This volume contains editions of 35 texts, which have been excavated nearly 100 years ago in the ancient Egyptian village of Karanis, and which were still waiting publication. As all texts written on papyrus from the Egyptian countryside, these texts give a new insight into the life of the people who dwelled in a typical village of the Roman period in Egypt. The texts show the cultural diversity of those who cohabitated, whether they had Greek or Egyptian names, whether their main gods were the crocodiles or Zeus. In the lives of all of them tax-paying played an important role, as well as caring for their cattle and fields, doing business, and fullfilling the obligations of the Roman government. In particular interesting is the personage of Socrates the tax-collector. Since the ruins of Karanis are still standing (and worth a visit) with two nearly intact temples from the period of the texts, a more complete image of village life emerges from texts and the archaeology behind them. Papyrologists welcome every newly published text as a further stone of the mosaic image that they try to create of the past.

This volume of Papyri contains a selection of 25 pieces which were excavated in the village of Karanis in the north-eastern Fayum (Egypt) by American archaeologists between 1924 and 1926. Many of the texts published here come from the archive of a well known figure in the village life of Karanis in the 2nd century AD: Socrates, son of Sarapion, was a tax collector here for many years, serving the Roman Empire collecting taxes due in money and in kind. Besides his successful economic activities - Socrates certainly belonged to the upper stratum of society in Karanis - the tax collector was a lover of Greek literature; for sure, he did not venture into high philosophy and the like, but he read Homer, comedies, and tried to be up to date about mythology in plays. Half of the new texts published here are literary, mostly from Socrates' library; other texts were found in the immediate neighbourhood of where Socrates lived, such as a surgical treatise about remedies of shoulder dislocations, which perhaps belonged to a doctor. The other half of the papyrus texts in this volume are documents that can shed new light on the activities of the tax collector, or of other inhabitants of Karanis. Altogether they give us a vivid picture of village life in Graeco/Roman Egypt in the 2nd century AD.

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book's second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book's second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures. This book presents innovative solutions in offline data mining and real-time analysis of sensor or geographically distributed data. It discusses the challenges and requirements for sensor data based knowledge discovery solutions in high-priority application illustrated with case studies. It explores the fusion between heterogeneous data streams from multiple sensor types and applications in science, engineering, and security.