Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Data Interpretation in Structural Health Monitoring: Toward a Universal Language.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read Online Read More Add to Saved list
  • Additional Information
    • Source:
      Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
    • Publication Information:
      Original Publication: Basel, Switzerland : MDPI, c2000-
    • Subject Terms:
      Algorithms* ; Monitoring, Physiologic*/methods; Humans ; Language ; Semantics
    • Abstract:
      Structural Health Monitoring (SHM) relies on the effective communication between sensors and diagnostic systems, yet data interpretation remains inconsistent and subjective. This paper introduces a novel perspective, viewing data as a form of language with its own syntax, semantics, and pragmatics. By adopting this linguistic framework, the study emphasizes the need for standardized "grammars" in data collection, processing, and analysis to reduce ambiguity and enhance diagnostic reliability. Using case studies from SHM, the paper illustrates how subjective decisions in variable selection, cluster labels, preprocessing, and modeling introduce biases that affect the outcomes. The findings highlight the potential of context-aware algorithms and integrated data sources to mitigate these biases. This conceptual approach has broader implications for data science, suggesting a universal "language of data" that fosters consistency and collaboration across disciplines. By recognizing the constructed nature of data, this work offers a path toward more accurate, efficient, and reliable structural diagnostics, advancing both SHM practices and data interpretation methodologies.
    • References:
      Sensors (Basel). 2017 Dec 01;17(12):. (PMID: 29194384)
      Sensors (Basel). 2018 Nov 01;18(11):. (PMID: 30388876)
    • Contributed Indexing:
      Keywords: AI and machine learning in SHM; Structural Health Monitoring (SHM); data interpretation; data standardization; diagnosis; diagnostic reliability; linguistic framework; monitoring; subjectivity in data
    • Publication Date:
      Date Created: 20250528 Date Completed: 20250528 Latest Revision: 20250604
    • Publication Date:
      20250604
    • Accession Number:
      PMC12115346
    • Accession Number:
      10.3390/s25103054
    • Accession Number:
      40431847