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A Metadata/Paradata Design Framework for Historic BIM

  • Maurice Murphy
  • , Petra Krajacic
  • , Eimear Meegan
  • , Rebecca O. Reilly
  • , Garrett Keenaghan
  • , Alain Chenaux
  • , Rafael Fernandes Dionizio
  • , Eloisa DezenKempter

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this paper a systematic examination of metadata/paradata is presented to support the creation and reuse of digital heritage data as a means of engaging in some way with the experience of past material cultural discourse. The contextual and procedural information generated throughout Historic Building Information Modelling (HBIM) workflows are presented through a series of case studies. The three phases of data capture, modelling and knowledge dissemination for HBIM workflows are reflected in the presented case studies. The first case study illustrate how metadata is recorded automatically by the terrestrial and aerial laser scanning instruments and software, whereas it is necessary to document paradata. Case study 2, shows how shape grammar libraries of architectural elements and procedural modelling both contained metadata within the HBIM software platforms. Again, there is a need to document the paradata using both graphic and text format, proving the need for standards and guidelines for HBIM. Finally, additional software platforms were reviewed to ensure survival of metadata (geometry, geolocation and other semantic attributes) when the virtual model is disseminated outside of HBIM in this case using Heritage GIS. The HBIM design framework is presented as a set of Data Cards, a standardised documentation to record key information about datasets, allowing for enhanced reuse of the data recorded in such a way as to contribute more meaningfully to the consideration of the many and various ways of living in the past.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Science and Business Media Deutschland GmbH
Pages127-138
Number of pages12
DOIs
Publication statusPublished - 2025

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15190 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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