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    3D documentation and digital heritage

    Spring, Adam Patrick (2019) 3D documentation and digital heritage. Doctoral thesis (PhD), Manchester Metropolitan University.

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    Abstract

    This Doctor of Philosophy by Published Work (Route 2) examines the cultural, theoretical and technical considerations in place when Cultural Heritage (CH) also becomes digital heritage. These aspects have ended up neglected or misunderstood because they lie between the competences of the technical and cultural worlds. The aims of best practice and long-term data considerations run across all publications; as do the objectives of examining human to human-object interactions with digital technologies, exploring workflows for long term data retrieval and digital technologies to document artefacts and landscapes. They are manifested through all publications with some of the obvious examples being: a) theoretical considerations, in particular Immanuel Kant’s Empirical Provenance and the concepts of cultural memory and data narrative b) the marriage between theoretical and applied science c) recognising that 3D imaging does not operate within a vacuum and is tethered to a broader ecosystem of information and communication technologies (ICT) d) the idea of cultural memory, and how the long-term survival of digital or non-tangible information is reliant upon, in this case, human-computer interactions. e) the way in which hardware and software feed into material culture and cultural memory. These considerations are necessary in order to give data a coherent and long-term narrative. It is clearly outlined in the IEEE Computer Graphics and Applications article and is also explained in broader theoretical context via the book chapter Digital Heritage, Industrial Memory and Memorialisation. User community-led developments and workflows are strong themes running across all publications. Digital workflows and associated material cultures have become distributed. They can no longer be solely defined by centralised or otherwise grounded means of production. This is especially so in the wake of big data or crowdsourced data. Prior to these conditions, linear workflows and Fordist modes of production regulated information flow and development. These are also examined and challenged across the publications submitted.

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