3D and 4D Simulations for Landscape Reconstruction and Damage Scenarios. GIS Pilot Applications

The project 3D and 4D Simulations for Landscape Reconstruction and Damage Scenarios: GIS Pilot Applications has been devised with the intention to deal with the demand for research, innovation and applicative methodology on the part of the international programme, requiring concrete results to increase the capacity to know, anticipate and respond to a natural disaster. This project therefore sets out to develop an experimental methodology, a wide geodatabase, a connected performant GIS platform and multifunctional scenarios able to profitably relate the added values deriving from different geotechnologies, aimed at a series of crucial steps regarding landscape reconstruction, event simulation, damage evaluation, emergency management, multi-temporal analysis. The Vesuvius area has been chosen for the pilot application owing to such an impressive number of people and buildings subject to volcanic risk that one could speak in terms of a possible national disaster. The steps of the project move around the following core elements: creation of models that reproduce the territorial and anthropic structure of the past periods, and reconstruction of the urbanized area, with temporal distinctions; three-dimensional representation of the Vesuvius area in terms of infrastructuralresidential aspects; GIS simulation of the expected event; first examination of the healthcareepidemiological consequences; educational proposals. This paper represents a proactive contribution which describes the aims of the project, the steps which constitute a set of specific procedures for the methodology which we are experimenting, and some thoughts regarding the geodatabase useful to “package” illustrative elaborations. Since the involvement of the population and adequate hazard preparedness are very important aspects, some educational and communicational considerations are presented in connection with the use of geotechnologies to promote the knowledge of risk

A web information system for the management and the dissemination of Cultural Heritage data.

Safeguarding and exploiting Cultural Heritage induce the production of numerous and heterogeneous data. The management of these data is an essential task for the use and the diffusion of the information gathered on the field. Previously, the data handling was a hand-made task done thanks to efficient and experienced methods. Until the growth of computer science, other methods have been carried out for the digital preservation and treatment of Cultural Heritage information. The development of computerized data management systems to store and make use of archaeological datasets is then a significant task nowadays. Especially for sites that have been excavated and worked without computerized means, it is now necessary to put all the data produced onto computer. This allows preservation of the information digitally (in addition with the paper documents) and offers new exploitation possibilities, like the immediate connection of different kinds of data for analyses, or the digital documentation of the site for its improvement. Geographical Information Systems have proved their potentialities in this scope, but they are not always adapted to the management of features at the scale of a particular archaeological site. Therefore this paper aims to present the development of a Virtual Research Environment dedicated to the exploitation of intra-site Cultural Heritage data. The Information System produced is based on open-source software modules dedicated to the Internet, so users can avoid being software driven and can register and consult data from different computers. The system gives the opportunity to do exploratory analyses of the data, especially at spatial and temporal levels. The system is compliant to every kind of Cultural Heritage site and allows management of diverse types of data. Some experimentation has been done on sites managed by the Service of the National Sites and Monuments of Luxembourg

Quantitative Perspectives on Fifty Years of the Journal of the History of Biology

Journal of the History of Biology provides a fifty-year long record for examining the evolution of the history of biology as a scholarly discipline. In this paper, we present a new dataset and preliminary quantitative analysis of the thematic content of JHB from the perspectives of geography, organisms, and thematic fields. The geographic diversity of authors whose work appears in JHB has increased steadily since 1968, but the geographic coverage of the content of JHB articles remains strongly lopsided toward the United States, United Kingdom, and western Europe and has diversified much less dramatically over time. The taxonomic diversity of organisms discussed in JHB increased steadily between 1968 and the late 1990s but declined in later years, mirroring broader patterns of diversification previously reported in the biomedical research literature. Finally, we used a combination of topic modeling and nonlinear dimensionality reduction techniques to develop a model of multi-article fields within JHB. We found evidence for directional changes in the representation of fields on multiple scales. The diversity of JHB with regard to the representation of thematic fields has increased overall, with most of that diversification occurring in recent years. Drawing on the dataset generated in the course of this analysis, as well as web services in the emerging digital history and philosophy of science ecosystem, we have developed an interactive web platform for exploring the content of JHB, and we provide a brief overview of the platform in this article. As a whole, the data and analyses presented here provide a starting-place for further critical reflection on the evolution of the history of biology over the past half-century.Comment: 45 pages, 14 figures, 4 table

Integration of Heterogeneous Cultural Heritage Data in a Web-based <br />Information System: A Case Study from Vianden Castle, Luxembourg

ISBN 978-963-8046-90-1International audienceThe project presented here proposes the first implementation of a Web-based Information System for the conservation, handling, and use of site data. The case study is the castle of Vianden in Luxembourg, on which considerable archaeological data have accumulated over the years. There is a recognized need in archaeology for a tool that will allow for fast, effective, and flexible exploratory analysis of data, especially at spatial and temporal levels. We have developed such an Information System with maximal portability by using Extensible Markup Language (XML) and Extensible Stylesheet Language (XSL) for data exchange. Our system consists of several interfaces permitting different types of access to heterogeneous information. We propose a description of the data in textual interfaces along with images, and dynamic links to this data through interactive 2D and 3D representations. The 2D images, photos, or vectors are generated in Scalable Vector Graphics (SVG), while 3D models are generated in X3

On the Use of XML in Medical Imaging Web-Based Applications

The rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the Extensible Markup Language (XML) language in web-based applications that aid in diagnosis or treatment of patients, considering how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applicationsPeer ReviewedPostprint (author's final draft

Web 2.0 and destination marketing: current trends and future directions

Over the last decade, destination marketers and Destination Marketing Organizations (DMOs) have increasingly invested in Web 2.0 technologies as a cost-effective means of promoting destinations online, in the face of drastic marketing budgets cuts. Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing

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

Infrastructures for digital research: new opportunities and challenges

No abstract available