Semantic Validation Research Articles

Towards a Fault Management Analysis Tool for Model Centric Systems Engineering

In an effort to effectively develop more complex spacecraft fault management (FM) systems new technologies are sought to enable rapid diagnostic model generation and validation, and provide tools to perform FM analyses Model-based Systems Engineering approaches to FM system development are uniquely suited to be combined with model-based tools currently utilized in the design of other parts of flight systems. Combined tools utilizing information from a common system model can reduce design inconsistencies and gaps in analyses. Tighter integration of FM with other system-level and subsystem-level hardware/software development activities allows crucial redundancy and sensor placement trades to be performed earlier and throughout the mission lifecycle. Our work has been towards the integration of a model-based fault management tool suite called MONSID®, with JPL’s Computer Aided Engineering for Systems ARchitecture (CAESAR ) platform as a way to improve FM system modeling and analysis. MONSID relies on application-specific models of the system being monitored. MONSID models consist of interconnected elements representing system hardware and measurement/command input points, called the topology. Model topology design is currently a manual process and often relies heavily on paper documentation such as hardware/software specs, engineering drawings, and interface control documents. CAESAR is a semantically- driven toolchain for model-based system engineering. At the core is a system model expressed in the Ontological Modeling Language (OML). It is intended to support semantic modeling, consistency validation, and continuous integration. A goal of the combined toolset is to automate FM model development by directly extracting models from CAESAR and then analyzing them in MONSID. Analyses currently available in MONSID include model topology inspection and validation and fault isolation capability based on sensor placement. While we have focused on two specific tools, the integration approaches can be leveraged by other semantically driven model-centric platforms and tools. This paper describes the evolution of our integration approaches as we evaluated different insertion points in the CAESAR toolchain with respect to MONSID model requirements. The MONSID-CAESAR tool is demonstrated on a simplified example of a spacecraft heat reclamation system. Results of the generated MONSID model are discussed, including levels of automation achieved and information surfaced to the users about the extracted model topology.

Metadata harvesting for digital library integration in Ukraine: a comparative study of the OAI-PMH protocol and VuFind’s efficacy

Purpose This paper aims to the problem of building an environment to support scientific research in connection with the development of Open Science in Ukraine. Design/methodology/approach An overview of modern portals for aggregating scientific data was conducted. Analysis of available tools and identifying problems that arise when collecting data from digital libraries and journals was conducted. The validity of choosing VuFind as a tool that allows building an extraction–transformation–loading (ETL) approach for data aggregation and bringing the format and values of metadata fields to one view was experimentally verified. Findings During the experimental verification, problems related to the fact that the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) protocol does not have strict requirements for the data structure, which lead to the complexity of integration, despite the fact that this protocol occupied a leading position, were noted. To simplify these problems, an ETL approach that allowed for the use of ontological methods (e.g. data mapping, linked data and dictionaries to improve the semantics of data for integration processes) was considered. A review of the possibilities of modern tools for OAI-PMH integration, which were actively supported and developed, was conducted. Originality/value This paper was an attempt to outline the problems that arose in integrating resources, with the aim of developing future integration protocols that would have simple means of semantic data validation and built-in ETL mechanism.

Semantic Web-Based CRUD Operation and Constraint Validation for IFC-Based Information Management

Semantic Web-Based CRUD Operation and Constraint Validation for IFC-Based Information Management

Development and Validation of a Game for Older Adults on Lifestyles and Frailty.

Games are a promising strategy for rehabilitating older adults. The effect of games on promoting healthy lifestyles and preventing frailty remains uncertain. This article aims to describe the process of development and validation of the game "Bem-me-quer para a saúde"® to promote the acquisition of healthy lifestyles and prevent frailty in over 65-year-olds. This study comprised three distinct phases, spanning from December 2023 to June 2024. The first phase comprised a thorough review of the scientific literature on the frailty and lifestyles of older adults, a second phase of game design, and a third phase of content and semantic validation conducted by specialized nurses and older adults. After revising literature, this study utilized an e-Delphi with a panel of 14 specialist nurses who underwent two rounds of evaluation. The "Bem-me-quer para a saúde"® game includes a puzzle board with 54 pieces and 30 educational cards. In the final phase, we evaluated the game on a cohort of 50 older adults, highlighting its reflective, interactive, and educational aspects. The game presented sufficient evidence of content validity and relevance to clinical practice. We should conduct additional research to evaluate its impact on lifestyle modification and frailty prevention.

Semantic validation of nursing outcome dry eye severity in intensive care

Objective: To semantically validate the indicators of the nursing outcome Dry Eye Severity in adult patients admitted to the intensive care unit. Methods: Methodological study of semantic validation developed with 15 nurses from an adult general ICU of a public university hospital located in the Northeast of Brazil. Data collection took place between the months of February and April 2019. For data analysis, the Kappa test was used with a value equal to or greater than 85% agreement. A value of p<0.05 was used to indicate statistical significance when the proportion was less than 85%. Results: After evaluating the nurses in relation to the constitutive and operational definitions and operational magnitudes of the indicators, all presented agreement ≥ 0.85. As all indicators that presented statistically significant p values (p < 0.05) presented a cutoff point with perfect agreement, all were admitted. In addition, the nurses' comments and suggestions were taken into account for the final version of the analysis. Conclusion: In the general evaluation of the NO Dry Eye Severity by the nurses, it was...

Forms of Gender Equality on Female Characters in Singkar Novels

This research aims to analyze the representation of gender equality through the characterization of female characters in the novel Singkar by Siti Aminah. Using a descriptive approach and feminist analysis framework, this research explores the forms of gender equality displayed by female characters and their relationship with the construction of their characters in the novel. The research data in the form of the entire text of the novel Singkar was analyzed through read-and-record techniques and descriptive analysis. Semantic validity and intraretter reliability were used to ensure data validity. The results showed five forms of gender equality expressed by female characters in the novel: 1) autonomy in making decisions, 2) ability to overcome problems, 3) courage to take responsibility, 4) participation in earning a living, and 5) resilience as a single parent. This finding confirms that the characterization of female characters in Singkar is the basis for actions that reflect gender equality.

Anxiety Inventory for Respiratory Disease: Cross-Cultural Adaptation and Semantic Validity of the Brazilian Version for Individuals with Chronic Obstructive Pulmonary Disease.

Most instruments available to screen for anxiety in people with chronic obstructive pulmonary disease (COPD) are not disease specific. Therefore, the Anxiety Inventory for Respiratory Disease (AIR) was developed to measure anxiety for this patient group; however, it requires cross-cultural adaptation for use in non-English speaking countries. To carry out cross-cultural adaptation of the AIR scale for Brazilian patients with COPD and to analyze its semantic validity. This methodological study followed six stages: 1) Initial translation by two independent translators fluent in English; 2) Synthesis of translations; 3) Back translation by two English first language translators; 4) Expert committee review (eight healthcare professionals, a methodologist, the translators, and back-translators); 5) Pre-final version evaluation with 30 patients with COPD through a cognitive interview; and 6) Submission of documents. Semantic validity was analyzed by agreement rate and content validity index (CVI) for the committee equivalence assessments. 1) Initial translation: the two translated versions presented eight divergences; 2) Synthesis of translations: the differences were discussed to reach consensus; 3) Back-translation: there were no important inconsistencies; 4) Expert Committee: the experts proposed eight and the instrument developer proposed three changes, which were analyzed and voted on, resulting in the pre-final version; 5) Evaluation of the pre-final version: data collection allowed for other changes and the formulation of instructions by applying the adapted instrument in an interview format. Patients rated the questions as clear or very clear; 6) The expert committee and the developer approved the final documents. The agreement rate and CVI were ≥ 0.80 for all items of the scale final version. The process of cross-cultural adaptation followed all necessary stages and the semantic validity results were adequate, providing the Brazilian version of the AIR to assess anxiety symptoms in patients with COPD.

Design and Implementation of an Ontology for Measurement Terminology in Digital Calibration Certificates.

Digital Calibration Certificates (DCCs) are a key focus in metrology digitalization, necessitating that they satisfy the criteria for machine readability and understandability. Current DCCs are machine-readable, but they are still missing the essential semantic information required for machine understandability. This shortfall is particularly notable in the lack of a dedicated semantic ontology for measurement terminologies. This paper proposes a domain ontology for measurement terminologies named the OMT (Ontology for Measurement Terminology), using a foundation of metrological terms from standards like the International Vocabulary of Metrology (VIM), the Guide to the Expression of Uncertainty in Measurement (GUM), and JJF1001. It also incorporates insights from models such as the SI Reference Point, the Simple Knowledge Organization System (SKOS), and the DCC Schema. The methodology was guided by Stanford's Seven-Step Method, ensuring a systematic development process tailored to the needs of metrological semantics. Through semantic expression capability verification and SPARQL query validations, the OMT has been confirmed to possess essential machine readability and understandability features. It has been successfully integrated into version 3.2.1 of DCCs across ten representative domains. This integration demonstrates an effective method for ensuring that DCCs are machine-readable and capable of interoperating within digital environments, thereby advancing the research in metrology digitization.

Translation and Validation of the Nutrition for Sport Knowledge Questionnaire in Brazil (NSKQ-BR).

This study aimed to translate, culturally adapt, and validate "The Nutrition for Sport Knowledge Questionnaire (NSKQ)" for Brazilian athletes. The NSKQ is an Australian instrument composed of 87 questions divided into six subsections (weight control, macronutrients, micronutrients, sports nutrition, supplementation, and alcohol) designed to assess the nutritional knowledge (NK) of athletes. The translation process followed the recommendations of the World Health Organization for translating and adapting instruments. Semantic validation involved a panel of specialists (n = 21), followed by an assessment performed by a group of adult Brazilian athletes from various sports (n = 17). The reproducibility and internal consistency of the questionnaire were evaluated via a test-retest approach in a sample of adult Brazilian athletes (n = 29) from diverse sports, who completed the Brazilian version of the NSKQ (NSKQ-BR). Overall, the NSKQ-BR presented good internal consistency (α = 0.95) and reproducibility (intraclass correlation coefficient (ICC) = 0.85). The factors "sports nutrition" and "alcohol" showed moderate reproducibility (ICC = 0.74 (0.46-0.88) and ICC = 0.68 (0.33-0.85), respectively). Most athletes (n = 17; 58.6%) presented a medium NK score (50-65%). The NSKQ-BR is available to evaluate the NK levels of Brazilian athletes. The NSKQ-BR presented high internal consistency and reproducibility, validating its applicability among adult athletes across diverse sports.

Fuzzing JavaScript engines with a syntax-aware neural program model

Neural network language modeling has become a remarkable approach in the generation of test cases for fuzzing JavaScript engines. Fuzzers built upon neural language models offer several advantages. They obviate the need for manually developing code generation rules, enable the extraction of patterns from high-quality seed sets, and exhibit commendable portability. Nevertheless, existing works confront challenges in three key aspects: diminished language modeling performance attributable to extensive vocabularies, potential semantic errors within generated test cases, and the limitation of black-box fuzzing, which fails to leverage the internal feedback from the target engine.This paper proposes an innovative neural model-based grey-box fuzzing approach for JavaScript engines. We incorporate the context-free grammar of JavaScript into the neural language model to mitigate the challenges associated with extensive vocabularies, thereby enhancing the model’s performance. Furthermore, to enhance the semantic validity of the generated test cases, we introduce semantic constraints into the mutation process. Notably, this work pioneers the integration of grey-box testing into a fuzzer built upon a neural language model, thereby enhancing the exploration of deep paths. Our prototype, PMFuzz, surpasses NNLM-based counterparts in both language modeling performance and test case generation capabilities. PMFuzz demonstrates a high level of competitiveness in exploring the software state space when compared to traditional coverage-guided grey-box fuzzers. In our evaluation, PMFuzz successfully identified 20 new defects within mainstream JS engines. Eight of them have been confirmed and fixed. Moreover, upon applying our method to C compilers, PMFuzz has revealed 11 new defects.

Distribution-aware fairness test generation

Ensuring that all classes of objects are detected with equal accuracy is essential in AI systems. For instance, being unable to identify any one class of objects could have fatal consequences in autonomous driving systems. Hence, ensuring the reliability of image recognition systems is crucial. This work addresses how to validate group fairness in image recognition software. We propose a distribution-aware fairness testing approach (called DISTROFAIR) that systematically exposes class-level fairness violations in image classifiers via a synergistic combination of out-of-distribution (OOD) testing and semantic-preserving image mutation. DISTROFAIR automatically learns the distribution (e.g., number/orientation) of objects in a set of images. Then it systematically mutates objects in the images to become OOD using three semantic-preserving image mutations – object deletion, object insertion and object rotation. We evaluate DISTROFAIR using two well-known datasets (CityScapes and MS-COCO) and three major, commercial image recognition software (namely, Amazon Rekognition, Google Cloud Vision and Azure Computer Vision). Results show that about 21% of images generated by DISTROFAIR reveal class-level fairness violations using either ground truth or metamorphic oracles. DISTROFAIR is up to 2.3× more effective than two main baselines, i.e., (a) an approach which focuses on generating images only within the distribution (ID) and (b) fairness analysis using only the original image dataset. We further observed that DISTROFAIR is efficient, it generates 460 images per hour, on average. Finally, we evaluate the semantic validity of our approach via a user study with 81 participants, using 30 real images and 30 corresponding mutated images generated by DISTROFAIR. We found that images generated by DISTROFAIR are 80% as realistic as real-world images.

The Chinese version of the general benefit finding scale (GBFS): Psychometric properties in a sample of college students.

Benefit finding has become a central construct in the evolution of positive psychology and attracted attention in recent literature. This study aimed to translate and validate the General Benefit Finding Scale (GBFS) in Chinese college students. Forward- and back-translation of the GBFS was followed by the assessment of semantic equivalence and content validity. A sample of 589 college students was recruited in China to conduct reliability and validity analysis. The construct validity was assessed using exploratory (EFA) and confirmatory factor analysis (CFA). Concurrent validity was assessed using Pearson's correlation coefficients of the GBFS with the Perceived Stress Scale (PSS) and World Health Organization-Five Well-Being (WHO-5). Internal consistency and two-week test-retest reliability were also evaluated. The content validity index for each item ranged from 0.83 to 1.00. EFA revealed a six-factor model, which exhibited acceptable goodness of fit in CFA (standardized root mean square residual = 0.031, root mean square error of approximation = 0.059, goodness-of-fit index = 0.860, comparative fit index = 0.904, Tucker-Lewis index = 0.890, chi-squared/degree of freedom = 2.07). The concurrent validity of the GBFS was supported by its statistically significant correlations with PSS (r = -0.271, p<0.001) and WHO-5 (r = 0.354, p<0.001). Moreover, the internal consistency for the overall scale was satisfactory, with Cronbach's α coefficient of 0.93 and McDonald's omega reliability of 0.94. The test-retest reliability was 0.82. Although the Chinese version of GBFS was examined in a homogeneous convenience sample of college students, it provides a reliable and valid instrument for assessing benefit finding in the Chinese context.

Deriving semantic validation rules from industrial standards: An OPC UA study

Industrial standards provide guidelines for data modeling to ensure interoperability between stakeholders of an industry branch (e.g., robotics). Most frequently, such guidelines are provided in an unstructured format (e.g., pdf documents) which hampers the automated validations of information objects (e.g., data models) that rely on such standards in terms of their compliance with the modeling constraints prescribed by the guidelines. This raises the risk of costly interoperability errors induced by the incorrect use of the standards. There is, therefore, an increased interest in automatic semantic validation of information objects based on industrial standards. In this paper we focus on an approach to semantic validation by formally representing the modeling constraints from unstructured documents as explicit, machine-actionable rules (to be then used for semantic validation) and (semi-)automatically extracting such rules from pdf documents. While our approach aims to be generically applicable, we exemplify an adaptation of the approach in the concrete context of the OPC UA industrial standard, given its large-scale adoption among important industrial stakeholders and the OPC UA internal efforts towards semantic validation. We conclude that (i) it is feasible to represent modeling constraints from the standard specifications as rules, which can be organized in a taxonomy and represented using Semantic Web technologies such as OWL and SPARQL; (ii) we could automatically identify modeling constraints in the specification documents by inspecting the tables ( P = 87 %) and text of these documents (F1 up to 94%); (iii) the translation of the modeling constraints into formal rules could be fully automated when constraints were extracted from tables and required a Human-in-the-loop approach for constraints extracted from text.

Organizational Climate Scale for Public Service: Development and Validation

This research presents four studies that developed and validated the Organizational Climate Perception Scale for Public Service (OCPS-PS). The first qualitative study consulted the literature and conducted a focus group to develop the initial version of the scale. The second study involved expert evaluation and pre-testing, aiming at the semantic and face validation of the items. This study resulted in 80 items forming the thirteen dimensions of organizational climate. The third study obtained the first quantitative sample for the exploratory validation phase of the scale. The final study, using a new sample, conducted confirmatory tests for the validation of the scale. A methodology for applying the scale was developed, allowing all interested parties to use the OCPS-PS for the assessment of the organizational climate in public service. The results of the four conducted studies indicate the adequacy of the OCPS-PS according to the proposed criteria of validity and reliability. Finally, the OCPS-OS was built to be applied in different public organizations and at different government levels.

Cross-cultural differences through subjective cognition: illustration in translatology with the SSTIC-E in the UAE.

The development of appropriate and valid multicultural and multilingual instruments research is necessary due to a growing multicultural and multilingual society in the 21st century. We explored the use of a cognitive scale related to subjective complaints, focusing on the first step: a cross-cultural and semantic validation. This study presents the translation and cross-validation process of the "Subjective Scale to Investigate Cognition in Schizophrenia" (SSTICS) for the United Arab Emirates (UAE) region via different languages used in Dubaï/Abu Dhabi. This scale measures cognitive complaints and has been validated with psychosis and used in 20 clinical trials worldwide. It evaluates areas of the illness related to self-awareness focusing on memory dysfunction and deficits of attention, language, and praxis. We described the method of cross-cultural validation, with back-translation, semantic steps, and societal contexts. The use of the Subjective Scale to Investigate Cognition in Emirates (SSTIC-E) was explored with different samples of UAE Arabic-speaking subjects. First, a pilot sample mean SSTICS total score was 16.5 (SD:16.9); (p < 0.001). The SSTIC-E was then administered to 126 patients and 84 healthy control participants. The healthy group has a lower mean score of 22.55 (SD = 12.04) vs. 34.06 (SD = 15.19). The method was extended to nine other languages, namely, Pakistani/Urdu, Hindi, Marathi, Lithuanian, Serbian, German, Romanian, Sinhala, and Russian. The scales are provided in the article. The overall aim of the translation process should be to stay close to the original version of the instrument so that it is meaningful and easily understood by the target language population. However, for construct validity, some items must be adapted at the time of translation to ensure that the questioned cognitive domain is respected. For example, cooking, an executive function, does not have the same occurrence for an Emirati male, or remembering a prime minister's name, semantic memory, requires an electoral system to appoint the leader of a country. Translation methods and processes present many challenges but applying relevant and creative strategies to reduce errors is essential to achieve semantic validation. This study aims to measure personally experienced knowledge or attitudes; such language effects can be a thorny problem.

Development and validation of an instrument on the perception of grandparents caring for grandchildren

Objective: develop and validate an instrument to characterize sociodemographic aspects, health conditions and care among elderly grandchild carers. Method: methodological study performed by active search on studies and instruments with the proposed theme, construction and validation of content, reliability and semantics of the instrument items. Results: the total Content Validity Index of the instrument, after validation by the judges, was 0.93%, which means that the content of the instrument makes it possible to measure what it proposes to measure. As for the reliability of the instrument, it presented an Intraclass Correlation Coefficient of 0.87 (95%CI 0.72 - 0.96), indicating that there is excellent stability of continuous variables. Cronbach's alpha presented a value of α=0.867, revealing the instrument's internal consistency. Brainstorming indicated that the items are easy to understand, with no major doubts on the part of the pilot group. Conclusion: The proposed instrument was developed and validated, and can contribute to the practice of professionals and researchers by unveiling the care relations between grandparents and grandchildren, besides supporting the development of public policies.

Translation and linguistic validation of the Sheffield Profile for Assessment and Referral for Care (SPARC) to Colombian Spanish.

We aimed to translate and linguistically and cross-culturally validate Sheffield Profile for Assessment and Referral for Care (SPARC) in Spanish for Colombia (SPARC-Sp). The linguistic validation of SPARC followed a standard methodology. We conducted focus groups to assess the comprehensibility and feasibility. The acceptability was assessed using a survey study with potential users. The comprehensibility assessment showed that additional adjustments to those made during the translation-back-translation process were required to apply SPARC-Sp in rural and low-schooled populations. It also identified the need for alternative administration mechanisms for illiterate people. The acceptability survey showed that potential users found SPARC-Sp as not only acceptable but also highly desirable. However, they desired to expand the number of items in all domains. Beyond the semantic and conceptual validity attained through the back-translation process, actual cultural validity could be acquired thanks to the comprehensibility tests. Although extending the instrument is something potential users would like to do, it would make it less feasible to utilize the SPARC-Sp in clinical settings. Nonetheless, the instrument might benefit from the inclusion of a domain that evaluates challenges encountered when accessing the health-care system. For communities lacking literacy, alternate administration methods must also be considered.

Translation and Cross-cultural Adaptation of the SOSG-OQ 2.0 Questionnaire into Brazilian Portuguese.

Objective: To perform the cross-cultural adaptation and translation into Brazilian Portuguese of the Spine Oncology Study Group - Outcomes Questionnaire 2.0 (SOSG-OQ 2.0) to enable its application to Brazilian patients and to allow Brazilian researchers to use a questionnaire that is on trend in the scientific literature. Materials and Methods: The present is a basic, non-randomized, non-comparative study. The translation followed the proposal by Reichenheime and Moraes, mainly for the semantic equivalence and measurement equivalence sessions, as well as the recommendations by Coster and Mancini mainly in the translation stage. The stages were as follows: first - translation into Brazilian Portuguese; second - back-translation; third - semantic comparison; fourth - validation of the final construct. Results: The translations of the SOSG-OQ 2.0 made by three translators presented a high degree of similarity for most questions. The translators kept all question titles and subtitles, as well as their internal and external orders. Two sworn translators, with native proficiency in English, performed the back-translation of the amalgamated text. Both back-translations were quite similar, and any differences were solved through consensus between the main author and the sworn translators, and the translated text was considered the final version. Conclusion: The present study shows a translated version of the SOSG-OQ 2.0 with semantic validity with the original version published in English. As such, researchers can apply the questionnaire to the Brazilian population, adding another tool for spine surgeons to improve the monitoring of this complex group of patients.

Translation, Reliability, and Validity of the Japanese Clinical Reasoning Skills Self-Evaluation Scale: An Instrument Design Study.

Currently, little evidence supports the notion that improved practical skills through simulation education are reflected in actual clinical practice and ultimately lead to positive outcomes for participants. However, by clarifying the relationship between the simulation foundation and its practicality, insights can be gained to develop educational programs to improve clinical reasoning skills. However, no clear scale is currently available in Japan. To create a valid Japanese version of the clinical reasoning skills self-evaluation scale and evaluate its reliability and validity. This instrument design study included 580 nursing students and nurses surveyed online from February to March 2023. The clinical reasoning skills self-evaluation scale was translated into Japanese using a back-translation method, and semantic equivalence and content validity were assessed. The content validity index was assessed using a pilot test involving 26 clinical nurses, 25 nursing students, and an expert panel. Validity and reliability were tested using a convenience sample of 580 nursing students and nurses. Reliability was assessed using internal consistency and test-retest reliability. Construct validity was assessed using confirmatory factor analysis. Cronbach's alpha for all dimensions was >0.7, and the questionnaire showed acceptable internal consistency. Test-retest reliability was evaluated using the intraclass correlation coefficient (0.674-0.797, all dimensions); the lowest value at a 95% confidence interval was 0.504 (at least moderate reliability). Our scale has acceptable validity and reliability. It may help in clinical reasoning skill assessment for nurses and nursing students and aid in examining and supporting these skills.

Multi-Dimensional Validation of the Integration of Syntactic and Semantic Distance Measures for Clustering Fibromyalgia Patients in the Rheumatic Monitor Big Data Study.

This study primarily aimed at developing a novel multi-dimensional methodology to discover and validate the optimal number of clusters. The secondary objective was to deploy it for the task of clustering fibromyalgia patients. We present a comprehensive methodology that includes the use of several different clustering algorithms, quality assessment using several syntactic distance measures (the Silhouette Index (SI), Calinski-Harabasz index (CHI), and Davies-Bouldin index (DBI)), stability assessment using the adjusted Rand index (ARI), and the validation of the internal semantic consistency of each clustering option via the performance of multiple clustering iterations after the repeated bagging of the data to select multiple partial data sets. Then, we perform a statistical analysis of the (clinical) semantics of the most stable clustering options using the full data set. Finally, the results are validated through a supervised machine learning (ML) model that classifies the patients back into the discovered clusters and is interpreted by calculating the Shapley additive explanations (SHAP) values of the model. Thus, we refer to our methodology as the clustering, distance measures and iterative statistical and semantic validation (CDI-SSV) methodology. We applied our method to the analysis of a comprehensive data set acquired from 1370 fibromyalgia patients. The results demonstrate that the K-means was highly robust in the syntactic and the internal consistent semantics analysis phases and was therefore followed by a semantic assessment to determine the optimal number of clusters (k), which suggested k = 3 as a more clinically meaningful solution, representing three distinct severity levels. the random forest model validated the results by classification into the discovered clusters with high accuracy (AUC: 0.994; accuracy: 0.946). SHAP analysis emphasized the clinical relevance of "functional problems" in distinguishing the most severe condition. In conclusion, the CDI-SSV methodology offers significant potential for improving the classification of complex patients. Our findings suggest a classification system for different profiles of fibromyalgia patients, which has the potential to improve clinical care, by providing clinical markers for the evidence-based personalized diagnosis, management, and prognosis of fibromyalgia patients.