Data Provenance
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Data Provenance
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Author : Boris Glavic
language : en
Publisher:
Release Date : 2021
Data Provenance written by Boris Glavic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Database management categories.
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.
Data Provenance And Data Management In Escience
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Author : Qing Liu
language : en
Publisher: Springer
Release Date : 2012-08-04
Data Provenance And Data Management In Escience written by Qing Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-04 with Technology & Engineering categories.
This book covers important aspects of fundamental research in data provenance and data management(DPDM), including provenance representation and querying, as well as practical applications in such domains as clinical trials, bioinformatics and radio astronomy.
Provenance In Data Science
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Author : Leslie F. Sikos
language : en
Publisher: Springer Nature
Release Date : 2021-04-26
Provenance In Data Science written by Leslie F. Sikos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-26 with Computers categories.
RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Secure Data Provenance And Inference Control With Semantic Web
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Author : Bhavani Thuraisingham
language : en
Publisher: CRC Press
Release Date : 2014-08-01
Secure Data Provenance And Inference Control With Semantic Web written by Bhavani Thuraisingham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-01 with Computers categories.
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.
Provenance In Databases
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Author : James Cheney
language : en
Publisher: Now Publishers Inc
Release Date : 2009-06-02
Provenance In Databases written by James Cheney and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-02 with Computers categories.
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
A Framework For Managing Big Data Provenance
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Author :
language : en
Publisher:
Release Date : 2015
A Framework For Managing Big Data Provenance written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Big data categories.
Provenance is a key metadata which contains information about how, when, and where a data product was derived from. Data provenance is used for describing data evolution, which records the whole data process, including input, output and transformation in scientific workflow. Making systems provenance-aware can greatly benefit all parties involved. In today's business environment, applications generate massive amounts of data at various levels of granularity. During execution of business processes, a number of issues may occur, e.g., system failures, process failures, service failures, or human errors, that can result in the processes not executing as expected, and as a result not adhering to the required compliance concerns. Business Provenance is an emerging concept which gives the flexibility to capture information required to address a specific compliance or performance goal. Big Data is a term which is commonly used to describe data that exceeds the processing capacity of conventional database systems, and we often use four V's (Volume, Variety, Velocity, and Value) to describe its characteristics. While much work has focused on capturing and modelling provenance data, little work has focused on how to manage massive amount of provenance data. The challenges of managing large amounts of big data provenance involve indexing, storing, classifying, and querying large number of provenance trees. This dissertation discusses the importance of data provenance and presents a framework to model and manage data provenance. We present a design for our proposed framework along with a prototype implementation. The research addresses challenges for managing large amounts of provenance information serialized as XML trees that have small average depth, and describe a scalable framework that can support the vast volumes of data and maintain a balance in the four V's: Volume, Velocity, Variety and Veracity.
Data Provenance A Complete Guide 2020 Edition
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Author : Gerardus Blokdyk
language : en
Publisher: 5starcooks
Release Date : 2019-11-17
Data Provenance A Complete Guide 2020 Edition written by Gerardus Blokdyk and has been published by 5starcooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-17 with categories.
Do you all define Data Provenance in the same way? Are the Data Provenance requirements complete? How do you manage Data Provenance Knowledge Management (KM)? What are the core elements of the Data Provenance business case? Who is the Data Provenance process owner? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Provenance investments work better. This Data Provenance All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data Provenance Self-Assessment. Featuring 945 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Provenance improvements can be made. In using the questions you will be better able to: - diagnose Data Provenance projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data Provenance and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data Provenance Scorecard, you will develop a clear picture of which Data Provenance areas need attention. Your purchase includes access details to the Data Provenance self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Provenance Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Provenance And Annotation Of Data And Processes
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Author : Bertram Ludäscher
language : en
Publisher: Springer
Release Date : 2015-03-20
Provenance And Annotation Of Data And Processes written by Bertram Ludäscher and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-20 with Computers categories.
This book constitutes the revised selected papers of the 5th International Provenance and Annotation Workshop, IPAW 2014, held in Cologne, Germany in June 2014. The 14 long papers, 20 short papers and 4 extended abstracts presented were carefully reviewed and selected from 53 submissions. The papers include tools that enable provenance capture from software compilers, from web publications and from scripts, using existing audit logs and employing both static and dynamic instrumentation.
Provenance And Annotation Of Data And Processes
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Author : Juliana Freire
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-02
Provenance And Annotation Of Data And Processes written by Juliana Freire and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-02 with Business & Economics categories.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Provenance and Annotation Workshop, IPAW 2008, held in Salt Lake City, UT, USA, in June 2007. The 14 revised full papers and 15 revised short and demo papers presented together with 2 keynote lectures were carefully reviewed and selected from 40 submissions. The paper are organized in topical sections on provenance: models and querying; provenance: visualization, failures, identity; provenance and workflows; provenance for streams and collaboration; and applications.
Data Provenance
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Author : Boris Glavic
language : en
Publisher:
Release Date : 2021-04-26
Data Provenance written by Boris Glavic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-26 with categories.
This book gives a comprehensive introduction to data provenance concepts, algorithms, and methodology developed in the last few decades.