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Open research questions in Semantic Web and Ontologies

109 unresolved questions extracted from the limitations and future-work sections of 887 Semantic Web and Ontologies papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Ontologies have emerged as powerful tools for establishing interoperable and reusable data structures from inconsistent data structures.

    An integrated data pipeline for semantic data representation of the flame spray pyrolysis process · 2025 · DOI

  • Despite advancements in semantic data representation for specific applications, integrating application ontologies with primary data repositories, such as electronic lab notebooks (ELNs), to feed world data remains an open task.

    An integrated data pipeline for semantic data representation of the flame spray pyrolysis process · 2025 · DOI

  • Prior work has often proceeded categorically, stabilizing general kinds of entities. There is a need for a constructive approach to ontology, deriving structures from basic elements and rules of composition.

    Things in States Through Time: A Constructive Ontological Framework for Predicate Logic and Derived Semantic Structure · 2026 · DOI

  • TST is proposed as a constructive ontological framework and predicate grammar substrate, not as a completed formal logic, finalized implementation standard, or exhaustive metaphysical system. Its purpose in this paper is to establish the proposition and value of a minimally categorical, maximally constructive approach to ontology. Several areas require future development. 14.1 Admissibility Algebra TST depends on the idea that not all State transitions preserve identity continuity. A Thing persists only when its changing States remain admissibly connected. This is expressed informally through: 𝐶(𝑇, 𝑆1, 𝑆2, 𝑡1, 𝑡2) However, the framework still requires a more formal admissibility algebra: a system of rules for determining when a transition is identity-preserving, identity-breaking, or ambiguous. Such an algebra would need to account for: • bounded distinguishability, • structural continuity, • functional continuity, • causal continuity, • semantic continuity, • spatiotemporal continuity, • institutional continuity, • domain-specific admissibility rules. This is one of the most important future tasks because the Continuity Identity Principle depends on it. 14.2 Continuity Metrics Relatedly, TST requires formal continuity metrics. A bridge may be repaired and remain the same bridge. A road may be resurfaced and remain the same road. A legal organization may change officers and remain the same organization. But each case relies on different continuity criteria. Future work should develop ways to measure or evaluate continuity across domains, including: • physical continuity, • legal continuity, • semantic continuity, • operational continuity, • • representational continuity, identity continuity. These metrics may vary by domain, but TST needs a general framework for representing them. 14.3 Formal Semantics TST presently defines a constructive predicate grammar but does not yet provide a complete formal semantics. Future work should formalize TST using one or more suitable systems, such as: • Common Logic, • • temporal first-order logic, typed predicate logic, • modal logic for potentiality, • causal logic, • description logic extensions, • or hybrid logic systems. The goal would be to specify the truth conditions, inference rules, typing constraints, and admissibility requirements for TST predicates and operators. 14.4 OWL / RDF Representation TST should also be represented in semantic web formats. An OWL/RDF profile would need to model: • Thing, • State, • StateType, • TimeIndex, • RelationalState, • Transition, • Interpretation, • PotentialState, • EpistemicState, • CausalTrace, • Representation, • EmbeddingState. However, TST should not be prematurely reduced to OWL. OWL is a representation layer, not the ontology itself.

    Things in States Through Time: A Constructive Ontological Framework for Predicate Logic and Derived Semantic Structure · 2026 · DOI

  • The complexity of unstructured information. The need for automated methods to learn ontology-based information extraction rules. The evaluation of the performance of different metaheuristics.

    Metaheuristics for Ontology-Based Information Extraction Rule Learning · 2026 · DOI

  • The process of adding text information to existing ontologies by hand is time-consuming. There is a need for automated methods to learn ontology-based information extraction rules.

    Metaheuristics for Ontology-Based Information Extraction Rule Learning · 2026 · DOI

  • The lack of labeled corpora for translating natural language into specialized query languages. The limitation of extracting value from industrial time-series databases to users with a high technical profile.

    LLMs for industrial databases: an agro-food production plant use case · 2026 · DOI

  • Future work should investigate alternative embedding strategies or heuristics that maintain semantic grounding while reducing computational footprint. Future work should explore: (1) augmenting the knowledge graph with timezone metadata at level; (2) developing specialized temporal reasoning modules that infer UTC offsets from conversational context (e.

    LLMs for industrial databases: an agro-food production plant use case · 2026 · DOI

  • Semantic gaps between different standards and technologies hinder unified machine-level understanding. The integration of AAS, OPC UA, and KGs for semantic interoperability is a complex challenge. The development of more comprehensive frameworks for integrating AAS, OPC UA, and KGs is needed.

    Semantic Interoperability in Industry 4.0: A Systematic Mapping Study on Integrating Knowledge Graphs with AAS and OPC UA · 2026 · DOI

  • Large-scale industrial deployment remains limited. While technical feasibility has been established, industrial deployment and best practices have not yet matured. The dominance of validation research over evaluation research indicates a need for more evaluation studies.

    Semantic Interoperability in Industry 4.0: A Systematic Mapping Study on Integrating Knowledge Graphs with AAS and OPC UA · 2026 · DOI

  • The lack of a paradigmatic transformation of area studies in the digital age. The lack of construction of semantic infrastructure through high-quality data annotation. The lack of development of a dual-engine model integrating United Nations normative corpora and Open Source INTelligence data annotation.

    From “Textual Interpretation” to “Cognitive Infrastructure”: The Data-Driven Transformation and Paradigm Reconstruction in Country and Regional Studies for the Digital Age — With a Strategic Value Analysis of Multilingual Open Source INTelligence (OSINT) Data Annotation · 2026 · DOI

  • Human efforts to undertake transformations of data into knowledge are challenged by large data scales and complexities. There is a need for a conceptual framework for an intelligent biomedical platform.

    A Perspective on Software Intelligence for Autonomous Transformations in Biomedical Data and Knowledge · 2026 · DOI

  • Existing methods treat labeled and unlabeled data separately, missing interaction opportunities. Prior approaches overlook the critical insight that labeled and unlabeled data can mutually enhance each other.

    Relational Retrieval: Leveraging Known-Novel Interactions for Generalized Category Discovery · 2026 · DOI

  • The paper suggests replacing Jaccard text overlap with LLM-based semantic purpose classification to fix the methodological issue with Purpose Alignment Recall. The paper suggests further evaluating the effectiveness of Teleological Fabric in various domains. The paper suggests exploring the applications of Teleological Fabric in supporting expert decision-making.

    Teleological Fabric: A Successor Framework to SECI for the Age of Generative AI: Why Knowledge Management Needs Purpose-Aligned Substrate, Not More Repositories · 2026 · DOI

  • The gap in transferring the judgment of expert practitioners remains a stubborn problem in knowledge management. The gap is one of level, with existing systems organizing knowledge at the wrong level. The paper argues that this gap can be addressed by introducing a new framework that organizes domain knowledge as reusable judgment patterns.

    Teleological Fabric: A Successor Framework to SECI for the Age of Generative AI: Why Knowledge Management Needs Purpose-Aligned Substrate, Not More Repositories · 2026 · DOI

  • The manual creation of ontologies for high-tech industries is extremely time-consuming. The use of raw Large Language Models (LLM) creates problems of hallucinations and data heterogeneity.

    Overview of methods for automated creation of ontologies for scientific domains · 2026 · DOI

  • The exact ground energy of -3.080878 has not been reached or confirmed on hardware. The spectral gap of 0.333330 has not been directly measured. A deeper ansatz and error mitigation would be required to test the predicted ground state value.

    Ontologia · 2026 · DOI

  • Future research should focus on confirming the bilateral Hilbert space ground state prediction specifically. The experiment would need a deeper ansatz, zero-noise extrapolation or probabilistic error cancellation, and a discriminating control Hamiltonian run on the same hardware.

    Ontologia · 2026 · DOI

  • Limited planning time and pedagogical resources for high school English teachers. The need for diverse, thematically aligned text sets. The complexity of evaluating text sets based on pedagogical merit.

    T-TExTS (Teaching Text Expansion for Teacher Scaffolding): Enhancing Text Selection in High School Literature through Knowledge Graph-Based Recommendation · 2026 · DOI

  • The lack of diverse text sets can impact the quality of education. Prior work has not addressed the specific needs of high school English Literature text selection.

    T-TExTS (Teaching Text Expansion for Teacher Scaffolding): Enhancing Text Selection in High School Literature through Knowledge Graph-Based Recommendation · 2026 · DOI

  • existing logic-based extraction pipelines often require issuing a large number of extraction queries - the decoupling of extraction from reasoning in existing approaches - the lack of exploitation of logical knowledge during the extraction process

    Logic-Guided Data Extraction with Answer Set Programming and Large Language Models · 2026 · DOI

  • Future research directions include combining large language models with knowledge graphs and hybrid neuro-symbolic reasoning. Federated privacy-preserving personalization is a potential area of research.

    Ontology-Based Recommender Systems for Online Learning Platforms: A Review · 2026 · DOI

  • The semantic gap between statistical signal and pedagogical meaning is a challenge. Cold start is a limitation of classical recommender paradigms. Ontology construction cost is a challenge.

    Ontology-Based Recommender Systems for Online Learning Platforms: A Review · 2026 · DOI

  • The project suggests that future research can focus on evaluating the effectiveness of the AI toolkit, the Knowledge Graph, and the Reference Architecture. The project suggests that future research can focus on developing similar technical infrastructures for other applications.

    AI4Deliberation_D4.1 – AI toolkit, Architecture and Knowledge Graph – first version · 2026 · DOI

  • The project identifies a need for a technical infrastructure to support AI-assisted, multimodal, and gamified deliberations. The project identifies a need for a WP4 AI toolkit, a Deliberation Knowledge Graph, and a Reference Architecture.

    AI4Deliberation_D4.1 – AI toolkit, Architecture and Knowledge Graph – first version · 2026 · DOI

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109 open questions have been extracted from the limitations and future-work passages of 887 Semantic Web and Ontologies papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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