Provenance In Data Science
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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.
Encyclopedia Of Big Data
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Author :
language : en
Publisher:
Release Date : 19??
Encyclopedia Of Big Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 19?? with categories.
Principles Of Data Integration
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Author : AnHai Doan
language : en
Publisher: Elsevier
Release Date : 2012-06-25
Principles Of Data Integration written by AnHai Doan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-25 with Computers categories.
Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels. - Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand - Enables you to build your own algorithms and implement your own data integration applications
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
Advances In Machine Learning And Data Science
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Author : Damodar Reddy Edla
language : en
Publisher: Springer
Release Date : 2018-05-16
Advances In Machine Learning And Data Science written by Damodar Reddy Edla and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-16 with Technology & Engineering categories.
The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.
Secure Data Management
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Author : Willem Jonker
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-11
Secure Data Management written by Willem Jonker 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 2008-08-11 with Business & Economics categories.
This book constitutes the refereed proceedings of the Fifth VLDB Workshop on Secure Data Management, SDM 2008, held in Auckland, New Zealand, on August 24, 2008, in conjunction with VLDB 2008. The 11 full papers were selected for publication in the book from 32 submissions. In addition, 3 position papers and a keynote paper are included. The papers are organized in topical sections on database security, trust management, privacy protection, and security and privacy in healthcare.
Multi Domain Master Data Management
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Author : Mark Allen
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-03-21
Multi Domain Master Data Management written by Mark Allen and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-21 with Computers categories.
Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. - Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. - Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. - Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data.
Foundations Of Data Science
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Author : Dr. Talluri Sunil Kumar, Dr. Radhika Pathi, Mr. Venu Aluri, K. Balasubramanian
language : en
Publisher: RK Publication
Release Date : 2025-05-02
Foundations Of Data Science written by Dr. Talluri Sunil Kumar, Dr. Radhika Pathi, Mr. Venu Aluri, K. Balasubramanian and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.
Foundations of Data Science offers a comprehensive introduction to data analysis, statistical modeling, machine learning, and computational techniques. Designed for students and professionals, it blends theory with practical applications, emphasizing critical thinking and data-driven decision-making across disciplines. The book equips readers to solve real-world problems using modern data science tools.
Ethical Practice Of Statistics And Data Science
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Author : Rochelle Tractenberg
language : en
Publisher: Ethics International Press
Release Date : 2023-11-25
Ethical Practice Of Statistics And Data Science written by Rochelle Tractenberg and has been published by Ethics International Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Language Arts & Disciplines categories.
Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, “the ethical practitioner”. The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.
Recent Advancement In Geoinformatics And Data Science
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Author : Xiaogang Ma
language : en
Publisher: Geological Society of America
Release Date : 2023-04-11
Recent Advancement In Geoinformatics And Data Science written by Xiaogang Ma and has been published by Geological Society of America this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Science categories.
"The chapters in this Special Paper present the latest progress and discoveries in both the methodology and technology of geoinformatics. The methodologies, technologies, and best practices will make this volume a useful reference with long-term impacts for data-intensive geoscience in the next decade and beyond"--