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The image of the archaeologist is changing; there is little we can do about that. The dusty boots, timeworn trowel, and coffee-stained notebooks may themselves become the images that we see in museums in a not too distant future. One only has to open up any archaeology publication today to find stunning images of drones, tablets, GPSs, laser scanners and a myriad of many other devices that were hardly thought of a decade or two ago (For example, see: Levy 2013; Levy, et al. 2010). The rapid evolution of technology has meant that there are new approaches to field archaeology that can enhance our work, help to preserve the past from our rather destructive discipline, and also help to disseminate our research to the public. Among all these tools, perhaps in the shadow of drones and laser scanners, is the archaeologist's notebook. That notebook, containing the primary observations for excavations is fundamental to understanding work conducted in any trench at any site; and like many of the other facets of archaeology, is also going through a process of change from analog to digital. In this article, we will look at one such tool, OpenDig, developed in the midst of many of these changes occurring all around us. OpenDig should be understood in the context of the circumstances out of which it grew, the problems which it was created to solve, and as a result can be of use to other archaeologists today.

The combination of 3D acquisition (terrestrial and airborne LiDAR, structured light, structure-from-motion) and 2D imaging (photographic, multispectral, panoramic, orthorectified, reflectance transformation) techniques allows the geometry, appearance and other aspects of culturally significant sites to be objectively documented. Traditionally, these data are usually transformed into models such as 3D textured meshes before they are visualized or analyzed—an often time- and effortintensive process. We propose a system for the direct visualization and analysis of such data, allowing the different aspects recorded to be layered together, and covisualized with annotations and other relevant information. We describe the required technical foundations, including gigapoint and gigapixel visualization pipelines that enable the dynamic layering of high-resolution imagery over massive minimally-processed LiDAR point clouds that serve as the base spatial layer. In particular, we introduce the pointbuffer—a GPU-resident view-dependent point cache—as the foundation of our gigapoint pipeline, and outline the use of virtual texturing for draping of gigapixel imagery onto point clouds. Finally, we present case studies from sites in Jordan and Italy.

Archaeological data is perfectly suited to 3D modeling and visualization. The geographical remoteness of many heritage sites means that few will ever be able to experience them firsthand. For centuries, practitioners of archaeology have meticulously drafted maps and illustrations, and captured photographs of sites and landscapes (Sanders 2014). Two-dimensional maps and photos reflect scale but never fully embody it. Hence, one of the goals of virtual reality modeling is to take another step toward bridging this gap. This article presents a variety of ways archaeologists, working closely with colleagues from computer science, visual arts, and engineering, have worked toward disseminating archaeological datasets to professionals and non-professional audiences alike through virtual reality.

Data recording is one of the primary requirements of any archaeological project. Some projects rely on the traditional pen-and-paper methods, while others have begun to employ field data recording applications through mobile computing platforms. The former method relies on later transcription of the data, while the later passes over this step, integrating the data from various devices at some later point. Many rely on commercial solutions to solve their data recording needs. Well-known platforms, which have had a long and successful track record with databases, are now being employed for archaeological databases. Although these robust platforms provide straightforward solutions, they are expensive and not easily extensible. OpenDig was developed with a focus on open source frameworks, with the idea that future expansion would be important for any archaeological database. By utilizing open source tools that were born in the World Wide Web, OpenDig provides a complete framework for archaeological data from the field and post-excavation studies. The three main tools that make up the OpenDig framework are: 1) a field recording application for describing archaeological contexts, associated photos, geospatial data, and find; 2) a lightweight data reader and editor for deployment in field laboratories; 3) a full web application for a more complete tool set for reviewing, analysing and disseminating these data acquired from the field. Three tools, on their own, may not seem very different from other solutions available to archaeologists today. However, OpenDig demonstrates the viability of using open source tools and open source data to create a complete system for data recording, analysis and dissemination. The future of archaeological data lays in finding ways to link disparate data sets from various projects and being able to make sensible comparisons. This can only be achieved by providing open access to these data and creating common interfaces that allow archaeologists to link their data with others.

The development of three-dimensional documentation technologies such as LiDAR and Structure from Motion (essentially digital photogrammetry) has led to a recording revolution, as these methods are increasingly applied to field archaeology. 3D methods have the potential to become an integral part of the archaeological toolkit, as they have the capability to produce spatially-referenced outputs, such as orthophotos and digital elevation models (DEMs), with greater efficiency than traditional methods. The combination of Structure from Motion and low-altitude aerial photography can facilitate the production of these GIS outputs, which can then be used for digitization or as basemaps. These methods allow for accurate and precise recording with a relative minimum of field time. As the existing body of 3D data increases in size, museums have the unique opportunity to be able to take advantage of these datasets to update their exhibits and display archaeological context and the process of excavation through visualizations of 3D models. The spread of 3D documentation and recording in archaeology may provide a unique opportunity for collaboration between these two professions, and allow for archaeology to improve its public outreach. The methodology presented here is based on field research in Jordan.

Archaeology as a discipline has always faced an ironic challenge. In order to improve our understanding of the past, it is nearly always necessary to destroy the source of knowledge as material remains left by past people are removed from their context. Archaeologists have long understood the responsibility this paradox confers on them-the imperative to record in great detail that which they demolish through excavation so that others may reinterpret their results (Wheeler 1954). The duty of documentation for the purpose of preserving dovetails with efforts toward recording for the excavators' own interpretation of the evidence uncovered. Traditionally, this process has occurred in notebooks through detailed descriptions of archaeological contexts, along with photographic and hand-drawn depictions of excavation. These methods, while tried-and-true, suffer from collection biases, omissions, and an inability to record in three dimensions. In a perfect world, archaeologists would be able to record the conditions of excavation in such a way that future researchers would be able to experience the site exactly as it appeared as it was excavated. Exclusively two-dimensional descriptions of the three-dimensional world falls short of this ideal, especially in a field of study that relies so fundamentally on interpretation of spatial relationships, both horizontal and vertical. Omissions in recording caused by collection biases are equally unacceptable. As archaeologists today bemoan the poor recording standards of 100 years ago, we can assume that the archaeologists of the future will find fault with our work today in a similar way. Traditional methods no longer appropriately fulfill the archaeologist's responsibility for extensive documentation with all practical and available means. How then can we remedy this issue and strive for a more comprehensive documentation program in which datasets more closely reflect conditions in the field during excavation? 3D recording may provide an answer to this critical question, while also providing a mechanism to upgrade traditional techniques.

Cyber-archaeology represents the marriage of archaeology, computer science, engineering, and the natural sciences with the aim of taking advantage of constantly evolving technologies for digital data capture, curation, analyses and dissemination. Digital data collection tools are perhaps the most rapidly changing arenas of development in cyber-archaeology and are becoming affordable tools for every archaeologist. In this paper, we examine two users’ approaches to produce point cloud models of archaeological sites using structure from motion (SfM) photography. The experiment took place at the Fountain of Peirene in ancient Corinth, Greece. Their implementation of the technology and their results are compared to highlight the very important role the photo-shooting session can play in the final outcome of the SfM reconstruction. We correlate the users’ approaches to the applied algorithms’ robust features and known limitations to provide a technical explanation of how archaeologists can significantly improve their success in SfM. As new algorithms and software emerge making SfM a common tool in archaeological documentation the methodology presented in this paper will enable archaeologists to meet the high demand for digital documentation on a global scale.

The broad adoption of diagnostic and analytical techniques in the field of archeology, presents a unique opportunity for e-Science in the form of scientific explanation, drawing from methodologies aimed at recording, archiving, analyzing, and disseminating, rich data collections to create the needed infrastructure for both research and web-based curation and data management system. This paper presents a needed stepping stone towards synergy between information technology and archeology, by introducing a data acquisition, tagging and characterization pipeline along with a novel method for spatially querying archeological data. © 2012 Elsevier B.V. All rights reserved.

LiDAR and photogrammetry are common mechanisms for the documentation of cultural heritage sites. Their outputs provide foundational primary sources for research and important engineering decisions contributing to the on-going conservation of sites and structures. Unfortunately, due to the complex nature of these data, they are rarely shared with stakeholders in their full forms. Raw data is routinely transferred to portable hard drives and forgotten at a project's end. Digital heritage documentation, often acquired with great effort and cost, is at risk of loss (UNESCO 2003). When these data are shared, they are rarely presented or formatted in ways which enable their widespread re-use. As processing tools improve at a rapid pace, and offer new pipelines for improved reconstruction and fusion with additional data sources, it is important to preserve the data in a way which maintains all functionality and interoperability between processing platforms. It's not enough to share data or to simply make them "available." Data must be technologically and intellectually intelligible (and useful). A new system framework is required to ensure their integrity and wide-spread utility, and to democratize these data for re-use by the diverse communities of stakeholders with whose purposes fall outside the narrow scopes of a 3D documentation project's original goals. In this paper we present OpenHeritage3D.org as a platform and framework for an open visual archive seeking to provide authoritative and democratized access to site-scale lidar and photogrammetry through data curation, file-sharing, and web-visualization systems with granular segmentation and data conversion capabilities. [ABSTRACT FROM AUTHOR]

Creating cave maps is an essential part of cave research. Traditional cartographic efforts are extremely time consuming and subjective, motivating the development of new techniques using terrestrial lidar scanners and mobile lidar systems. However, processing the large point clouds from these scanners to produce detailed, yet manageable "maps" remains a challenge. In this work, we present a methodology for synthesizing a basemap representing the cave floor from large scale point clouds, based on a case study of a SLAM-based lidar data acquisition from a cave system in the archaeological site of Las Cuevas, Belize. In 4 days of fieldwork, the 335 m length of the cave system was scanned, resulting in a point cloud of 4.1 billion points, with 1.6 billion points classified as part of the cave floor. This point cloud was processed to produce a basemap that can be used in GIS, where natural and anthropogenic features are clearly visible and can be traced to create accurate 2D maps similar to traditional cartography. [ABSTRACT FROM AUTHOR]

Traditional sensors, such as accelerometers and displacement transducers, are widely used in laboratory and field experiments in earthquake engineering to measure the motions of both structural and nonstructural components. Such sensors, however, must be physically attached to the structure and require cumbersome cabling and configurations and substantial time for setup. For reduced-scale experiments, these conventional sensors may substantially alter the dynamic properties of the system by changing the mass, stiffness, and damping properties of the specimen. Moreover, it is very difficult with traditional sensors to capture the three-dimensional motions of light or oddly shaped components such as microscopes, computers, or other building contents. In this paper, the methodology of light-based motion tracking is applied to the measurement of the three-dimensional motions of various types of equipment and building contents commonly found in biological and chemical science laboratories. The system is comprised of six high-speed, high-resolution charge-coupled-device (CCD) cameras outfitted with a cluster of red-light emitting diodes (LEDs). Retroreflective (passive) spherical markers discretely located in a scene are tracked in time and used to describe the behavior of various types of equipment and contents subjected to a range of earthquake motions. Results from this study show that the nonintrusive, light-based approach is extremely promising in terms of its ability to capture relative displacements in three orthogonal directions and complementary rotations. CE Database subject headings: Tracking; Digital techniques; Earthquakes; Ground motion; Shake table tests.