Provenance, i.e., the origin or source of something, is becoming an important concern, since it offers the means to verify data products, to infer their quality, and to decide whether they can be trusted. For instance, provenance enables the reproducibility of scientific results; provenance is necessary to track attribution and credit in curated databases; and, it is essential for reasoners to make trust judgements about the information they use over the Semantic Web. As the Web allows information sharing, discovery, aggregation, filtering and flow in an unprecedented manner, it also becomes difficult to identify the original source that produced information on the Web. This survey contends that provenance can and should reliably be tracked and exploited on the Web, and investigates the necessary foundations to achieve such a vision.

Reviews research over the past ten years on why, how, and where provenance, clarifies the relationships among these notions of provenance, and describes some of their applications in confidence computation, view maintenance and update, debugging, and annotation propagation

The term provenance is used in the art world to describe a record of the history of ownership of a piece of art. This term has been adapted by the database community to describe a record of the origin of a piece of data. Data provenance emerged as a research topic in the database community in the late 1990s. Data provenance, by explaining how the result of an operation was derived from its inputs, has proven to be a useful tool that is applicable in a wide variety of applications. This monograph gives a comprehensive introduction to data provenance concepts, algorithms, and methodology developed in the last few decades. It introduces the reader to the formalisms, algorithms, and system's developments in this fascinating field as well as providing a collection of relevant literature references for further research. The monograph provides a concise starting point for research into and using provenance in data. Although focusing on data provenance in databases pointers to work in other fields are given throughout. The intended audience is researchers and practitioners unfamiliar with the topic who want to develop a basic understanding of provenance techniques and the state-of-the-art in the field as well as researchers with prior experience in provenance that want to broaden their horizon.

The 7 revised full papers, 11 revised medium-length papers, 6 revised short, and 7 demo papers presented together with 10 poster/abstract papers describing late-breaking work were carefully reviewed and selected from numerous submissions. Provenance has been recognized to be important in a wide range of areas including databases, workflows, knowledge representation and reasoning, and digital libraries. Thus, many disciplines have proposed a wide range of provenance models, techniques, and infrastructure for encoding and using provenance. The papers investigate many facets of data provenance, process documentation, data derivation, and data annotation.

With an ever-increasing amount of information on the web, it is critical to understand the pedigree, quality, and accuracy of your data. Using provenance, you can ascertain the quality of data based on its ancestral data and derivations, track back to sources of errors, allow automatic re-enactment of derivations to update data, and provide attribution of the data source. Secure Data Provenance and Inference Control with Semantic Web supplies step-by-step instructions on how to secure the provenance of your data to make sure it is safe from inference attacks. It details the design and implementation of a policy engine for provenance of data and presents case studies that illustrate solutions in a typical distributed health care system for hospitals. Although the case studies describe solutions in the health care domain, you can easily apply the methods presented in the book to a range of other domains. The book describes the design and implementation of a policy engine for provenance and demonstrates the use of Semantic Web technologies and cloud computing technologies to enhance the scalability of solutions. It covers Semantic Web technologies for the representation and reasoning of the provenance of the data and provides a unifying framework for securing provenance that can help to address the various criteria of your information systems. Illustrating key concepts and practical techniques, the book considers cloud computing technologies that can enhance the scalability of solutions. After reading this book you will be better prepared to keep up with the on-going development of the prototypes, products, tools, and standards for secure data management, secure Semantic Web, secure web services, and secure cloud computing.

This engaging volume celebrates the life and work of Theodor Holm “Ted” Nelson, a pioneer and legendary figure from the history of early computing. Presenting contributions from world-renowned computer scientists and figures from the media industry, the book delves into hypertext, the docuverse, Xanadu and other products of Ted Nelson’s unique mind. Features: includes a cartoon and a sequence of poems created in Nelson’s honor, reflecting his wide-ranging and interdisciplinary intellect; presents peer histories, providing a sense of the milieu that resulted from Nelson’s ideas; contains personal accounts revealing what it is like to collaborate directly with Nelson; describes Nelson’s legacy from the perspective of his contemporaries from the computing world; provides a contribution from Ted Nelson himself. With a broad appeal spanning computer scientists, science historians and the general reader, this inspiring collection reveals the continuing influence of the original visionary of the World Wide Web.

The growth of electronic publishing of literature has created new challenges, such as the need for mechanisms for citing online references in ways that can assure discoverability and retrieval for many years into the future. The growth in online datasets presents related, yet more complex challenges. It depends upon the ability to reliably identify, locate, access, interpret, and verify the version, integrity, and provenance of digital datasets. Data citation standards and good practices can form the basis for increased incentives, recognition, and rewards for scientific data activities that in many cases are currently lacking in many fields of research. The rapidly-expanding universe of online digital data holds the promise of allowing peer-examination and review of conclusions or analysis based on experimental or observational data, the integration of data into new forms of scholarly publishing, and the ability for subsequent users to make new and unforeseen uses and analyses of the same data-either in isolation, or in combination with, other datasets. The problem of citing online data is complicated by the lack of established practices for referring to portions or subsets of data. There are a number of initiatives in different organizations, countries, and disciplines already underway. An important set of technical and policy approaches have already been launched by the U.S. National Information Standards Organization (NISO) and other standards bodies regarding persistent identifiers and online linking. The workshop summarized in For Attribution-Developing Data Attribution and Citation Practices and Standards: Summary of an International Workshop was organized by a steering committee under the National Research Council's (NRC's) Board on Research Data and Information, in collaboration with an international CODATA-ICSTI Task Group on Data Citation Standards and Practices. The purpose of the symposium was to examine a number of key issues related to data identification, attribution, citation, and linking to help coordinate activities in this area internationally, and to promote common practices and standards in the scientific community.

This Festschrift volume, published in honour of Peter Buneman, contains contributions written by some of his colleagues, former students, and friends. In celebration of his distinguished career a colloquium was held in Edinburgh, Scotland, 27-29 October, 2013. The articles presented herein belong to some of the many areas of Peter's research interests.

A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso

The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.