Glossary
The following terms are used consistently across the related working papers, case studies, and reference implementations. Wherever an established standard provides a suitable concept, the terminology follows or builds upon that standard; framework-specific terms are introduced where the required distinction is not adequately captured by existing terminology. The glossary is not intended to replace definitions provided by ISO, PROV, RiC, CIDOC CRM, ODRL, or other external standards. Where those standards or models are used, their own formal definitions continue to apply.
General Vocabulary
Artificial Intelligence
AI agent
ISO/IEC 22989 defines an automated entity that senses and responds to its environment and takes actions to achieve its goals (ISO/IEC 2022).
Inference
ISO/IEC 22989 defines inference generally as reasoning by which conclusions are derived from known premises, where premises in AI may include facts, rules, models, features, or raw data (ISO/IEC 2022).
Information & Documentation
Identifier
In a register, an identifier is a linguistically independent sequence of characters capable of uniquely and permanently identifying that with which it is associated (ISO 2026). More generally, it is a “value by which something is identified.” (ISO/IEC 2024)
Knowledge source
source of information from which a knowledge base has been created for a specific kind of problem [ISO/IEC 2382-28:1995]. (ISO 2023)
Taxonomy
scheme of categories and subcategories that can be used to sort and otherwise organize itemized knowledge or information [ISO 25964-2:2013, definition 3.83 modified] (ISO 2013)
Work
distinct, abstract creation of the mind whose existence is revealed through one or more expressions (e.g. a performance) or manifestations (e.g. an object) (ISO 2022)
Expression
intellectual or artistic realisation of one and only one work
Note: may take the form of a notation
Manifestation
physical embodiment of an expression (ISO 2017)
Computer & Data Science
Tuple
An ordered collection of values, fields, or elements. [SOURCE: ISO/IEC 39075:2024; ISO/IEC 2382:2015, 17.04.05] (ISO/IEC 2024) In the present framework, tuples are used as relational representations whose positions have explicitly defined semantic roles (e.g., the atomic assertion \((s,p,v)\) as a three-field tuple).
Knowledge representation
The process or result of encoding and storing knowledge in a knowledge base [ISO/IEC 2382-28:1995; ISO (2023)].
Knowledge graph
A knowledge representation that uses a graph-structured data model to represent and operate on data (ISO 2023).
ReactAI Research Vocabulary
Semantic Knowledge Production
Assertion
A semantic statement concerning a subject, predicate, and value. In the present framework, the elementary assertion is represented as the ordered tuple \((s,p,v)\). Assertions may be candidates, reviewed assertions, or members of a stabilised semantic state. Where represented in RDF, this structure corresponds to the subject-predicate-object structure of an RDF triple.
Atomic assertion
An assertion treated as a single independently identifiable and reviewable semantic unit. In the present framework, an atomic assertion is represented as
\[(s,p,v),\]
where \(s\) is the subject, \(p\) the predicate, and \(v\) the value. The term atomic indicates that the assertion is not decomposed into simpler assertions within the operation under consideration. In RDF, the corresponding elementary structure is a triple; in formal logic, the related concept is an atomic formula.
Candidate assertion
An assertion made available for consideration but not thereby assumed to be corroborated or stabilised.
Example: depicted garment — instance of — Livonian folk dress may enter review as a candidate.
Candidate generation
The operation through which one or more semantic assertions become explicit candidates for subsequent review or finalisation. Candidate generation is an elementary operation of the Review Algebra; observation and inference are different mechanisms through which candidate generation may occur.
Knowledge-producing activity
A provenance-bearing human or computational activity through which semantic assertions are generated, examined, interpreted, reconciled, inferred, reviewed, or otherwise transformed. Different knowledge-producing activities may use different evidence, methods, agents, competences, rules, and applicable policies.
Semantic state
The set of semantic assertions available as represented knowledge at a particular stage of semantic production. A stabilised semantic state may provide input to further observation, interpretation, reconciliation, inference, candidate generation, review, or finalisation.
Semantic stabilisation
The process through which incomplete, ambiguous, heterogeneous, contested, or partially conflicting semantic assertions become sufficiently stable for a specified purpose while preserving relevant uncertainty, provenance, competing interpretations, and opportunities for subsequent revision. Stabilisation is purpose-relative and does not imply permanent truth or universal agreement.
Semantic knowledge production
The broader process through which human and computational agents produce semantic knowledge by observing evidence, interpreting it under relevant competences, identifying and reconciling entities, applying explicit rules, reviewing candidate assertions, and progressively stabilising knowledge for particular purposes. The Review Algebra formalises a deliberately narrower part of this process.
Evidence & Interpretation
Evidence
entity or represented assertion made available to, examined by, or used by a knowledge-producing activity in relation to one or more semantic assertions. [SOURCE: Adapted from W3C PROV-DM (prov:Entity, prov:used); ISO 5127:2017] (Moreau and Missier 2013; ISO 2017) Evidence denotes an operational role in a particular activity; it does not imply truth, correctness, sufficiency, or a particular ontological class. Example: pict003.jpg is evidence used to establish what the depicted person is wearing.
Evidentiary frame
The relationship under which evidence is examined in a particular knowledge-producing activity, specifying what kind of semantic object the activity concerns.
Example: pict003.jpg is observed as evidence concerning a depicted garment.
Observation
Observation may be performed by human or computational agents. Computational performance of an activity does not by itself imply autonomy: ISO/IEC 22989 distinguishes automated operation under specified conditions from autonomy, in which a system can modify its intended domain of use or goal without external intervention, control, or oversight (ISO/IEC 2022).
Example: fscontext observes that pict003.jpg has MIME type image/jpeg.
Observe as
A practical expression for specifying the evidentiary frame under which an observation activity examines evidence: for example, observing a JPEG as a digital manifestation, as a photograph, or as evidence concerning a depicted garment or activity. It constrains what subjects and predicates are meaningful within the activity without becoming part of the elementary domain assertion.
Identification
A knowledge-producing activity that establishes or proposes which particular entity participates in an observation, representation, record, expression, or other semantic relationship. This builds on the standardised meaning of identify as referring without ambiguity and of an identifier as a value by which something is identified [@iso_39075_2024].
Example: The depicted person in pict003.jpg is identified as Hilda Grīva.
Interpretation
A knowledge-producing activity through which an agent applies linguistic, disciplinary, historical, legal, cultural, or other specialised competence to evidence or represented knowledge.
Example: A textile researcher interprets the depicted garment as Livonian folk dress.
Reconciliation
A knowledge-producing activity that proposes or establishes relationships between locally represented entities or expressions and entities or identifiers in external knowledge representations, authority systems, registers, or other namespaces. A namespace is understood as a classification scheme that permits a given name to identify multiple objects distinguished by context (ISO/IEC 2024).
Intermediate Representations
Intermediate semantic representation
semantically explicit computational representation constructed for a particular stage or operation of semantic knowledge production. Preserves the identities and semantic roles required to reconstruct the underlying assertions and their provenance. Intermediate describes its role in computation, not data longevity.
Relational projection
An operational construct or view that maps underlying semantic assertions into a specified tabular or relational structure for computational processing. [SOURCE: Adapted from ISO/IEC 2382:2015, 17.04.11; ISO/IEC 39075:2024] (ISO 2023; ISO/IEC 2024)
In the present framework, a relational projection selects, joins, or reshapes assertions for a review, analytical, or other knowledge-producing operation without altering the semantics or identity of the underlying atomic assertions.
Elementary projection
A relational projection of atomic assertions \((s,p,v)\). In an elementary long projection, subject, predicate, and value remain explicit fields and each row represents one atomic assertion. In an elementary wide projection, assertions sharing a subject are reshaped so that predicates become columns where cardinalities permit an unambiguous pivot.
dual projection
relational projection formed by joining two atomic assertions on a shared entity, represented in relational algebra as \((e,r,s)\bowtie_s(s,p,v) \mapsto (e,r,s,p,v)\). The joined tuple does not constitute a new compound assertion; both underlying assertions retain independent identities, provenance, and reviewability.
Wide projection
A relational projection in which assertions sharing a subject are reshaped so that selected predicates become columns where cardinalities permit an unambiguous pivot. In bounded federation, a wide projection may expose a rectangular subject–predicate space containing intersections that do not correspond to candidate assertions; these can be represented explicitly as Not applicable.
Semantic mediation representation
An intermediate semantic representation used to mediate between independently represented semantic systems. In the present model, the atomic tuple \((s,p,v)\) provides a thin common representation in which graph-to-graph candidate correspondences can be made explicit and reviewed without replacing the persistent representation of either participating graph.
Human-Centred Review
Agent
A human or computational participant capable of performing or participating in a knowledge-producing activity. In the specific case of an AI agent, ISO/IEC 22989 defines an automated entity that senses and responds to its environment and takes actions to achieve its goals (ISO/IEC 2022). In semantic knowledge production, what an agent can responsibly establish additionally depends on the competence, method, applicable policies, and other conditions relevant to the particular activity.
Competence
The capacity of an agent to responsibly perform a particular knowledge-producing activity or establish a particular kind of assertion. Competence is activity-specific rather than a general property of an agent.
Example: A textile researcher and a local speaker may competently describe the same coat in different conceptual vocabularies.
Review
The Review Algebra operation through which an existing candidate assertion, or one or more of its components, is examined and a semantic value together with an explicit review status is returned.
Example: A domain expert corroborates the candidate classification Livonian folk dress.
Review status
An explicit representation of what happened to a candidate during review, distinct from the semantic value returned by that review. Core statuses include corroborated, falsified, and deferred. The generation of an alternative semantic value is not itself a review status: an alternative assertion may be generated during the same activity while remaining distinct from the disposition recorded for the candidate under review.
Deferred
A review status indicating that a candidate has been examined but cannot presently be corroborated or falsified. Deferral records the result of a completed review activity rather than an absent value.
Finalisation
The Review Algebra operation that applies an explicit policy to review results or other eligible candidates and determines which semantic assertions enter a subsequent stabilised semantic state. Finalisation is distinct from review: epistemic judgement and operational authority need not belong to the same agent or process.
Review Algebra
The formal and computational framework developed in the companion paper for representing candidate generation, review, and finalisation as provenance-bearing transformations between semantic states. The Review Algebra deliberately does not prescribe the epistemology, evidence, competence, or domain models of the knowledge-producing activities that supply its candidates.
Applicability & Epistemic State
Applicability
The conditions under which a question, activity, rule, method, or inference is relevant or warranted. Applicability may depend on previously stabilised assertions, entity classes, relationships, temporal or geographical conditions, scope, applicable policies, or other explicitly represented knowledge.
Conditions of applicability
The explicit conditions that must be satisfied before a rule, inference, question, method, or other knowledge-producing operation is applicable. Scope may contribute to these conditions but is not synonymous with them.
Scope
An explicit qualification of the semantic or applicability context within which an assertion is intended to hold. Scope may be retained where interpretation or validity depends on context and may contribute to determining whether a rule is applicable. Scope is distinct from the evidentiary frame of an observation activity and from provenance more generally.
Unknown
A state in which relevant knowledge may exist or a property may have a determinate value, but that knowledge has not yet been established. Unknown knowledge may therefore justify further observation, investigation, reconciliation, interpretation, or review.
Indeterminate
A state in which a requested property cannot presently have a determinate value because the event or condition that would determine it has not occurred. Indeterminacy is distinct from unknown knowledge. A living person, for example, does not presently have a death year that remains to be discovered.
Unresolved dependency
A represented requirement for another assertion or condition that must be established before a candidate can be generated, an inference can proceed, or an operational decision can be made.
Example: A publication decision remains blocked until the recording date is established.
Inference
Inference
ISO/IEC 22989 defines inference generally as reasoning by which conclusions are derived from known premises, where premises in AI may include facts, rules, models, features, or raw data (ISO/IEC 2022).
In the Review Algebra, inference is formally defined as the rule-governed generation of candidate assertions \(C_k^* = \bigcup_{r \in \mathcal{G}} g_r(S_k, R, \sigma)\) operating strictly over the stabilised semantic state \(S_k\). Intermediate candidates generated within cycle \(k\) are explicitly barred from serving as premises for further inference during the same cycle. Example: Stabilised authorship and life dates may satisfy the conditions of a rule that generates a candidate copyright conclusion.
Provenance & Governance
Domain knowledge
Semantic knowledge about the entities, relationships, events, properties, classifications, or other subject matter of the domain under investigation. Domain knowledge is knowledge concerning the subject matter of an activity, distinguished analytically from evidence, provenance knowledge, and normative consequences.
Example: Hilda Grīva wears Livonian folk dress.
Provenance
A record that describes the entities, activities, and agents involved in producing, influencing, or delivering data or another thing, including relations of use, generation, derivation, association, attribution, and responsibility. [SOURCE: Adapted from W3C PROV-DM and PROV-O] (Moreau and Missier 2013; Lebo et al. 2013) In semantic knowledge production, provenance records the lineage and circumstances through which assertions or semantic states were produced, reviewed, inferred, or finalised. Evidence, agents, and activities are not themselves synonymous with provenance; rather, their participation and relationships are represented in provenance information. Domain-specific qualifications such as methods, rules, competences, and evidentiary roles may extend this account where required.
Provenance knowledge
Knowledge describing how domain assertions and semantic states were generated, reviewed, inferred, finalised, or otherwise transformed. Provenance knowledge is represented separately from domain knowledge even where the two are closely connected.
Example: What Hilda Grīva wears was observed by an expert reviewer examining pict003.jpg.
Permission
The ability or authorisation to exercise an action over a resource. In ODRL, a Permission is the ability to exercise an Action over an Asset (Iannella and Villata 2018). Permission is distinct from epistemic warrant: an assertion may be well supported while its use, disclosure, transformation, or other action remains restricted.
Bounded Federation
Bounded federation
Purpose-directed and reviewable semantic exchange between independently governed knowledge graphs within an explicitly delimited federation boundary. Bounded federation establishes the semantic warrant for specified assertion-level exchanges without asserting global equivalence between the participating ontologies or knowledge graphs. Its distinctive boundary is therefore semantic and operational: other federation architectures may independently restrict technical reachability, query relevance, access, or participation.
Federation boundary
The explicitly delimited semantic domain within which a federation claims sufficient competence for specified exchanges. A federation boundary may restrict participating entities, predicates, ontological patterns, candidate assertions, directions of exchange, or other conditions relevant to the federation. Assertions outside the boundary are not thereby considered false or invalid; no federation claim is made about them.
Bounded projection
A relational projection restricted to the subjects, predicates, assertions, or other semantic elements selected for a federation boundary. A bounded projection exposes the candidate space required for a specified federation operation rather than projecting the source knowledge graph as a whole. The projection changes how candidate assertions are arranged and presented for review without changing their semantic identity or candidate status.
Pragmatic purpose
The declared purpose for which a bounded federation is established. The pragmatic purpose motivates competency questions against which the adequacy of the federation can be assessed. Pragmatic does not mean approximately correct or merely convenient: correspondence must be adequate for the declared purpose under explicit competence boundaries.
Competency question
A question used to state what an ontology, ontological pattern, or bounded federation is intended to be capable of representing or answering. In bounded federation, competency questions operationalise the pragmatic purpose of an exchange and contribute to delimiting its federation boundary (Blomqvist et al. 2016).
Ontological pattern
A reusable semantic structure addressing a recurring modelling problem. In bounded federation, an ontological pattern identifies the portion of semantic structure required to support the declared competency questions without requiring complete alignment of the participating ontologies (Blomqvist et al. 2016; Berardinis et al. 2023).
Inferential competence
The bounded competence of a federation to support specified interpretations or inferences involving federated assertions. Warrant to exchange an assertion does not by itself establish warrant for every inference that the destination graph can derive from that assertion.
Federation outcome
The federation-specific result associated with a reviewed candidate correspondence or exposed subject–predicate intersection. The present demonstrator distinguishes Federate, Redefine, Skip, and Not applicable. These outcomes describe different relationships to the proposed federation operation and do not constitute either a truth scale or a replacement for the underlying review state.
Federate
A federation outcome indicating that a candidate assertion or correspondence is sufficiently established for the specified exchange within the declared federation boundary. Federation does not imply global equivalence between the participating graphs, entities, predicates, or ontologies.
Redefine
A federation outcome indicating that sufficient semantic contact exists to identify a related commitment, but the proposed correspondence does not adequately preserve the meaning required by the destination graph. The appropriate local formulation is retained or established rather than treating the source and destination representations as semantically interchangeable.
Skip
A federation outcome indicating that a candidate assertion exists but its exchange is not warranted in the current federation operation. Skip therefore differs from Not applicable, where no candidate assertion exists at the exposed subject–predicate intersection.
Not applicable
A federation outcome indicating that an exposed subject–predicate intersection does not constitute a candidate assertion within the federation boundary. Not applicable is distinct from an unknown or missing value, rejection, deferral, and Skip: no atomic candidate assertion exists at that intersection.
Warranted exchange
A semantic exchange admitted through review and finalisation as adequate for the declared federation purpose and competence boundary. Warrant for an exchange is bounded and does not by itself imply global semantic equivalence, unrestricted inferential warrant, destination-graph admission, or normative authority.
European Interoperability Framework (EIF)
The European Interoperability Framework (EIF) is a set of recommendations and guidelines that aims to facilitate communication and collaboration between public administrations, businesses, and citizens within the European Union and across national borders (Commission and Digital Services 2017).
Application-Domain Vocabulary
Cultural & Creative Assets
asset identifier
persistent identifier used for musical works, sound recordings, editions, audiovisual items, or other cultural objects. CITF requires asset identifiers to be resolvable and interoperable across systems. (citf_2025?)
Music
audio recording
fixation of sounds (ISO 2019)
creator
in the context of this policy paper, we use the broad term for the arranger, author, composer, lyricist; for individual definitions see ISWC standard (ISO 2022)
DSP or digital streaming platform
Digital service providers (DSPs), or Digital Streaming Platforms are companies or organisations that provide access to services online. DSPs can provide access to music downloads, like Apple’s iTunes Store, or access to streaming music like Spotify, or even provide satellite-delivered content such as SiriusXM in the USA.
musical work
composed of a combination of sounds, with or without accompanying text (ISO 2022)
movement
A principal division of a musical work. (ISO 2022)
original title
A title given to the work by its creator(s) shown in its original language. (ISO 2022)
formal title
A standardized title in which the elements are arranged in a pre-determined order, such as titles created for classical works. (ISO 2022)
original version
The first established form of a work. (ISO 2022)
track
single recording on a sound carrier (ISO 2017)
music video recording
fixation of sounds synchronized with pictures or moving pictures where (a) the fixed sounds are wholly or substantially a musical performance or (b) the recording is intended for viewing in association with a recording of a musical performance. This definition includes music videos and concert recordings, together with music-related interviews and documentaries, but does not extend to genera! audiovisual material, even if it includes music.(ISO 2019)
performer
The performer of a musical work; in case of a sound recording, the performer whose performance is fixed in the recording. They may be entitled to neighbouring rights in sound recordings. In some contexts, the performer is part of the broadly defined creator group.
producer
The person or legal entity that produces the recorded fixation of the sound recording. They are entitled to neighbouring or sound recording copyrights. In some contexts, the producer is part of the broadly defined creator group.
rights management (organisations)
the function of managing the rights on behalf of rights owners. It can be companies whose sole purpose is to ensure that content that has been licensed has delivered royalties that are identified and accounted for. The role can be taken by collective management organisations or by private companies on behalf of songwriters, composers, performers, music publishers, or record labels.
ISMN
The International standard music number (ISMN) was developed by, and for, the music publishing sector as a separate system to complement the International standard book number (ISBN). The existence of the ISMN as a separate identifier system makes it possible to identify printed and notated music as a distinct category of publication within the global supply chain and to develop trade directories and similar services for the specialized market for music publications. (→ asset identifier)