Building a Wiki resource on digital 3D reconstruction related knowledge assets

Purpose – While single theoretical approaches related to visual humanities research and in particular digital 3D reconstruction – as the virtual, interpretative 3D modeling and visualization of historical objects – are widely described in compendia like Wikipedia, and various publications discuss approaches from certain disciplinary perspectives, a comprehensive and multidisciplinary systematization is still missing. Against this background, the research activity described within this article is intended to gain a wide and multidisciplinary overview for research approaches, theories, and methods which are relevant to investigate or explain knowledge-related phenomena in the context of visual humanities research and education. Design/methodology/approach – To meet these interests we intend to set up a Wiki resource as a structured repository. The content will be based on (a) interactive workshops held at conferences to collect and structure knowledge assets on visual knowledge involving experts from different domains. Moreover, (b) a student seminar starting in early 2017 is designated to describe some typical research designs as well as amend related methods and theories in the Wiki resource based on Wikipedia articles. A content structuring principle for the Wiki resource follows the guidelines of Wikimedia as well as plans for the results to be populated again in Wikipedia. Originality/value – While Wiki approaches are frequently used in the context of visual humanities, these resources are primarily created by experts. Furthermore, Wiki-based approaches related to visualization are often focused on a certain disciplinary context as, for example, art history. A unique aspect of the described setting is to build a Wiki on digital 3D reconstruction including expertise from different knowledge domains – i.e. on perception and cognition, didactics, information sciences, as well as computing and visual humanities. Moreover, the combination of student work and assessments by experts also provides novel insights for educational research. Practical implications – The intended product is a comprehensive and multidisciplinary structured repository on digital 3D reconstruction research approaches, methods, theories, publication bodies, and good practice examples. The editing of the project results into the Wikipedia will lead to a wide dissemination and visibility of group activities and outcomes as well as enhance competencies of all contributors on collaborative work

A 4D information system for the exploration of multitemporal images and maps using photogrammetry, web technologies and VR/AR

[EN] This contribution shows the comparison, investigation, and implementation of different access strategies on multimodal data. The first part of the research is structured as a theoretical part opposing and explaining the terms of conventional access, virtual archival access, and virtual museums while additionally referencing related work. Especially, issues that still persist in repositories like the ambiguity or missing of metadata is pointed out. The second part explains the practical implementation of a workflow from a large image repository to various four-dimensional applications. Mainly, the filtering of images and in the following, the orientation of images is explained. Selection of the relevant images is partly done manually but also with the use of deep convolutional neural networks for image classification. In the following, photogrammetric methods are used for finding the relative orientation between image pairs in a projective frame. For this purpose, an adapted Structure from Motion (SfM) workflow is presented, in which the step of feature detection and matching is replaced by the Radiant-Invariant Feature Transform (RIFT) and Matching On Demand with View Synthesis (MODS). Both methods have been evaluated on a benchmark dataset and performed superior than other approaches. Subsequently, the oriented images are placed interactively and in the future automatically in a 4D browser application showing images, maps, and building models Further usage scenarios are presented in several Virtual Reality (VR) and Augmented Reality (AR) applications. The new representation of the archival data enables spatial and temporal browsing of repositories allowing the research of innovative perspectives and the uncovering of historical details.Highlights:Strategies for a completely automated workflow from image repositories to four-dimensional (4D) access approaches.The orientation of historical images using adapted and evaluated feature matching methods.4D access methods for historical images and 3D models using web technologies and Virtual Reality (VR)/Augmented Reality (AR).[ES] Esta contribución muestra la comparación, investigación e implementación de diferentes estrategias de acceso a datos multimodales. La primera parte de la investigación se estructura en una parte teórica en la que se oponen y explican los términos de acceso convencional, acceso a los archivos virtuales, y museos virtuales, a la vez que se hace referencia a trabajos relacionados. En especial, se señalan los problemas que aún persisten en los repositorios, como la ambigüedad o la falta de metadatos. La segunda parte explica la implementación práctica de un flujo de trabajo desde un gran repositorio de imágenes a varias aplicaciones en cuatro dimensiones (4D). Principalmente, se explica el filtrado de imágenes y, a continuación, la orientación de las mismas. La selección de las imágenes relevantes se hace en parte manualmente, pero también con el uso de redes neuronales convolucionales profundas para la clasificación de las imágenes. A continuación, se utilizan métodos fotogramétricos para encontrar la orientación relativa entre pares de imágenes en un marco proyectivo. Para ello, se presenta un flujo de trabajo adaptado a partir de Structure from Motion, (SfM), en el que el paso de la detección y la correspondencia de entidades es sustituido por la Transformación de entidades invariante a la radiancia (Radiant-Invariant Feature Transform, RIFT) y la Correspondencia a demanda con vistas sintéticas (Matching on Demand with View Synthesis, MODS). Ambos métodos han sido evaluados sobre la base de un conjunto de datos de referencia y funcionaron mejor que otros procedimientos. Posteriormente, las imágenes orientadas se colocan interactivamente y en el futuro automáticamente en una aplicación de navegador 4D que muestra imágenes, mapas y modelos de edificios. Otros escenarios de uso se presentan en varias aplicación es de Realidad Virtual (RV) y Realidad Aumentada (RA). La nueva representación de los datos archivados permite la navegación espacial y temporal de los repositorios, lo que permite la investigación en perspectivas innovadoras y el descubrimiento de detalles históricos.The research upon which this paper is based is part of the junior research group UrbanHistory4D’s activities which has received funding from the German Federal Ministry of Education and Research under grant agreement No 01UG1630. This work was supported by the German Federal Ministry of Education and Research (BMBF, 01IS18026BA-F) by funding the competence center for Big Data “ScaDS Dresden/Leipzig”.Maiwald, F.; Bruschke, J.; Lehmann, C.; Niebling, F. (2019). Un sistema de información 4D para la exploración de imágenes y mapas multitemporales utilizando fotogrametría, tecnologías web y VR/AR. Virtual Archaeology Review. 10(21):1-13. https://doi.org/10.4995/var.2019.11867SWORD1131021Ackerman, A., & Glekas, E. (2017). Digital Capture and Fabrication Tools for Interpretation of Historic Sites. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W2, 107-114. doi:10.5194/isprs-annals-IV-2-W2-107-2017Armingeon, M., Komani, P., Zanwar, T., Korkut, S., & Dornberger, R. (2019). A Case Study: Assessing Effectiveness of the Augmented Reality Application in Augusta Raurica Augmented Reality and Virtual Reality (pp. 99-111): Springer.Artstor. (2019). Artstor Digital Library. Retrieved April 30, 2019, from https://library.artstor.orgBay, H., Tuytelaars, T., & Van Gool, L. (2006). SURF: Speeded Up Robust Features. Paper presented at the European Conference on Computer Vision, Berlin, Heidelberg.Beaudoin, J. E., & Brady, J. E. (2011). Finding visual information: a study of image resources used by archaeologists, architects, art historians, and artists. Art Documentation: Journal of the Art Libraries Society of North America, 30(2), 24-36.Beltrami, C., Cavezzali, D., Chiabrando, F., Iaccarino Idelson, A., Patrucco, G., & Rinaudo, F. (2019). 3D Digital and Physical Reconstruction of a Collapsed Dome using SFM Techniques from Historical Images. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W11, 217-224. doi:10.5194/isprs-archives-XLII-2-W11-217-2019Bevilacqua, M. G., Caroti, G., Piemonte, A., & Ulivieri, D. (2019). Reconstruction of lost Architectural Volumes by Integration of Photogrammetry from Archive Imagery with 3-D Models of the Status Quo. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W9, 119-125. doi:10.5194/isprs-archives-XLII-2-W9-119-2019Bitelli, G., Dellapasqua, M., Girelli, V. A., Sbaraglia, S., & Tinia, M. A. (2017). Historical Photogrammetry and Terrestrial Laser Scanning for the 3d Virtual Reconstruction of Destroyed Structures: A Case Study in Italy. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-5/W1, 113-119. doi:10.5194/isprs-archives-XLII-5-W1-113-2017Bruschke, J., Niebling, F., Maiwald, F., Friedrichs, K., Wacker, M., & Latoschik, M. E. (2017). Towards browsing repositories of spatially oriented historic photographic images in 3D web environments. Paper presented at the Proceedings of the 22nd International Conference on 3D Web Technology.Bruschke, J., Niebling, F., & Wacker, M. (2018). Visualization of Orientations of Spatial Historical Photographs. Paper presented at the Eurographics Workshop on Graphics and Cultural Heritage.Bruschke, J., & Wacker, M. (2014). Application of a Graph Database and Graphical User Interface for the CIDOC CRM. Paper presented at the Access and Understanding-Networking in the Digital Era. Session J1. The 2014 annual conference of CIDOC, the International Committee for Documentation of ICOM.Burdea, G. C., & Coiffet, P. (2003). Virtual reality technology: John Wiley & Sons.Callieri, M., Cignoni, P., Corsini, M., & Scopigno, R. (2008). Masked photo blending: Mapping dense photographic data set on high-resolution sampled 3D models. Computers & Graphics, 32(4), 464-473.Chum, O., & Matas, J. (2005). Matching with PROSAC-progressive sample consensus. Paper presented at the Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on.Coordination and Support Action Virtual Multimodal Museum (ViMM). (2018). ViMM. Retrieved April 30, 2019, from https://www.vi-mm.eu/CultLab3D. (2019). CultLab3D. Retrieved April 30, 2019, from https://www.cultlab3d.deDeng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009). Imagenet: A large-scale hierarchical image database. Paper presented at the 2009 IEEE conference on computer vision and pattern recognition.Deutsches Archäologisches Institut (DAI). (2019). iDAI.objects arachne (Arachne). Retrieved April 30, 2019, from https://arachne.dainst.org/Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap: CRC press.Europeana. (2019). Europeana Collections. Retrieved 30.04.2019, from https://www.europeana.euEvens, T., & Hauttekeete, L. (2011). Challenges of digital preservation for cultural heritage institutions. Journal of Librarianship and Information Science, 43(3), 157-165.Fischler, M. A., & Bolles, R. C. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381-395.Fleming‐May, R. A., & Green, H. (2016). Digital innovations in poetry: Practices of creative writing faculty in online literary publishing. Journal of the Association for Information Science and Technology, 67(4), 859-873.Franken, T., Dellepiane, M., Ganovelli, F., Cignoni, P., Montani, C., & Scopigno, R. (2005). Minimizing user intervention in registering 2D images to 3D models. The visual computer, 21(8-10), 619-628.Girardi, G., von Schwerin, J., Richards-Rissetto, H., Remondino, F., & Agugiaro, G. (2013). The MayaArch3D project: A 3D WebGIS for analyzing ancient architecture and landscapes. Literary and Linguistic Computing, 28(4), 736-753. doi:10.1093/llc/fqt059Grussenmeyer, P., & Al Khalil, O. (2017). From Metric Image Archives to Point Cloud Reconstruction: Case Study of the Great Mosque of Aleppo in Syria. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W5, 295-301. doi:10.5194/isprs-archives-XLII-2-W5-295-2017Gutierrez, M., Vexo, F., & Thalmann, D. (2008). Stepping into virtual reality: Springer Science & Business Media.Guttentag, D. A. (2010). Virtual reality: Applications and implications for tourism. Tourism Management, 31(5), 637-651.Hartley, R., & Zisserman, A. (2003). Multiple view geometry in computer vision: Cambridge university press.Koutsoudis, A., Arnaoutoglou, F., Tsaouselis, A., Ioannakis, G., & Chamzas, C. (2015). Creating 3D Replicas of Medium-to Large-Scale Monuments for Web-Based Dissemination Within the Framework of the 3D-Icons Project. CAA2015, 971.Li, J., Hu, Q., & Ai, M. (2018). RIFT: Multi-modal Image Matching Based on Radiation-invariant Feature Transform. arXiv preprint arXiv:1804.09493.Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60(2), 91-110.Maietti, F., Di Giulio, R., Piaia, E., Medici, M., & Ferrari, F. (2018). Enhancing Heritage fruition through 3D semantic modelling and digital tools: the INCEPTION project. Paper presented at the IOP Conference Series: Materials Science and Engineering.Maiwald, F., Schneider, D., Henze, F., Münster, S., & Niebling, F. (2018). Feature Matching of Historical Images Based on Geometry of Quadrilaterals. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2, 643-650. doi:10.5194/isprs-archives-XLII-2-643-2018Maiwald, F., Vietze, T., Schneider, D., Henze, F., Münster, S., & Niebling, F. (2017). Photogrammetric analysis of historical image repositories for virtual reconstruction in the field of digital humanities. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 447.Matas, J., Chum, O., Urban, M., & Pajdla, T. (2004). Robust wide-baseline stereo from maximally stable extremal regions. Image and Vision Computing, 22(10), 761-767.Melero, F. J., Revelles, J., & Bellido, M. L. (2018). Atalaya3D: making universities' cultural heritage accessible through 3D technologies.Milgram, P., Takemura, H., Utsumi, A., & Kishino, F. (1995). Augmented reality: A class of displays on the reality-virtuality continuum. Paper presented at the Telemanipulator and telepresence technologies.Mishkin, D., Matas, J., & Perdoch, M. (2015). MODS: Fast and robust method for two-view matching. Computer Vision and Image Understanding, 141, 81-93.Moulon, P., Monasse, P., & Marlet, R. (2012). Adaptive structure from motion with a contrario model estimation. Paper presented at the Asian Conference on Computer Vision.Münster, S., Kamposiori, C., Friedrichs, K., & Kröber, C. (2018). Image libraries and their scholarly use in the field of art and architectural history. International journal on digital libraries, 19(4), 367-383.Niebling, F., Bruschke, J., & Latoschik, M. E. (2018). Browsing Spatial Photography for Dissemination of Cultural Heritage Research Results using Augmented Models.Niebling, F., Maiwald, F., Barthel, K., & Latoschik, M. E. (2017). 4D Augmented City Models, Photogrammetric Creation and Dissemination Digital Research and Education in Architectural Heritage (pp. 196-212). Cham: Springer International Publishing.Oliva, L. S., Mura, A., Betella, A., Pacheco, D., Martinez, E., & Verschure, P. (2015). Recovering the history of Bergen Belsen using an interactive 3D reconstruction in a mixed reality space the role of pre-knowledge on memory recollection. Paper presented at the 2015 Digital Heritage.Pani Paudel, D., Habed, A., Demonceaux, C., & Vasseur, P. (2015). Robust and optimal sum-of-squares-based point-to-plane registration of image sets and structured scenes. Paper presented at the Proceedings of the IEEE International Conference on Computer Vision.Ross, S., & Hedstrom, M. (2005). Preservation research and sustainable digital libraries. International journal on digital libraries, 5(4), 317-324.Schindler, G., & Dellaert, F. (2012). 4D Cities: Analyzing, Visualizing, and Interacting with Historical Urban Photo Collections. Journal of Multimedia, 7(2), 124-131.Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-cam: Visual explanations from deep networks via gradient-based localization. Paper presented at the Proceedings of the IEEE International Conference on Computer Vision.Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556.Slater, M., & Sanchez-Vives, M. V. (2016). Enhancing our lives with immersive virtual reality. Frontiers in Robotics and AI, 3, 74.Styliani, S., Fotis, L., Kostas, K., & Petros, P. (2009). Virtual museums, a survey and some issues for consideration. Journal of cultural Heritage, 10(4), 520-528.Tschirschwitz, F., Büyüksalih, G., Kersten, T., Kan, T., Enc, G., & Baskaraca, P. (2019). Virtualising an Ottoman Fortress - Laser Scanning and 3D Modelling for the Development of an Interactive, Immersive Virtual Reality Application. International archives of the photogrammetry, remote sensing and spatial information sciences, 42(2/W9).Web3D Consortium. (2019). Open Standards for Real-Time 3D Communication. Retrieved April 30, 2019, from http://www.web3d.org/Wu, C. (2013). Towards linear-time incremental structure from motion. Paper presented at the 3D Vision-3DV 2013, 2013 International conference on.Wu, Y., Ma, W., Gong, M., Su, L., & Jiao, L. (2015). A Novel Point-Matching Algorithm Based on Fast Sample Consensus for Image Registration. IEEE Geosci. Remote Sensing Lett., 12(1), 43-47.Yoon, J., & Chung, E. (2011). Understanding image needs in daily life by analyzing questions in a social Q&A site. Journal of the American Society for Information Science and Technology, 62(11), 2201-2213

Supporting Learning in Art History – Artificial Intelligence in Digital Humanities Education

In recent years and especially in the context of the coronavirus pandemic, digital distance learning increases. But for academic students, the selection of adequate learning materials for educational purposes is becoming more and more complex. This marks only one starting point where the use of artificial intelligence (AI) offers additional value. AI has a great potential to enhance and support research and education in the field of digital humanities (DH). As international organisations have just expressed their thoughts on the subject, AI is the topic par excellence and will decisively shape the future development of educational processes

Browsing and Experiencing Repositories of Spatially Oriented Historic Photographic Images

Many institutions archive historical images of architecture in urban areas and make them available to scholars and the general public through online platforms. Users can explore these often huge repositories by faceted browsing or keyword-based searching. Metadata that enable these kinds of investigations, however, are often incomplete, imprecise, or even wrong. Thus, retrieving images of interest can be a cumbersome task for users such as art and architectural historians trying to answer their research questions. Many of these images, often containing historic buildings and landscapes, can be oriented spatially using automatic methods such as “structure from motion” (SfM). Providing spatially and temporally oriented images of urban architecture, in combination with advanced searching and exploration techniques, offers new potential in supporting historians in their research. We are developing a 3D web environment useful to historians enabling them to search and access historic photographic images in a spatial context. Related projects use 2D maps, showing only a planar view of the current urban situation. In this paper, we present an approach to create interactive views of 4D city models, i.e., 3D spatial models that show changes over time, to provide a better understanding of the urban building situation regarding the photographer’s position and surroundings. A major feature of the application is to make it possible to spatially align 3D reconstruction models to photogrammetric digitized models based on historical photographs. At the same time, this mixed methods approach is used for validation of the 3D reconstructions

Novel Approaches to research and discover Urban History

Photographs and plans are an essential source for historical research (Münster, Kamposiori, Friedrichs, & Kröber, 2018) and key objects in Digital Humanities (Kwastek, 2014). Numerous digital image archives, containing vast numbers of photographs, have been set up in the context of digitization projects. These extensive repositories of image media are still difficult to search. It is not easy to identify sources relevant for research, analyze and contextualize them, or compare them with the historical original. The eHumanities research group HistStadt4D, funded by the German Federal Ministry of Education and Research (BMBF) until July 2020 consists of 14 people – including 4 post-doctoral and 5 PhD researchers. Since a focal interest is to comprehensively investigate how to enhance accessibility of large scale image repositories, researchers and research approaches originate from the humanities, geoand information technologies as well as from educational and information studies. In contrast to adjacent projects dealing primarily with large scale linked text data as the Venice Time Machine project (“The Venice Time Machine,” 2017), sources addressed by the junior group are primarily historical photographs and plans. Historical media and their contextual information are being transferred into a 4D – 3D spatial and temporal scaled - model to support research and education on urban history. Content will be made accessible in two ways; via a 4D browser and a location-dependent augmented-reality representation. The prototype database consists of about 200,000 digitized historical photographs and plans of Dresden from the Deutsche Fotothek (“Deutsche Fotothek,”)

Interaktive parallele Nachbearbeitung von Simulationsdaten auf unstrukturierten Gittern

Numerical simulations and the assessment of their results are constantly gaining importance in product design and optimization workflows in many different fields of engineering. The availability of massively parallel manycore computing resources enables simulations to be executed with accuracies posing very high requirements on the methods for interactive post-processing of the simulation results. A traditional post-processing of such large-scale simulation datasets on single workstations is often no longer possible due to the limited resources such as main memory, the low number of compute cores and the available network bandwidth to the simulation cluster. In this work, concepts and solutions are presented that enable interactive post-processing of large-scale datasets generated by fluid dynamic simulations on unstructured grids through the use of parallel manycore environments. A software architecture the parallel post-processing and visualization, as well as specific optimizations of frequently used methods for post-processing are introduced that enable the interactive use of parallel manycore resources. The implementation of the methods and algorithms is based on existing manycore devices in the form of programmable graphics hardware, which are no longer solemnly usable for computer graphics applications, but are getting increasingly interesting for general purpose computing. It will be shown, that methods for visualization of fluid simulation data such as the interactive computation of cut-surfaces or particle traces is made possible even for large-scale unstructured data. Additionally, an algorithm for the dense texture-based visualization of flow fields will be introduced that combines the presented methods for the extraction of cut-surfaces, isosurfaces and particle tracing. This algorithm for line integral convolution enables the interactive post-processing of flow fields on partitioned and distributed unstructured grids. The methods introduced in this thesis are evaluated using several large-scale simulation datasets from different fields of engineering in scientific and industrial applications.Numerische Simulationen und deren Auswertung gewinnen in Produktdesign und Produktoptimierung im ingenieurwissenschaftlichen Umfeld stetig an Bedeutung. Durch die Verfügbarkeit massiv paralleler Manycore Rechenressourcen werden diese Simulationen in einer Genauigkeit ermöglicht, welche sehr hohe Anforderungen an die Methoden der interaktiven Nachbearbeitung der jeweiligen Ergebnisse stellt. So ist wegen des hohen Datenaufkommens oft eine herkömmliche Nachbearbeitung auf einzelnen Workstations, aufgrund der dort vorhandenen Ressourcen wie Speichermenge, Anzahl an Prozessorkernen sowie der verfügbaren Netzwerkbandbreite zum Simulationscluster, nicht mehr möglich. In dieser Arbeit werden Konzepte und Lösungen vorgestellt, mit denen eine interaktive Nachbearbeitung großer Datenmengen aus Strömungssimulationen auf unstrukturierten Gittern durch den Einsatz paralleler Manycore Rechenressourcen ermöglicht wird. Hierbei wird sowohl eine Softwarearchitektur für die parallele Nachbearbeitung und Visualisierung vorgestellt, als auch konkrete Optimierungen häufig genutzter Methoden der Nachbearbeitung für den interaktiven Einsatz in parallelen Manycore Umgebungen beschrieben. Für die Implementierung und Evaluation der verwendeten Methoden und Algorithmen kommt programmierbare Graphikhardware, die nicht mehr ausschließlich für computergraphische Anwendungen, sondern zunehmend auch für generelle Berechnungen eingesetzt wird, als aktuell verfügbare parallele Manycore Ressource zum Einsatz. Es wird gezeigt, dass durch die Verwendung paralleler Graphikhardware Auswertungsmethoden für Strömungssimulationsdaten, wie die Berechnung von Schnitten und Partikelbahnen, auch für sehr große Datensätze auf unstrukturierten Gittern mit interaktivem Antwortzeitverhalten ausgeführt werden können. Außerdem wird ein Verfahren für die texturbasierte Visualisierung von Strömungsfeldern vorgestellt, welches die gezeigten Verfahren zur Schnitt- und Partikelberechnung kombiniert. Dieses Verfahren zur Linienintegralfaltung ermöglicht erstmalig eine interaktive Nachbearbeitung auf verteilten unstrukturierten Gittern. Die Evaluierung der vorgestellten Verfahren erfolgt mittels der Nachbearbeitung großer Simulationsdatensätze aus Forschnung und industrieller Nutzung in verschiedenen ingenieurwissenschaftlichen Anwendungsgebieten

Building a Wiki resource on digital 3D reconstruction related knowledge assets

Purpose – While single theoretical approaches related to visual humanities research and in particular digital 3D reconstruction – as the virtual, interpretative 3D modeling and visualization of historical objects – are widely described in compendia like Wikipedia, and various publications discuss approaches from certain disciplinary perspectives, a comprehensive and multidisciplinary systematization is still missing. Against this background, the research activity described within this article is intended to gain a wide and multidisciplinary overview for research approaches, theories, and methods which are relevant to investigate or explain knowledge-related phenomena in the context of visual humanities research and education. Design/methodology/approach – To meet these interests we intend to set up a Wiki resource as a structured repository. The content will be based on (a) interactive workshops held at conferences to collect and structure knowledge assets on visual knowledge involving experts from different domains. Moreover, (b) a student seminar starting in early 2017 is designated to describe some typical research designs as well as amend related methods and theories in the Wiki resource based on Wikipedia articles. A content structuring principle for the Wiki resource follows the guidelines of Wikimedia as well as plans for the results to be populated again in Wikipedia. Originality/value – While Wiki approaches are frequently used in the context of visual humanities, these resources are primarily created by experts. Furthermore, Wiki-based approaches related to visualization are often focused on a certain disciplinary context as, for example, art history. A unique aspect of the described setting is to build a Wiki on digital 3D reconstruction including expertise from different knowledge domains – i.e. on perception and cognition, didactics, information sciences, as well as computing and visual humanities. Moreover, the combination of student work and assessments by experts also provides novel insights for educational research. Practical implications – The intended product is a comprehensive and multidisciplinary structured repository on digital 3D reconstruction research approaches, methods, theories, publication bodies, and good practice examples. The editing of the project results into the Wikipedia will lead to a wide dissemination and visibility of group activities and outcomes as well as enhance competencies of all contributors on collaborative work