Guiding questions

  • How can scholarship be structured?

  • What are visual approaches in the humanities?

  • Is there an ideal structure for the 3D reconstruction process?

  • Where can digital 3D reconstruction be located within disciplines?

Basic terms

  • Visual humanities

  • Scholarly culture

  • Communities

  • Disciplines

4.1 Introduction

Further reading: Research on Scientific Communities

Various social empirical methods have been used during the last decades to evaluate, quantify, and qualify the usage of digital 3D modeling for particular fields of humanities. Most of these approaches focus on qualitative analysis, e.g., by expert boards or surveys. The EPOCH network of excellence (2004–2008) employed focus group discussions and perspectives on digital 3D techniques in cultural heritage studies [1]. While qualitative approaches are appropriate to identify and explain [2] phenomena in terms of evolutions, current states, and perspectives, they show only limited usefulness for quantifying uncovered phenomena or investigating scientific structures. The VIA project organized a series of workshops and questionnaire-based surveys to investigate visualization in archaeology in the UK [3]. From 2012, the Enumerate project has performed bi-annual monitoring of digitization activities of cultural heritage institutions within the EU—primarily museums and archives [4, 5]. The DARIAH DIMPO workgroup is periodically monitoring the digital humanities community [6]. Recently, several monitoring actions were conducted by the European Commission [7, 8], e.g., to investigate digital competency in cultural institutions [9]. Several associations surveyed the consequences of the COVID-19 pandemic for cultural institutions and their digital transition [10].Footnote 1

Research regarding scholarly behavior often relies on analyzing the publication record. With regards to a scholarly area of visual digital humanities and its adjacent fields like digital heritage, Hicks et al. [11] stated that publication and research habits are widely spread between single disciplines in the (digital) humanities. Similarly, Leydesdorff et al. [12] examined the disciplinary canon in humanities and digital humanities employing bibliometric methods. With regards to a scholarly community within the digital humanities, Terras [13] reported that until 2006, US, Canada, and UK-based researchers contributed most to academic discourse. Similarly, Grandjean performed a social network analysis of Twitter to map the digital humanities community [14]. Specifically for digital heritage, Scollar [15] investigated the Conference on Computer Application in Archaeologies from 1973 until 1996. Secondly, information habits of visual digital humanities scholars are the focus of various studies. Since older investigations found large differences in information behavior between scholars in different disciplines [16], nowadays, many scholars in art history and architecture rely heavily on digital information and perform visual search strategies [17, 18].

Scientific structures can be classified according to various criteria. One common approach is to distinguish different disciplines as branches of science. Another approach is to identify scientific communities as groups of scholars “[...] who have agreed to accept a paradigm” [19] by analysing their research outcomes. Thus, an important object of study is the author cohorts of publications, and the classification of topics of interest.

4.2 Disciplines Which Benefit from the Method

Disciplines are characterized by common methods and theories. Furthermore, they usually share comparable “reference systems, disciplinary ways of thinking, quality criteria, publication habits and bodies” [20, p. 6] and a similar institutionalization. Similarly, Knorr-Cetina thought that each discipline has its own “epistemic culture” in the sense of different “architectures of empirical approaches, specific constructions of the referent, particular ontologies of instruments, and different social machines” [21, p. 3]. Disciplines and their boundaries are social constructions [22] and a number of phenotypic fields can be identified [23]. One basic classification scheme is the distinction between humanities and sciences. In a more elaborate classification the Organization for Economic Co-operation and Development lists six scientific fields containing around 40 disciplines [24, 25]; library classification delivers highly sophisticated categorization schemes [26].

4.2.1 Visual Approaches in the Humanities

Digital 3D models are used in several humanities disciplines with highly differing settings. In comparison to text-related disciplines, the employment of digital methods related to image or object analysis recently became a major trend. Possible reasons may be the diverse nature of the methods used in disciplines focusing on these types of artifacts [27], but also the heterogeneous level of establishment of digital research methods in those disciplines [11]. Although all disciplines in the humanities are dealing with vision and visualization, some disciplines are particularly engaged here:

  • Digital humanities, despite various attempts [28,40,41,42,32], is still defined in a blurred and heterogeneous way [31, 33]. From a historical perspective, the digital humanities have evolved since the mid-2000s through the development of an independent epistemic culture from historical computer science and “humanities computing” [34,46,47,48,38]. There is a broad consensus that digital humanities deal with “the application of technology to humanities work” [33].The data foci of digital humanities are texts, audio-visual content, images, and objects. While the use of digital methods in the text-oriented disciplines is currently widely established and standardized [39, p. 10], the scope of digital methods related to images and other visual objects based on vision rather than close reading remains—despite various attempts [1, 40,52,53,43]—essentially uncharted.

  • Art and architectural history studies investigate mainly works of art and architecture from the late Antiquity to the modern age [44] to provide insights into their origin and meaning [45], their spatial, social, and political preconditions and effects [46]. Methods for investigating genetic and morphologic connections are covered by analyzing style [47] and structure [48]. Another important range of methods is concerned with the meaning of the works of art (iconography) and systems of meaning (iconology) [47].

  • Museology focuses on the presenting and collecting of cultural heritage, and ways to educate the public [49]. Digital technologies are used to enhance museum visits, e.g., visitor information systems and didactically enhanced applications. Other scenarios are virtually accessible collections and virtual museums, which have no counterpart in the real world [50].

  • Archaeology investigates tangible remains and evidence of human culture [51, p. 11] to generate a representation of what exists now and closely approximates what may have once been [52]. Often, it is not possible to physically preserve the archaeological site, making thorough documentation and data collection highly relevant. Surveying techniques [53,65,66,67,57] and traditional photos and plans are used to document excavations.

  • Architecture deals with the design and construction of built environments. Architecture is usually part of engineering or design sciences and deeply linked to the processes of design and of understanding, learning, and teaching spatial imagination. Although digital 3D models are frequently used, especially the creation of haptic architectural models has not yet fully shifted into the virtual world [58].

  • Heritage studies comprise a variety of approaches to human culture and behavior related to heritage [59, 60]. Relevant strands are derived from humanities, social sciences, design and engineering, most frequently anthropology, history, and architecture [61].

Citizen Science and 3D Models

A large amount of 3D heritage content is user-generated. Sketchfab, currently the largest repository for 3D content, hosted 100,000 3D cultural heritage models in 2019, representing 30% of all 3D models on this platform [62]. User creation is strongly supported by the availability of ready-to-use photogrammetric applications and open-source 3D modeling tools. In terms of level of participation (Fig. 4.1), most citizen science projects use crowdsourcing as the involvement of “non-scientists to help to analyze or collect data as part of a researcher-led project” [63] p. 259]. Examples include collecting and processing images as a prerequisite for 3D photogrammetry [64], or crowd-based creation of 3D models [65, 66]. Co-design “involves citizens into the research process from its beginnings, or the stimulus for the research project originates from the citizens” [67 p. 4]. Although more prominent in humanities research [68], co-design is frequently used for 3D content and experience design for museums [69, 70] or (serious) history games [71]. Besides the challenges of participatory processes such as user activation and management, task definition or quality control [72], citizen science in the humanities has to handle complex, non-standardized, and knowledge-intensive tasks, which are challenging to operationalize and to assess for scientific quality of processes and outcomes [73, 74]. Other activities involving citizens in open science processes related to 3D modeling include metadata enrichment and annotation of 3D models [75].

Fig. 4.1
A C S C E Community Participation Model ranging from transmissive with convey and consume to transformational with co-create with details on interactions, goals, activities, power balance, and slogans.

The CSCCE Community Participation Model distinguishes between several types of citizen engagement [76]

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4.2.2 Visual Digital Humanities

Digital humanities disciplines dealing with the visual share a grounding in visual literacy, that is “the abilities to understand (read), and use (write) images (and spatial objects), as well as to think and learn in terms of images (and spatial objects)” [77, p. 26]. Against this background, the term “visual digital humanities” [78] was coined to cover research approaches in the digital humanities dependent on both consuming and producing pictorial and spatial, rather than textual, information to answer research questions [79]. Visual digital humanities encompass computational-supported research on complex visual information to treat research questions and interests from the humanities (e.g., a composition of complex figurative paintings), concerning aspects of data collection; data retrieval; reconstructing, simulating, and producing objects (e.g., 3D models); administering and organizing people and objects [80, 81]. Tasks include the collection, semantic enrichment, and analysis of complex visual information, and the creation of imagery:

  • Image analysis (e.g., pattern analysis of large-scale image collections)

  • Perception-based techniques (e.g., visuospatial analysis of architectural objects)

  • Spatial modeling (e.g., 3D reconstruction of historical architecture)

  • Visualization (e.g., sketching for visuospatial reasoning)

Objects are cultural heritage artifacts and images, and scholars in visual digital humanities use technologies to “understand (read), and use (write) images [and spatial objects], as well as to think and learn in terms of images [and spatial objects]” [82].

The digital 3D reconstruction of past, altered, or never-realized buildings is a research method that can supposedly be assigned to the history of architecture. This kind of categorization within academic disciplinary boundaries is part of a much broader debate [83, 84], which in our case can be divided into several exemplary problems.

First, the overarching, general method of reconstruction finds its application in numerous disciplines of the humanities (of course subjects outside of the humanities also use reconstruction to arrive at or communicate research results, e.g., experimental setup in the natural sciences). Since a reconstruction inevitably leads to a model, the process of creating the model can be cited as part of the method, especially in technical subjects [85]. As a research discipline, architecture has always worked with reconstructions, models, and design- as well as construction processes [86, pp. 73–74]. Criticism and experiences of reconstruction methods are, therefore, to be expected and evaluated in an interdisciplinary way.

Secondly, despite limiting our case to historical architecture, no sharp disciplinary boundary can be drawn. The thematic intersection of the archaeological subjects, architectural history from the perspective of art history, building research from the perspective of the architectural faculties at technical universities as well as the sciences of monument preservation and museum didactics, is simply too large. Differences can at best be found in the academic tradition rather than in the subject matter. Since the epistemological differences mostly relate to the questions posed before or during the reconstruction process, the motives for the differences are not clear. The motives for creating digital 3D models are directly dependent on the creator’s professional tradition.

Thirdly, in digital 3D reconstruction, team members of different academic backgrounds and specialist traditions usually work together. Clients have certain expectations and prior knowledge about the object to be reconstructed and thus set the necessary framework conditions. 3D modelers possess both the technical skill and craft to create the reconstruction. Again, the professional tradition of the 3D modeler can have a considerable influence on the process and outcome (i.e., the 3D model), not least on the choice of modeling software. As a user, not a developer, the 3D modeler has no influence on the 3D modeling software. Therefore, computer graphics is an aspect of digital 3D reconstruction that sometimes receives too little attention but has a decisive influence on its result. The mediator between the client and the 3D modeler is often a technical expert who structures the knowledge about the reconstruction object in terms of their own specific field. All these roles may be taken by people in the same professional tradition or even the same person. Nevertheless, the resulting 3D reconstruction is highly dependent on the experience gained from the individual steps.

In an ideal scenario, the client controls the entire reconstruction process according to their requirements, the 3D modeler has the technical and professional prerequisites, and a computer scientist guarantees individual computer graphic requirements. The latter applies to the virtual environment (i.e., modeling software) in which the 3D model is created and the communication of the results (→Workflows). The technical expert also accompanies the entire process, from the research on which to base the reconstruction to evaluating and documenting the results.

In view of these idealized, highly specialized steps, disciplinary boundaries are obstacles that must be overcome in the collective work process. Therefore, digital 3D reconstruction should possibly even be treated as an interdisciplinary research field of its own. As is evident from the history of models (→Basics and Definitions), digital 3D reconstruction developed from a long-established specialist tradition. It remains to be clarified whether an independent culture of knowledge is developing across that will reach its full potential beyond existing academic disciplinary boundaries.

4.3 Scholars and Topic Areas

Another approach to study scientific communities starts from the assumption that publications such as conference papers and journals are main podia for knowledge sharing in academia [87]. What is the background of people who are actively publishing in the field of cultural heritage? Despite various attempts to attract researchers from other parts of the world, e.g. at conference locations in non-European countries, the community is primarily European.

Within Europe the majority of researchers in the field of digital heritage are Italian, followed by Germans and Greek (Fig. 4.2). What are disciplinary backgrounds of authors? Concerning findings shown in Fig. 4.3, a majority of participants assorted themselves to humanities. Most frequently named within this discipline was archaeology [88].

Fig. 4.2
A vertical bar graph with frequency count up to 250 on the y-axis and categories like Data Management, Acquisition, Analysis, and Education on the x-axis. Others has the highest count up to around 200 while the lowest is for education at 0.

Nationality of scholars in the field of digital heritage (Online Survey, conducted in 2016, Top 10 out of n = 693) [87]

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Fig. 4.3
A vertical bar graph with frequency count up to 300 on the y-axis and categories like humanities, computing, geo sciences, architecture, engineering, natural sciences, and design on the x-axis. Humanities has the highest count up to around 270 while the lowest is for design at around 20.

Disciplinary background of conference participants (Online survey, conducted in 2016, n = 752) [87]

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Concerning the individual topic areas (Fig. 4.4), data management was most frequently named, ranging from GIS and BIM to metadata schemes and data architecture. These were followed by data acquisition, photogrammetry, laser scanning, and other surveying technologies. Many responses to the survey on topic areas did not fit into the predefined categories and were subsumed in “Others”—in most cases, specific methods, or objects of research. A discourse in conference publications is primarily driven by technologies, and the most common keywords refer to the technologies used. Most research is around data concerned with acquisition and management, visualization, or analysis. Moreover, the observed scientific discourse closely refers to practical projects relating to specific cultural objects, technologies, or practices [87]. Both indications lead to the assumption that the observed scientific community is foremost a community of practice [89].

Fig. 4.4
A vertical bar graph with frequency count up to 250 on the y-axis and categories like Data Management, Acquisition, Analysis, and Education on the x-axis. Others has the highest count up to around 200 while the lowest is for education at around 10.

Topic areas in 3D modeling in the humanities (Online survey, n = 825 conducted in 2016) [90]

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4.4 Scholarly Culture

Does an independent epistemic culture exist apart from historiography and historical culture? That is, is digital 3D reconstruction an independent discipline? A comparison of the characteristics of scholarly fields by Armin Krishnan [84] shows that digital 3D construction has these characteristics. Counterexamples assign these characteristics to existing research fields (Table 4.1).

Table. 4.1 Characteristics of scholarly fields [84] and assessment for digital 3D reconstruction in the German-speaking area
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Due to the persistence of established disciplinary traditions, no clear demarcation or independent research field can be clearly derived for the digital 3D reconstruction, much less for the digital 3D reconstruction of historical architecture. It remains equally questionable whether it makes sense to subdivide academic disciplines, as interdisciplinary or within an existing discipline, makes sense, or creates new obstacles. The most serious obstacle that limits the development of 3D digital reconstruction is interdisciplinary (→Workflows).

The challenge is to bridge historical research tradition and information technological developments in application. This is about a discrepancy regarding the use of the 3D reconstruction. Is it a means to answer a research question, which is written down or visualized, published, and in this traditional way integrated into academic discourse? In this case, the digital 3D reconstruction would be a sub-discipline of historical sciences and its academic traditions. Or can the 3D model itself represent knowledge, in that as an information carrier it makes accessible an incalculable number of research questions and findings in a fundamentally different way than the narrative text, thereby changing the research process as a whole?

In addition to its function as a medium of communication, either internally within a project or to the specialist community, the 3D model is above all a dataset that can both be interpreted by humans in a very intuitive and location-independent way and calculated by computers. The areas of application cannot yet be fully specified, but a possible future can already be postulated.

Regarding an epistemic culture, a wide variety of research and application topics are related to 3D reconstruction, each with specific conferences, journals, and frequently contributing researchers and institutions [87]. With Nowotny et al. and De Solla Price, one could see 3D reconstruction as a mode 2 research [91,92,93] that is interdisciplinary, uses machines, and has joint intellectual property. Consequently, 3D reconstruction shares its disciplinary culture with both, engineering and the humanities [78].

Summary

This chapter gives the reader a basic understanding of the scholarly communities that deal in the broadest sense with 3D reconstructions, the opportunities and challenges involved in interdisciplinary research within these communities. It also introduces the prerequisites for working on a 3D reconstruction, explored in detail in the following chapter.

Key literature

  • Becher, T., Academic Disciplines, in Academic Tribes and Territories: Intellectual Enquiry and the Cultures of Disciplines, T. Becher, Editor. 1989, OPEN UNIVERSITY PRESS: Milton Keynes. p. 19–35 [83].

  • Krishnan, A., What are academic disciplines. Some observations on the Disciplinarity vs. Interdisciplinarity debate. 2009, Southampton: University of Southampton. National Centre for Research Methods [84].

  • Münster, S., Digital Cultural Heritage as Scholarly Field—Topics, Researchers and Perspectives from a bibliometric point of view. Journal of Computing and Cultural Heritage, 2019. 12(3): pp. 22–49 [87].