formed meaningful data that is truthful” (2005) [3] and following Fred Dretske it will define information as “an objective commodity capable of yielding knowledge”; knowledge in turn will be defined as “information caused belief” (1999) [4].”
MethodSeven Challenges for Risk Communication in Today’s Digital Era: The Emergency Manager’s Perspective
Ross, A. D., Siebeneck, L. K., Wu, H., Kopczynski, S., Nepal, S., & Sauceda, M. (2024) · Sustainability · doi:10.3390/su162411306 · Cited by 7
“Misinformation refers to false or inaccurate information created without the intention of causing harm; however, when people believe it to be true, it can mislead them and cause harm to individuals or society as a whole [55–58].”
Donner, S. (2025) · Journal of Documentation · doi:10.1108/jd-11-2024-0271 · Cited by 7
Tallerås, K., Colbjørnsen, T., & Øfsti, M. (2019) · Norsk medietidsskrift · doi:10.18261/issn.0805-9535-2019-01-02 · Cited by 6
An Information‐based Solution for the Puzzle of Testimony and Trust
Taddeo, M. (2010) · Social Epistemology · doi:10.1080/02691728.2010.521863 · Cited by 6
“…nature of information is referred to Bar-Hillel and Carnap (1953), Devlin (1991), and Colburn (2000) for the arguments against the veridical nature of information, and to Dretske (1981), Grice (1989), and Floridi (2004, 2005) for the arguments in favour of the veridical nature of information.”
BackgroundDinneen, J. D., & Brauner, C. (2018) · Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · doi:10.29173/cais1011 · Cited by 6
“…is abstract is consistent with some existing definitions of information, including Marcia Bates’s (2006) definition of information as “the pattern of organization of energy or matter”, Luciano Floridi’s semantic conception of information as true, well-formed, meaningful data (Floridi, 2005).”
ResultShannon versus semantic information processing in the brain
Majumdar, K. (2018) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1284 · Cited by 6
Did you just say what I think you said? Talking about genes, identity and information
Henschke, A. (2010) · Identity in the Information Society · doi:10.1007/s12394-010-0071-x · Cited by 7
“Gregory Bateson’s slogan, that information “consists of differences that make a difference” (Bateson 1979) tracks 8 As truth is a philosophically messy area, I am going to assume that Floridi’s argument for the truth condition holds (Floridi 2005).”
BackgroundA Hermeneutic Approach to the Notion of Information in IS
Wang, S. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85565-1_43 · Cited by 6
Mak, B., & Renear, A. H. (2023) · Isis · doi:10.1086/727568 · Cited by 5
Offline and online data: on upgrading functional information to knowledge
Primiero, G. (2012) · Philosophical Studies · doi:10.1007/s11098-012-9860-4 · Cited by 5
“(Floridi 2005) has replied to this question by maintaining that semantic and alethically neutral data provides only necessary but insufficient conditions for information: a pile of syntactical data which proves to be false or meaningless, cannot beaccountedforinformationand,inthebestcase,reducesto…”
BackgroundDigital Preservation through Digital Sustainability
Stuermer, M., & Abu-Tayeh, G. (2017) · Bern Open Repository and Information System (University of Bern) · doi:10.7892/boris.98845 · Cited by 5
From Thermodynamic Entropy to Knowledge Entropy
Brătianu, C. (2020) · Proceedings of the ... International Conference on Business Excellence · doi:10.2478/picbe-2020-0055 · Cited by 5
“Recently, Floridi (2005, 2012, 2013) focused on the concepts of information and information entropy and showed that researchers should be aware of the limitations introduced by the Bar-Hillel and Carnap assumptions, and the need to understand very well the context of any application: “Polysemantic…”
BackgroundA Computational Interpretation of Conceptivism
Ferguson, T. M. (2017) · Trends in logic · doi:10.1007/978-3-319-70821-8_4 · Cited by 5
Empirical modeling and information semantics
Dodig-Crnković, G. (2007) · Mind & Society · doi:10.1007/s11299-007-0035-5 · Cited by 5
“Or, as Floridi (2005) formulates it, ‘‘Information is such a powerful and elusive concept that it can be associated with several explanations, depending on the requirements and intentions.’’”
BackgroundSynthetic versus analytic approaches to protein and DNA structure determination
Bolinska, A. (2018) · Biology & Philosophy · doi:10.1007/s10539-018-9636-0 · Cited by 5
Challenges of using auto-correction tools for language learning
Rüdian, S., Dittmeyer, M., & Niels Pinkwart, C. (2022) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3506860.3506867 · Cited by 12
“Semantic analysis is usually used to determine whether the context (e.g., a sentence) is true based on previous information [31].”
BackgroundNanyanzi, A., Barker, K., Radhakrishnan, S., et al. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.112021 · Cited by 4
Complex-Information Ethics Theory
Solis, K. (2022) · Journal of Big History · doi:10.22339/jbh.v5i1.5150 · Cited by 4
Yu, L., & Zhang, Y. (2023) · Journal of Documentation · doi:10.1108/jd-07-2023-0133 · Cited by 5
Does the no miracles argument apply to AI?
Rowbottom, D. P., Peden, W., & Curtis-Trudel, A. (2024) · Synthese · doi:10.1007/s11229-024-04524-z · Cited by 4
Research Dimensions in Information Seeking of Music: A Plea for the Socio-technical Perspective
Lugović, S. (2014) · Communications in computer and information science · doi:10.1007/978-3-319-14136-7_75 · Cited by 5
“generation processes [13], influencing system performance by imposing goals which create benefit for these agents, not for society.”
BackgroundStrongly Semantic Information as Information About the Truth
Cevolani, G. (2014) · Trends in logic · doi:10.1007/978-3-319-06080-4_5 · Cited by 4
Nafría, J. M. D. (2011) · IGI Global eBooks · doi:10.4018/978-1-61350-201-3.ch003 · Cited by 4
On Falsifiable Statistical Hypotheses
Genin, K. (2022) · Philosophies · doi:10.3390/philosophies7020040 · Cited by 5
Decoupling Source and Semantic Encoding: An Implementation Study
Feng, Y., Jin, X., Liang, C., Yu, G., Hu, L., & Yuan, T. (2023) · Electronics · doi:10.3390/electronics12132755 · Cited by 5
Documentation As Meta-Level Activity
Donner, S. (2023) · Proceedings from the Document Academy · doi:10.35492/docam/10/2/11 · Cited by 4
Orientações contemporâneas da Ciência da Informação
de Gómez, M. N. G. (2022) · Museologia & Interdisciplinaridade · doi:10.26512/museologia.v11i22.43380 · Cited by 5
Structured Reflection In Information Systems Teaching and Research
Gregory, M. A., & Descubes, I. (2011) · Journal of the Association for Information Systems · Cited by 4
Information Content Inclusion Relation and its Use in Database Queries
Feng, J., & Salt, D. (2010) · Journal of Software Engineering and Applications · doi:10.4236/jsea.2010.33031 · Cited by 4
“Another view on the topic of the relationship between information and data is that if it is truthful, meaningful data is semantic information [12].”
BackgroundInformação e inclusão social: perspectivas possíveis
Medeiros, F. G. G., & Presser, N. H. (2020) · CIÊNCIA DA INFORMAÇÃO EM REVISTA · doi:10.28998/cirev.2020v7n1b · Cited by 4
Not All Structure and Dynamics Are Equal
Mindt, G. (2021) · Entropy · doi:10.3390/e23091226 · Cited by 6
Luciano Floridi's Metaphysical Theory of Information Ethics
Spence, E. H. (2010) · International Journal of Technology and Human Interaction · doi:10.4018/jthi.2010091701 · Cited by 5
Information is intrinsically semantic but alethically neutral
Long, B. R. (2014) · Synthese · doi:10.1007/s11229-014-0457-7 · Cited by 4
“Floridi’s view and that of Dretske is that information has an alethic value because it is only ever true and cannot be false (Floridi 2005, pp. 25, 30).”
BackgroundMaking Sense of Normative Functions and Information in Neurobiological Systems
Kraemer, D. M. (2012) · DukeSpace (Duke University) · Cited by 4
Introduction to solving task-level programming problems in logic programming language
Foit, K. (2014) · Journal of Achievements of Materials and Manufacturing Engineering · Cited by 3
Computation as Information Processing
Fresco, N. (2013) · Studies in applied philosophy, epistemology and rational ethics · doi:10.1007/978-3-642-41375-9_6 · Cited by 3
I'm Sorry to Say, But Your Understanding of Image Processing Fundamentals Is Absolutely Wrong
Diamant, E. (2008) · InTech eBooks · doi:10.5772/6042 · Cited by 3
“What follows from this, is that nonrandom data structures could be described in a concise compressed form, which Chaitin calls “Algorithmic Information” (Chaitin, 1977), Floridi – “Meaningful data” (Floridi, 2005), Vitanyi – “Meaningful Information” (Vitanyi, 2006). That means that each message can be seen as a compos…”
BackgroundInfluentialIntuition, Computation, and Information
Herold, K. R. (2013) · Minds and Machines · doi:10.1007/s11023-013-9324-4 · Cited by 3
“In describing his semantic theory of information, Floridi (2005) requires data be well-formed and meaningful in order to comprise information.”
Two paradoxes of semantic information
Ferguson, T. M. (2015) · Synthese · doi:10.1007/s11229-015-0717-1 · Cited by 3
“Beyond themere resolution of the BCP, Floridi has outlined numerous arguments in favor of the veridicality of semantic information in papers such as Floridi (2005) or Floridi (2007).”
Automated Interpretation of Key Performance Indicators by Using Rules
Tomić, B. (2009) · IGI Global eBooks · doi:10.4018/978-1-60566-402-6.ch026 · Cited by 3
“Most scientists agree that data becomes information when meaning is added to it (Floridi, 2005, pp. 353).”
BackgroundConsidering a non-document: concepts, components, and contexts
Kosciejew, M. R. H. (2019) · Journal of Documentation · doi:10.1108/jd-07-2018-0118 · Cited by 3
Evidence, computation and AI: why evidence is not just in the head
Rowbottom, D. P., Curtis-Trudel, A., & Peden, W. (2023) · Asian Journal of Philosophy · doi:10.1007/s44204-023-00061-7 · Cited by 5
“…speak of “truthful data” rather than “true data” because the data in question may not be linguistic (a map, for example, is truthful rather than true)… (Floridi, 2005, p. 366) This passage entails that ‘representing or conveying true contents about the referred situation’ is possible via…”
BackgroundMethodResultInfluentialHow Physical Information Underlies Causation and the Emergence of Systems at all Biological Levels
Farnsworth, K. D. (2025) · Acta Biotheoretica · doi:10.1007/s10441-025-09495-3 · Cited by 5
Allo, P. (2010) · Knowledge, technology & policy/Knowledge in society/Knowledge, technology, & policy · doi:10.1007/s12130-010-9098-4 · Cited by 3
The Information Liar Paradox: A Problem for Floridi’s RSDI Definition
Lundgren, B. (2014) · Philosophy & Technology · doi:10.1007/s13347-014-0155-x · Cited by 3
“(Floridi 2005:353). Philos. Technol. (2015) 28:323–327 DOI 10.”
Against “soft” statistical information
Kraemer, D. M. (2013) · Philosophical Psychology · doi:10.1080/09515089.2013.785127 · Cited by 3
“The veridicality thesis is endorsed by nearly everyone who has written about natural information in the philosophical literature (e.g., Cohen & Meskin, 2006; Dretske, 1981; Floridi, 2005; Grice, 1957) and I will discuss the motivation for it in the next section.”
BackgroundA New Look at Schema Instance Recoverability with the Notion of 'Information Carrying'
Xu, K., & Feng, J. (2009) · International Conference on Research Challenges in Computer Science · doi:10.1109/icrccs.2009.13 · Cited by 3
“This idea is established upon Dretske’s semantic theory of information [4], Devlin’s notion of ‘infon’ and situation semantics [3] and Floridi’s information philosophy [5].”
MethodThe Epistemology and Ethics of Media Markets in the Age of Information
Spence, E. H. (2009) · The International Review of Information Ethics · doi:10.29173/irie88 · Cited by 3
Silva, J. L. C., & Gomes, H. F. (2015) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 3
Information Waste, the Environment and Human Action: Concepts and Research
Wijnhoven, F., Dietz, P., & Amrit, C. (2012) · IFIP advances in information and communication technology · doi:10.1007/978-3-642-33332-3_13 · Cited by 3
“The Concept of Information Waste Information is meaningful data or meaningful representations [5], [32].”
Models of Information Behavior
(2016) · Studies in information · doi:10.1108/s2055-53772016007 · Cited by 3
Addressing Uncertainties in Complex Manufacturing Environments: A Multidisciplinary Approach
Dhiman, H., Plewe, D. A., & Röcker, C. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-94196-7_10 · Cited by 3
“Any given message will be true in a context, at a LoA for a particular purpose [16].”
BackgroundPerception and Testimony as Data Providers
Floridi, L. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780198833635.003.0004 · Cited by 3
Self-citationThe analysis of uncertain knowledge based on meaning of information
Cang, P., & Wang, S. (2009) · Cited by 3
Epistemic representation in science and beyond
Bolinska, A. (2015) · TSpace (University of Toronto) · Cited by 3
Pieters, C. (2008) · University of Humanistic Studies OAI Repository · Cited by 3
Metadata
- Authors
- FLORIDI, L.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- FLORIDI, LUCIANO
- ORCID
- FLORIDI, LUCIANO
- Venue
- Philosophy and Phenomenological Research
- Publisher
- Wiley
- Published
- 2005-03
- Volume
- 70
- Issue
- 2
- Pages
- 351-370
- ISSN
- 0031-8205 (ISSN-L)
- 1933-1592
- OpenAlex
- W2059974307
- Semantic Scholar
- 2af4a76b5eac94619fac8f2a44d008de8f94d58a
- Cited by
- 375
- References
- 40
- Citations by year
- 2026: 10 · 2025: 17 · 2024: 14 · 2023: 21 · 2022: 17 · 2021: 15 · 2020: 11 · 2019: 30 · 2018: 18 · 2017: 19 · 2016: 23 · 2015: 27 · 2014: 20 · 2013: 20 · 2012: 17
- FWCI
- 97.33
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Philosophy and Phenomenological Research (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- University of Hertfordshire Research Archive (University of Hertfordshire) (submittedVersion)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Social Sciences › Arts and Humanities › Philosophy › Philosophy and Theoretical Science
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Scientific Research and Philosophical Inquiry
- Keywords
- semantic information, misinformation, truth conditions, definition of information
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-28, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
