Polysemic Case Study Approach

• Polysemic case study approach is a multidimensional methodology that captures multiple layers of meaning and contextual complexity across diverse domains.
• It integrates techniques such as SKOS mapping and micro-ontologies to systematically address semantic ambiguity and resolve controlled vocabulary conflicts.
• The approach enables interdisciplinary research by combining deductive models, statistical analysis, and rich narrative data to support robust theory development.

A polysemic case paper approach is characterized by its explicit engagement with multiple layers of meaning, contextual complexity, and cross-domain integration—whether in knowledge organization, language modeling, educational analysis, or interdisciplinary research contexts. It draws on varied methodologies to address semantic ambiguity, methodological plurality, and the practical requirements of mapping, reasoning, or interpreting phenomena inherently rich in alternative perspectives. The approach is documented across domains such as SKOS-enabled terminology mapping (Mayr et al., 2010), controlled natural language semantics (Gruzitis et al., 2015), narrative analysis (Bornes-Varol et al., 2019), multimethod research design (Bennett et al., 2022), and design pattern discourse (Corneli et al., 2021).

1. Conceptual Foundations and Motivations

Polysemy refers to the coexistence of multiple, context-dependent meanings within a given term, construct, or modality. A polysemic case paper approach does not attempt to suppress this multiplicity but rather seeks to systematically annotate, model, or operationalize it. In case paper research, this translates into a prioritization of rich, “thick” narrative data and disciplined handling of ambiguities—aligning with the Flyvbjerg paradigm, which asserts that expert knowledge and scientific progress often depend on context-dependent, multifaceted case exemplars (Flyvbjerg, 2013).

In terminology mapping and knowledge organization, polysemy emerges when linking or merging distinct vocabularies or ontologies—necessitating methods that resolve or formalize sense differences, such as SKOS mapping for concept interoperability (Mayr et al., 2010). In computational linguistics, it becomes central in the word sense disambiguation (WSD) problem, especially within controlled natural language frameworks, motivating splitting of global ontologies into micro-ontologies and the explicit labeling of ambiguous terms with multi-word units (Gruzitis et al., 2015).

2. Structural and Methodological Features

A polysemic case paper approach is typified by multilayered annotation, iterative cross-validation, and the use of mapping or coding schemes designed to capture, rather than erase, contextual and semantic plurality.

• In knowledge containers such as the Aliento database, brief sapiential units are not stored in isolation but embedded within rich XML annotation structures: these encode literal, figurative, grammatical, and cultural senses, supported by graded and lemmatized tags to handle orthographic, phonetic, and morphological variability (Bornes-Varol et al., 2019).
• In SKOS thesauri mapping, concept-based vocabularies are published with URIs and mapping properties (e.g., skos:exactMatch, skos:closeMatch) to support bilateral crosswalks between systems. Polysemy is addressed through extensions for complex or “combination” mappings where single terms may map to composite concepts (Mayr et al., 2010).
• In computational semantics, micro-ontologies function as domain-specific, monosemous sense inventories. Their merging is formalized by consistency checks (e.g., via OWL DL reasoners) and explicit partitioning with multi-word units, yielding a set of disambiguated, context-sensitive labels that resolve polysemy at the lexical and procedural levels (Gruzitis et al., 2015).

Typical methodological steps include:

Domain	Polysemic Methodology	Annotation Strategy
Thesaurus Mapping	SKOS crosswalks & URI-linking	Concept-level mapping, SKOS-XL
CNL Semantics	Micro-ontologies + MWUs	Domain namespace labels
Sapiential Corpus	XML graded, language-specific tags	Lemmatization, figurative tags
Design Patterns	PLACARD (PAR+CLA+DPL) integrative protocol	Layered/collaborative review

3. Addressing Semantic Ambiguity and Polysemy

The resolution of ambiguity and handling of polysemy requires explicit procedures at both the annotation and reasoning levels.

• In controlled vocabularies, SKOS mapping properties (skos:exactMatch, skos:closeMatch) are used to explicitly relate concepts between different schemes, but must be extended to cover “use combination” relations when mappings are not one-to-one.
• Micro-ontology-based WSD relies on formal tests for logical unsatisfiability during merging; only unifiable senses are consolidated, others are separated and named distinctly. This procedure is formalized as:

$$X \equiv Y \iff (X \subseteq Y) \wedge (Y \subseteq X)$$

If adding subclass relations yields inconsistency, terms remain separated as, e.g., "A-Germany" vs. "B-Germany" (Gruzitis et al., 2015).

• In multi-language sapiential corpora, every unit is annotated with tags for grammatical variants, lemmatized forms, and translated senses. A similarity function is conceptualized as:

$$S(u, v) = \sum_{i=1}^{n} w_i \cdot \operatorname{sim}(\mathrm{entity}_i(u), \mathrm{entity}_i(v))$$

capturing weighted contributions from multiple annotation layers (Bornes-Varol et al., 2019).

4. Integration and Multimethod Applications

Polysemic case studies are often embedded in multimethod frameworks that integrate formal, statistical, and case-oriented analysis to triangulate evidence and enable theory development.

• A synergistic approach combines deductive (formal models), statistical (large-N patterns), and case paper (process tracing) traditions, leveraging each for unique inferential strengths. Sequencing might involve hypothesis formulation in formal models, statistical testing across cases, and outlier investigation via detailed case analysis (Bennett et al., 2022).
• Attention to “use novelty” and transparency in model selection ensures that each method contributes new evidence, rather than replicating findings.
• Design pattern discourse applies layered analytic methods (PAR for perception, CLA for cognitive depth, DPL for actionable design language). This integration (denoted by the equation $$\textrm{PAR} + \textrm{CLA} + \textrm{DPL} = \textrm{PLACARD}$$) supports robust action, adaptability, and multi-perspectival enrichment (Corneli et al., 2021).

5. Practical Implementations and Knowledge Infrastructure

Polysemic case studies have direct application in building interoperable knowledge bases, advanced educational environments, and robust linked data architectures.

• The multi-thesauri scenario publishes SKOS-enabled vocabularies via SPARQL endpoints, then interlinks them for semantic interoperability—enabling term-, concept-, and data-level integration for advanced search and retrieval (Mayr et al., 2010).
• In contrastive case analyses, multiple cognitive and ecological models (e.g., framing, case-based reasoning, environmental affordance) explain variance in learning outcomes and scaffold the negotiation of meaning across activity structures (Camp, 2013).
• Resource graph representations model the coordination of visual, verbal, algebraic, and gestural modes in physics problem-solving, extending polysemic analysis to compound, discipline-specific representations (Weliweriya et al., 2018).

6. Challenges, Extensions, and Future Directions

Principal challenges in the polysemic case paper paradigm include the representation of non-preferred terms, composite or complex mappings, and handling cross-domain or diachronic variability.

• Extension of SKOS mapping schema and annotation protocols is necessary to represent complex many-to-many or “combination” mappings, as well as to encode subtle cultural or diachronic semantic shifts (Mayr et al., 2010, Bornes-Varol et al., 2019).
• Automated approaches to semantic shift detection, as exemplified in tracking “polymorphism,” “semaphore,” and “ontology” across domains (Choi et al., 2023), can be formalized using word embedding techniques:

$$\Delta \mathbf{v}(t) = \mathbf{v}(t + \Delta t) - \mathbf{v}(t)$$

where semantic change is quantified by the norm of context vector differences over time.

• Methodological rigor and explicit guideline development are vital in generalizing case survey methods (and analogous template-based frameworks) for reliable, reproducible research—especially in fields with evolving practices and epistemic ambiguity (Melegati et al., 2020).

7. Disciplinary Significance and Theoretical Implications

The polysemic case paper approach systematically embraces complexity, ambiguity, and context dependence as resources rather than obstacles.

• In Flyvbjerg’s framework, case studies are positioned as loci for generating and testing hypotheses—emphasizing the narrative richness and selective force of critical exemplars for theory building (Flyvbjerg, 2013).
• Interdisciplinary approaches show that methods and annotation protocols with roots in one domain (e.g., elite training or futures studies) can be productively adapted and enriched through polysemic application in design, knowledge management, or computational modeling (Corneli et al., 2021).
• By making explicit the multiple layers, modalities, and cross-domain sense mappings, polysemic case studies support more precise, interoperable, and generalizable models—serving as a foundation for semantically rich research infrastructures and innovative scientific processes.

In sum, the polysemic case paper approach provides a robust methodology for systematically addressing and leveraging context-dependent, multi-layered meaning across domains, modalities, and research traditions. Its integration of annotation, mapping, multimethod analysis, and interoperability is central to advancing theory, infrastructure, and practice in contemporary research environments.