This text reviews the theory, concepts, and basic methods involved in archaeological analysis with the aim of familiarizing both students and professionals with its underlying principles. Topics covered include the nature and presentation of data; database and research design; sampling and quantification; analyzing lithics, pottery, faunal, and botanical remains; interpreting dates; and archaeological illustration. A glossary of key terms completes the book.

This book aims to give archaeologists a non-technical but thorough grounding in the use of computers.

3D Data Acquisition for Bioarchaeology, Forensic Anthropology, and Archaeology serves as a handbook for the collection and processing of 3-D scanned data and as a tool for scholars interested in pursuing research projects with 3-D models. The book's chapters enhance the reader's understanding of the technology by covering virtual model processing protocols, alignment methods, actual data acquisition techniques, basic technological protocols, and considerations of variation in research design associated with biological anthropology and archaeology. - Thoroughly guides the reader through the "how-to on different stages of 3D-data-related research - Provides statistical analysis options for 3D image data - Covers protocols, methods and techniques as associated with biological anthropology and archaeology

The advent of Big Data is a recent and debated issue in Digital Archaeology. Papers consider the historiographic context and current developments, as well as comprehensive examples of a multidisciplinary and integrative approach to the recording, management and exploitation of excavation data and documents produced over a long period of research.

If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie's account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.

This second edition of the classic textbook, The Archaeologist’s Laboratory, is a substantially revised work that offers updated information on the archaeological work that follows fieldwork, such as the processing and analysis of artifacts and other evidence. An overarching theme of this edition is the quality and validity of archaeological arguments and the data we use to support them. The book introduces many of the laboratory activities that archaeologists carry out and the ways we can present research results, including graphs and artifact illustrations. Part I introduces general topics concerning measurement error, data quality, research design, typology, probability and databases. It also includes data presentation, basic artifact conservation, and laboratory safety. Part II offers brief surveys of the analysis of lithics and ground stone, pottery, metal artifacts, bone and shell artifacts, animal and plant remains, and sediments, as well as dating by stratigraphy, seriation and chronometric methods. It concludes with a chapter on archaeological illustration and publication. A new feature of the book is illustration of concepts through case studies from around the world and from the Palaeolithic to historical archaeology.The text is appropriate for senior undergraduate students and will also serve as a useful reference for graduate students and professional archaeologists.

This book provides a state-of-the art overview of satellite archaeology and it is an invaluable volume for archaeologists, scientists, and managers interested in using satellite Earth Observation (EO) to improve the traditional approach for archaeological investigation, protection and management of Cultural Heritage. The recent increasing development of EO techniques and the tremendous advances in Information and Communication Technologies (ICT) have resulted primarily in Cultural Heritage applications. The book focuses on new challenging prospects for the use of EO in archaeology not only for probing the subsurface to unveil sites and artifacts, but also for the management and valorization as well as for the monitoring and preservation of cultural resources. The book provides a first-class understanding of this revolutionary scenario which was unthinkable several years ago. The book offers: (i) an excellent collection of outstanding articles focusing on satellite data processing, analysis and interpretation for archaeological applications, (ii) impressive case studies, (iii) striking examples of the high potential of the integration of multi-temporal, multi-scale, multi-sensors techniques. Each chapter is composed as an authoritative contribution to help the reader grasp the value of its content. The authors are renowned experts from the international scientific community. Audience: This book will be of interest to scientists in remote sensing applied to archeology, geoarcheology, paleo-environment, paleo-climate and cultural heritage.

Provides analytical theories offered by innovative artificial intelligence computing methods in the archaeological domain.

In the decade since its publication, the first edition of Statistics for Archaeologists has become a staple in the classroom. Taking a jargon-free approach, this teaching tool introduces the basic principles of statistics to archaeologists. The author covers the necessary techniques for analyzing data collected in the field and laboratory as well as for evaluating the significance of the relationships between variables. In addition, chapters discuss the special concerns of working with samples. This well-illustrated guide features several practice problems making it an ideal text for students in archaeology and anthropology. Using feedback from students and teachers who have been using the first edition, as well as another ten years of personal experience with the text, the author has provided an updated and revised second edition with a number of important changes. New topics covered include: -Proportions and Densities -Error Ranges for Medians -Resampling Approaches -Residuals from Regression -Point Sampling -Multivariate Analysis -Similarity Measures -Multidimensional Scaling -Principal Components Analysis -Cluster Analysis Those already familiar with the clear and useful format of Statistics for Archaeologists will find this new edition a welcome update, and the new sections will make this seminal textbook an indispensible resource for a whole new group of students, professors, and practitioners.

Airborne Laser Scanning (ALS), or lidar, is an enormously important innovation for data collection and interpretation in archaeology. The application of archaeological 3D data deriving from sources including ALS, close-range photogrammetry and terrestrial and photogrammetric scanners has grown exponentially over the last decade. Such data present numerous possibilities and challenges, from ensuring that applications remain archaeologically relevant, to developing practices that integrate the manipulation and interrogation of complex digital datasets with the skills of archaeological observation and interpretation. This volume addresses the implications of multi-scaled topographic data for contemporary archaeological practice in a rapidly developing field, drawing on examples of ongoing projects and reflections on best practice. Twenty papers from across Europe explore the implications of these digital 3D datasets for the recording and interpretation of archaeological topography, whether at the landscape, site or artifact scale. The papers illustrate the variety of ways in which we engage with archaeological topography through 3D data, from discussions of its role in landscape archaeology, to issues of context and integration, and to the methodological challenges of processing, visualization and manipulation. Critical reflection on developing practice and implications for cultural resource management and research contextualize the case studies and applications, illustrating the diverse and evolving roles played by multi-scalar topographic data in contemporary archaeology.