Data warehousing Books

Book Synopsis1 Propagating integrity information among interrelated databases.- 2 Integrity constraint enforcement in a multidatabase using distributed active rules.- 3 The constraint operator of MedLan: its efficient implementation and use.- 4 Growing dependency on IT: the consequences thereof for the organization and for IT-auditors.- 5 TOP: an example of complex application controls.- 6 Algebra for databases with explicit markings of damaged data.- 7 Application of models from epidemiology to metrics for computer virus risk.- 8 Integrity control of spreadsheets: organisation & tools.- 9 Design basis for achieving information integrity a feedback control system approach.- 10 Modification of integrity constraints through knowledge discovery.- 11 Managing data quality and integrity in federated databases.- 12 A logical formalization of integrity policies for database management systems.- 13 Maintaining integrity constraints and security in real-time database systems.- 14 Assurance what is it?.- Two: General Information.- Index of contributors.- Keyword index.Table of ContentsPreface. Part One: IFIP TC-11 Working Group 11.5. 1. Propagating Integrity Information Among Interrelated Databases; A. Rosenthal, E. Sciore. 2. Integrity Constraint Enforcement in a Multidatabase Using Distributed Active Rules; L.G. Gomez, S.D. Urban. 3. The Constraint Operator of MedLan: Its Efficient Implementation and Use; P. Asirelli, et al. 4. Growing Dependency on IT: The Consequences Thereof for the Organization and for IT-Auditors; M.E. van Biene-Hershey. 5. TOP: An Example of Complex Application Controls; M. Korver. 6. Algebra for Databases with Explicit Markings of Damaged Data; G. Rumolo, S. Jajodia. 7. Application of Models from Epidemiology to Metrics for Computer Virus Risk; J.L. Aron, R.A. Gove. 8. Integrity Control of Spreadsheets: Organisation & Tools; K. Rajalingham, D. Chadwick. 9. Design Basis for Achieving Information Integrity - a Feedback Control System Approach; V.V. Mandke, K.M. Nayar. 10. Modification of Integrity Constraints Through Knowledge Discovery; V. Atluri. 11. Managing Data Quality and Integrity in Federated Databases; M. Gertz. 12. A Logical Formalization of Integrity Policies for Database Management Systems; F. Cuppens, C. Saurel. 13. Maintaining Integrity Constraints and Security in Real-Time Database Systems; Q.N. Ahmed, S.V. Vrbsky. 14. Assurance - What is it? M.D. Abrams, et al. Part Two: General Information. IFIP TC-11. IFIP TC-11 Working Groups. Index of Contributors. Keyword Index.

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Book SynopsisMicrosoft’s revolutionary Power Pivot is a tool that allows users to create and transform data into reports and dashboards in new and much more powerful ways using the most-used analytical tool in the world: Excel.This book, written by a member of Microsoft’s Power Pivot team, provides a practical step by step guide on creating a financial dashboard. The book covers in detail how to combine and shape the relevant data, build the dashboard in Excel, providing layout and design tips and tricks, prepare the model to work with fiscal dates, and show values used in many financial reports, including year-to-date, variance-to-target, percentage-of-total, and running totals reports.Accessibly written, this book offers readers a practical, real-world scenario and can be used as a day-to-day reference. Though the guide focuses on Power Pivot for Excel 2010, a chapter that discusses Power View—compatible with Excel 2013— and Power BI is also included.

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Book SynopsisMassive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets.In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany.   Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting

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Book SynopsisAre you struggling to find the data that you need to support your business activities? Are you concerned that people may be using the wrong data for their business activities? Are you having difficulty understanding the data that you do find in your data resource? Are you frustrated over documenting that understanding in a manner that is readily accessible to anyone in the organisation? If the answer to any of these questions is Yes, then you need to read "Data Resource Guide" to help identify, understand, access, and use the appropriate data. Most public and private sector organisations today have no formal, single location for the complete documentation of their data resource that is readily available to everyone in the organisation. Many organisations do not even have a concept of how to design, develop, or manage a single repository containing an understanding all the data available to the organisation. Yet they are staking their business on those data. "Data Resource Data" provided the complete data resource model for an organisation''s Data Resource Data. Data Resource Understanding provided a detailed description of how to thoroughly understand an organisation''s data resource through those Data Resource Data. Now, "Data Resource Guide" provides the detailed specifications for developing a simple, inexpensive, and effective way to document the data resource understanding and make that understanding readily available to anyone in the organisation. Michael Brackett draws on over half a century of data management experience to complete two trilogies for formally managing an organisation''s data as a critical resource. The Data Architecture Trilogy describes the development of a single organisation wide data architecture for an organization. The Data Understanding Trilogy describes the acquisition and documentation of understanding about all the data at an organisation''s disposal.

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Book SynopsisOrganizations invest incredible amounts of time and money obtaining and then storing big data in data stores called data lakes. But how many of these organizations can actually get the data back out in a useable form? Very few can turn the data lake into an information gold mine. Most wind up with garbage dumps. Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess. Bill Inmon opened our eyes to the architecture and benefits of a data warehouse, and now he takes us to the next level of data lake architecture.

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Book SynopsisHow do we enable our organisations to enjoy the often significant benefits of BI and analytics, while at the same time minimising the cost and risk of failure? In this book, I am not going to try to be prescriptive; I wont tell you exactly how to build your BI environment. Instead, I am going to focus on a few core principles that will enable you to navigate the rocky shoals of BI architecture and arrive at a destination best suited for your particular organisation. Some of these core principles include: Have an overarching strategy, plan, and roadmap. Recognise and leverage your existing technology investments. Support both data discovery and data reuse. Keep data in motion, not at rest. Separate information delivery from data storage. Emphasise data transparency over data quality. Take an agile approach to BI development. This book will show you how to successfully navigate both the jungle of BI technology and the minefield of human nature. It will show you how to create a BI architecture and strategy that addresses the needs of all organisational stakeholders. It will show you how to maximise the value of your BI investments. It will show you how to manage the risk of disruptive technology. And it will show you how to use agile methodologies to deliver on the promise of BI and analytics quickly, succinctly, and iteratively. This book is about many things. But principally, its about success. The goal of any enterprise initiative is to succeed and to derive benefit -- benefit that all stakeholders can share in. I want you to be successful. I want your organisation to be successful. This book will show you how. This book is for anyone who is currently or will someday be working on a BI, analytics, or Big Data project, and for organisations that want to get the maximum amount of value from both their data and their BI technology investment. This includes all stakeholders in the BI effort -- not just the data people or the IT people, but also the business stakeholders who have the responsibility for the definition and use of data. There are six sections to this book: In Section I, What Kind of Garden Do You Want?, we will examine the benefits and risks of Business Intelligence, making the central point that BI is a business (not IT) process designed to manage data assets in pursuit of enterprise goals. We will show how data, when properly managed and used, can be a key enabler of several types of core business processes. The purpose of this section is to help you define the particular benefit(s) you want from BI. In Section II, Building the Bones, we will talk about how to design and build out the hardscape (infrastructure) of your BI environment. This stage of the process involves leveraging existing technology investments and iteratively moving toward your desired target state BI architecture. In Section III, From the Ground Up, we explore the more detailed aspects of implementing your BI operational environment. In Section IV, Weeds, Pests and Critters, we talk about the myriad of things that can go wrong on a BI project, and discuss ways of mitigating these risks. In Section V, The Sustainable Garden, we talk about how to create a BI infrastructure that is easy and inexpensive to maintain. Finally, Section VI presents a case study illustrating the principles of this book, as applied to a fictional manufacturing company (the Blue Moon Guitar Company).

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Book SynopsisLearn how big data and other sources of information can be transformed into valuable knowledge -- knowledge that can create incredible competitive advantage to propel a business toward market leadership. Learn through examples and experience exactly how to pick projects and build analytics teams that deliver results. Know the ethical and privacy issues, and apply the three-part litmus test of context, permission, and accuracy. Without a doubt, data and analytics are the new source of competitive advantage, but how do executives go from hype to action? Thats the objective of this book -- to assist executives in making the right investments in the right place and at the right time in order to reap the full benefits of data analytics.

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Book SynopsisDevelop modern solutions with Snowflake's unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel, cloning, and data-sharing features to optimize data operationsKey Features Build and scale modern data solutions using the all-in-one Snowflake platform Perform advanced cloud analytics for implementing big data and data science solutions Make quicker and better-informed business decisions by uncovering key insights from your data Book DescriptionSnowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud. This book introduces you to Snowflake's unique architecture, which places it at the forefront of cloud data warehouses.You'll explore the compute model available with Snowflake, and find out how Snowflake allows extensive scaling through the virtual warehouses. You will then learn how to configure a virtual warehouse for optimizing cost and performance. Moving on, you'll get to grips with the data ecosystem and discover how Snowflake integrates with other technologies for staging and loading data.As you progress through the chapters, you will leverage Snowflake's capabilities to process a series of SQL statements using tasks to build data pipelines and find out how you can create modern data solutions and pipelines designed to provide high performance and scalability. You will also get to grips with creating role hierarchies, adding custom roles, and setting default roles for users before covering advanced topics such as data sharing, cloning, and performance optimization.By the end of this Snowflake book, you will be well-versed in Snowflake's architecture for building modern analytical solutions and understand best practices for solving commonly faced problems using practical recipes.What you will learn Get to grips with data warehousing techniques aligned with Snowflake's cloud architecture Broaden your skills as a data warehouse designer to cover the Snowflake ecosystem Transfer skills from on-premise data warehousing to the Snowflake cloud analytics platform Optimize performance and costs associated with a Snowflake solution Stage data on object stores and load it into Snowflake Secure data and share it efficiently for access Manage transactions and extend Snowflake using stored procedures Extend cloud data applications using Spark Connector Who this book is forThis book is for data warehouse developers, data analysts, database administrators, and anyone involved in designing, implementing, and optimizing a Snowflake data warehouse. Knowledge of data warehousing and database and cloud concepts will be useful. Basic familiarity with Snowflake is beneficial, but not necessary.Table of ContentsTable of Contents Getting Started with Snowflake Managing the Data Life Cycle Loading and Extracting Data into and out of Snowflake Building Data Pipelines in Snowflake Data Protection and Security in Snowflake Performance and Cost Optimization Secure Data Sharing Back to the Future with Time Travel Advanced SQL Techniques Extending Snowflake's Capabilities

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Book SynopsisTake your data engineering skills to the next level by learning how to utilize Scala and functional programming to create continuous and scheduled pipelines that ingest, transform, and aggregate data Key Features Transform data into a clean and trusted source of information for your organization using Scala Build streaming and batch-processing pipelines with step-by-step explanations Implement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD) Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount. This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You’ll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You’ll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users. By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices.What you will learn Set up your development environment to build pipelines in Scala Get to grips with polymorphic functions, type parameterization, and Scala implicits Use Spark DataFrames, Datasets, and Spark SQL with Scala Read and write data to object stores Profile and clean your data using Deequ Performance tune your data pipelines using Scala Who this book is forThis book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies.Table of ContentsTable of Contents Scala Essentials for Data Engineers Environment Setup An Introduction to Apache Spark and Its APIs – DataFrame, Dataset, and Spark SQL Working with Databases Object Stores and Data Lakes Understanding Data Transformation Data Profiling and Data Quality Test-Driven Development, Code Health, and Maintainability CI/CD with GitHub Data Pipeline Orchestration Performance Tuning Building Batch Pipelines Using Spark and Scala Building Streaming Pipelines Using Spark and Scala

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Book SynopsisAre you struggling with a disparate data resource? Are there multiple existences of the same business fact scattered throughout the data resource? Are those multiple existences out of synch with each other? Do you have difficulty finding the data you need to support business activities? Do the data you find have poor quality? If the answer to any of these questions is Yes, then you need this book to guide you toward creating an integrated data resource. Most public and private sector organisations have a disparate data resource that was created over many years. That disparate data resource contains multiple existences of business facts that are out of synch with each other, are of poor quality, and are difficult to locate. The traditional approach to dealing with a disparate data resource is to perform periodic and temporary data integration to support a specific application or business activity. Those piecemeal data integration efforts may meet a current need, but seldom solve the underlying problems with a disparate data resource, and sometimes make the situation worse. This book explains how to go about understanding and resolving a disparate data resource and creating a comparate data resource that fully meets an organisation''s current and future business information demand. It builds on Data Resource Simplexity, which described how to stop the burgeoning data disparity. It explains the concepts, principles, and techniques for understanding a disparate data resource within the context of a common data architecture, and resolving that disparity with minimum impact on the business. Like Data Resource Simplexity, Michael Brackett draws on five decades of data management experience building and managing data resources, and resolving disparate data resources in both public and private sector organisations. He leverages theories, concepts, principles, and techniques from a wide variety of disciplines, such as human dynamics, mathematics, physics, chemistry, and biology, and applies them to the process of understanding and resolving a disparate data resource. He shows you how to approach and resolve a disparate data resource, and build a comparate data resource that fully supports the business.

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Book SynopsisAre you struggling with the formal design of your organisation''s data resource? Do you find yourself forced into generic data architectures and universal data models? Do you find yourself warping the business to fit a purchased application? Do you find yourself pushed into developing physical databases without formal logical design? Do you find disparate data throughout the organisation? If the answer to any of these questions is Yes, then you need to read Data Resource Design to help guide you through a formal design process that produces a high quality data resource within a single common data architecture. Most public and private sector organisations do not consistently follow a formal data resource design process that begins with the organisation''s perception of the business world, proceeds through logical data design, through physical data design, and into implementation. Most organisations charge ahead with physical database implementation, physical package implementation, and other brute-force-physical approaches. The result is a data resource that becomes disparate and does not fully support the organisation in its business endeavours. This book describes how to formally design an organisation''s data resource to meet its current and future business information demand. It builds on Data Resource Simplexity, which described how to stop the burgeoning data disparity, and on Data Resource Integration, which described how to understand and resolve an organisation''s disparate data resource. It describes the concepts, principles, and techniques for building a high quality data resource based on an organisation''s perception of the business world in which they operate. Like Data Resource Simplexity and Data Resource Integration, Michael Brackett draws on five decades of data management experience building and managing data resources, and resolving disparate data in both public and private sector organisations. He leverages theories, concepts, principles, and techniques from a wide variety of disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to properly designing data as a critical resource of an organisation. He shows how to understand the business environment where an organisation operates and design a data resource that supports the organisation in that business environment.

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Book SynopsisDo your business intelligence (BI) projects take too long to deliver? Is the value of the deliverables less than satisfactory? Do these projects propagate poor data management practices? If you screamed yes to any of these questions, read this book to master a proven approach to building your enterprise data warehouse and BI initiatives. Extreme Scoping, based on the Business Intelligence Roadmap, will show you how to build analytics applications rapidly yet not sacrifice data management and enterprise architecture. In addition, all of the roles required to deliver all seven steps of this agile methodology are explained along with many real-world examples. From Wayne Eckerson''s Foreword -- I''ve read many books about data warehousing and business intelligence (BI). This book by Larissa Moss is one of the best. I should not be surprised. Larissa has spent years refining the craft of designing, building, and delivering BI applications. Over the years, she has developed a keen insight about what works and doesn''t work in BI. This book brings to light the wealth of that development experience. Best of all, this is not some dry text that laboriously steps readers through a technical methodology. Larissa expresses her ideas in a clear, concise, and persuasive manner. I highlighted so many beautifully written and insightful paragraphs in her manuscript that it became comical. I desperately wanted the final, published book rather than the manuscript so I could dog-ear it to death and place it front-and-center in my office bookshelf! From David Well''s Foreword : Extreme Scoping is rich with advice and guidance for virtually every aspect of BI projects from planning and requirements to deployment and from back-end data management to front-end information and analytics services. Larissa is both a pragmatist and an independent thinker. Those qualities come through in the style of this book. This is a well-written book that is easy to absorb. It is not full of surprises. It is filled with a lot of common sense and lessons learned through experience.

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Book SynopsisFeatures: 366 SQL Server Interview Questions; 76 HR Interview Questions; Real life scenario based questions; Strategies to respond to interview questions; 2 Aptitude Tests. This is a perfect companion to stand a head above the rest in todays competitive job market. Rather than going through comprehensive, textbook-sized reference guides, this book includes only the information required immediately for job search to build an IT career. This book puts the interviewee in the driver's seat and helps them steer their way to impress the interviewer.

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Book SynopsisThis timely textbook presents a comprehensive guide to the core topics in cybersecurity, covering issues of security that extend beyond traditional computer networks to the ubiquitous mobile communications and online social networks that have become part of our daily lives. In the context of our growing dependence on an ever-changing digital ecosystem, this book stresses the importance of security awareness, whether in our homes, our businesses, or our public spaces.This fully updated new edition features new material on the security issues raised by blockchain technology, and its use in logistics, digital ledgers, payments systems, and digital contracts.Topics and features: Explores the full range of security risks and vulnerabilities in all connected digital systems Inspires debate over future developments and improvements necessary to enhance the security of personal, public, and private enterprise systems Raises thought-provoking questions regarding legislative, legal, social, technical, and ethical challenges, such as the tension between privacy and security Describes the fundamentals of traditional computer network security, and common threats to security Reviews the current landscape of tools, algorithms, and professional best practices in use to maintain security of digital systems Discusses the security issues introduced by the latest generation of network technologies, including mobile systems, cloud computing, and blockchain Presents exercises of varying levels of difficulty at the end of each chapter, and concludes with a diverse selection of practical projects Offers supplementary material for students and instructors at an associated website, including slides, additional projects, and syllabus suggestions This important textbook/reference is an invaluable resource for students of computer science, engineering, and information management, as well as for practitioners working in data- and information-intensive industries.Table of ContentsPart I: Introduction to Traditional Computer Network Security Computer Network Fundamentals Computer Network Security Fundamentals Part II: Security Issues and Challenges in the Traditional Computer Network Security Threats and Threat Motives to Computer Networks Introduction to Computer Network Vulnerabilities Cyber Crimes and Hackers Scripting and Security in Computer Networks and Web Browsers Security Assessment, Analysis, and Assurance Part III: Dealing with Computer Network Security Challenges Disaster Management Access Control and Authorization Authentication Control and Authorization Authentication Cryptography Firewalls System Intrusion Detection and Prevention Computer and Network Forensics Virus and Content Filtering Standardization and Security Criteria: Security Evaluation of Computer Products Computer Network Security Protocols Security in Wireless Networks and Devices Security in Sensor Networks Other Efforts to Secure Data in Computer Networks and Beyond Part IV: The Emergence of the Digital and Social Network Ecosystem – The Elastic Extension of the Traditional Computer Network Through Virtualization, Cloud Computing and Mobile Technologies Virtualization Technology and Security Cloud Computing Technology and Security Mobile Systems and Corresponding Intractable Security Issues Internet of Things (IoT): Growth, Challenges, and Security Blockchains, Cryptocurrency, and Smart Contracts Technology: Security Considerations Part V: Securing the Last Frontiers – The Home Front Conquering the Last Frontier in the Digital Invasion: The Home Front Part VI: Hands-On Projects Projects

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Book SynopsisChapters “No. 10 and No. 21” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Table of ContentsResearch.- Resources.- In-Use Track.

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Book SynopsisThis book provides a principled data-driven framework that progressively constructs, enriches, and applies taxonomies without leveraging massive human annotated data. Traditionally, people construct domain-specific taxonomies by extensive manual curations, which is time-consuming and costly. In today’s information era, people are inundated with the vast amounts of text data. Despite their usefulness, people haven’t yet exploited the full power of taxonomies due to the heavy curation needed for creating and maintaining them. To bridge this gap, the authors discuss automated taxonomy discovery and exploration, with an emphasis on label-efficient machine learning methods and their real-world usages. Taxonomy organizes entities and concepts in a hierarchy way. It is ubiquitous in our daily life, ranging from product taxonomies used by online retailers, topic taxonomies deployed by news outlets and social media, as well as scientific taxonomies deployed by digital libraries across various domains. When properly analyzed, these taxonomies can play a vital role for science, engineering, business intelligence, policy design, e-commerce, and more. Intuitive examples are used throughout enabling readers to grasp concepts more easily.Table of ContentsIntroduction.- Concept Set Expansion.- Taxonomy Construction.- Taxonomy Enrichment.- Taxonomy-Guided Classification.- Conclusions.

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Book SynopsisThis book constitutes the proceedings of the satellite events held at the 19th Extended Semantic Web Conference, ESWC 2022, during May—June in Hersonissos, Greece, 2022. The included satellite events are: the poster and demo session; the PhD symposium; industry track; project networking; workshops and tutorials. During ESWC 2022, the following ten workshops took place:10th Linked Data in Architecture and Construction Workshop (LDAC 2022); 5th International Workshop on Geospatial Linked Data (GeoLD 2022); 5th Workshop on Semantic Web solutions for large-scale biomedical data analytics (SeMWeBMeDA 2022); 7th Natural Language Interfaces for the Web of Data (NLIWOD+QALD 2022); International Workshop on Knowledge Graph Generation from Text (Text2KG 2022); 3rd International Workshop on Deep Learning meets Ontologies and Natural Language Processing (DeepOntoNLP 2022); 1st Workshop on Modular Knowledge (ModularK 2022); Third International Workshop On Knowledge Graph Construction (KGCW 2022); Third International Workshop On Semantic Digital Twins (SeDIT 2022); and the 1st International Workshop on Semantic Industrial Information Modelling (SemIIM 2022). Table of Contents Summary of Workshops and Tutorials at European Semantic Web Conference 2022.- Posters and Demos.- Towards UML-style Visual Queries over Wikidata.- Using the ODRL Profile for Access Control for Solid Pod Resource Governance.- Relation Canonicalization in Open Knowledge Graphs: A Quantitative Analysis.- Harmonizing and Using Numismatic Linked Data in Digital Humanities Research and Application Development: Case DigiNUMA.- Extending AgreementMakerLight to Perform Holistic Ontology Matching.- It’s all in the Name: Entity Typing using Multilingual Language Models.- The Supervised Semantic Similarity Toolkit.- Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings.- DataSpecer: A Model-Driven Approach to Managing Data Specifications.- Towards Query Processing over Heterogeneous Federations of RDF Data sources.- SAND: A Tool for Creating Semantic Descriptions of Tabular Sources.- BLAST: Block Applications for Things.- Leibniz Data Manager – A Research Data Management System.- Towards Knowledge Graph-Agnostic SPARQL Query Validation for Improving Question Answering.- Towards Generalized Welding Ontology in line with ISO and Knowledge Graph Construction.- O’FAIRe: Ontology FAIRness Evaluator in the AgroPortal semantic resource repository.- domOS Common Ontology: Web of Things Discovery in Smart Buildings.- WeaKG-MF: a Knowledge Graph of Observational Weather Data.- DAGOBAH UI: A New Hope For Semantic Table Interpretation.- KartoGraphI: Drawing a Map of Linked Data.- WikidataComplete – An easy-to-use method for rapid validation of text-extracted new facts applied to the Wikidata knowledge graph.- Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping.- Semantic Video Entity Linking.- Walk this Way! Entity Walks and Property Walks for RDF2vec.- Self-Verifying Web Resource Representations using Solid, RDF-star and Signed URIs.- From OWL to Graphol: importing ontologies into Eddy the editor.- Audio Ontologies for Intangible Cultural Heritage.- Ontology Matching Through Absolute Orientation of Embedding Spaces.- Semantic modeling and reconstruction of drones’ Trajectories.- How to Search and Contextualize Scenes inside Videos for Enriched Watching Experience: Case Stories of the Second World War Veterans.- PhD Symposium.- (Semi-) Automatic construction of knowledge graph Metadata.- Towards a Similarity Algorithm for Controlled Vocabularies within the Digital Humanities.- Causal Domain Adaptation for Information Extraction from Complex Conversations.- Knowledge Graph Population with Out-of-KG Entities.- Dynamic Knowledge Graph Embeddings via Local Embedding Reconstructions.- Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation.- Building Narrative Structures from Knowledge Graphs.- Using Referential Language Games for Task-oriented Ontology Alignment.- Balancing RDF generation from heterogeneous data sources.- Geological Information Capture with Sketches and Ontologies.- Industry.- The Data Value Quest: A Holistic Semantic Approach at Bosch.- Extracting Subontologies from SNOMED CT.- “Semantify” business and content to meet demands for expert solutions in professional markets.- Enhancing Knowledge Graph Generation with Ontology Reshaping – Bosch Case.- Semantic Data Integration for Monitoring Operators’ Ergonomics in an Automotive Manufacturing Setting.- Semantic Description of Equipment and its Controls in Building Automation Systems.

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Book SynopsisThis book constitutes the refereed proceedings of the 20th International Conference on Business Process Management, BPM 2022, which took place in Münster, Germany, in September 2022. The 22 papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in topical sections as follows: task mining; design methods; process mining; process mining practice; analytics; and systems. The book also includes one keynote talk in full-paper length and 5 tutorial papers. Table of ContentsKeynote.- Advancing Business Process Science via the Co-Evolution of Substantive and Methodological Knowledge.- Tutorials.- BPM in Digital Transformation: New Tools and Productivity Challenges.- Multi-Dimensional Process Analysis.- Theory and Practice - What, With What and How Is Business Process Management Taught at German Universities.-How to Leverage Process Mining in Organizations - Towards Process Mining Capabilities.- Mastering Robotic Process Automation with Process Mining.- Task Mining.- A Reference Data Model for Process-Related User Interaction Logs.- Analysing Variable Human Actions for Robotic Process Automation.- The SWORD is Mightier than the Interview: A Framework for Semi-automatic WORkaround Detection.- Design Methods.- Back to the Roots – Investigating the Theoretical Foundations of Business Process Maturity Models.- Applying Process Mining in Small and Medium sized IT Enterprises – Challenges and Guidelines.- A Process Mining Success Factors Model.- Process Mining.- No Time to Dice: Learning Execution Contexts from Event Logs for Resource-Oriented Process Mining.- A Purpose-Guided Log Generation Framework.- Conformance Checking with Uncertainty via SMT.- Process Mining Practice.- The Dark Side of Process Mining. How Identifiable Are Users Despite Technologically Anonymized Data? A Case Study From the Health Sector.- Analyzing How Process Mining Reports Answer Time Performance Questions.- Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing.- Process Mining Practices: Evidence from Interviews.- Analytics.- Measuring Inconsistency in Declarative Process Specifications.- Understanding and Decomposing Control-Flow Loops in Business Process Models.- Reasoning on Labelled Petri Nets and their Dynamics in a Stochastic Setting.- Incentive Alignment through Secure Computations.- Business Process Simulation with Differentiated Resources: Does it Make a Difference.- Uncovering Object-centric Data in Classical Event Logs for the Automated Transformation from XES to OCEL.- Systems.- Why Companies Use RPA: A Critical Reflection of Goals.- A trustworthy decentralized change propagation mechanism for declarative choreographies.- Architecture of decentralized Process Management Systems.

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Book SynopsisThis book provides a new model to explore discoverability and enhance the meaning of information. The authors have coined the term epidata, which includes items and circumstances that impact the expression of the data in a document, but are not part of the ordinary process of retrieval systems. Epidata affords pathways and points to details that cast light on proximities that might otherwise go unknown. In addition, epidata are clues to mis-and dis-information discernment. There are many ways to find needed information; however, finding the most useable information is not an easy task. The book explores the uses of proximity and the concept of epidata that increases the probability of finding functional information. The authors sketch a constellation of proximities, present examples of attempts to accomplish proximity, and provoke a discussion of the role of proximity in the field. In addition, the authors suggest that proximity is a thread between retrieval constructs based on known topics, predictable relations, and types of information seeking that lie outside constructs such as browsing, stumbling, encountering, detective work, art making, and translation.Table of ContentsProximity and Clues.- More than Meets the Eye.- Epidata, Clues, Threads, and Webs.- Provocations and Invitations.

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Book SynopsisThis book provides a broad introduction to search engines by integrating five different perspectives on Web search and search engines that are usually dealt with separately: the technical perspective, the user perspective, the internet-based research perspective, the economic perspective, and the societal perspective.After a general introduction to the topic, two foundational chapters present how search tools can cover the Web’s content and how search engines achieve this by crawling and processing the found documents. The next chapter on user behavior covers how people phrase their search queries and interact with search engines. This knowledge builds the foundation for describing how results are ranked and presented. The following three chapters then deal with the economic side of search engines, i.e., Google and the search engine market, search engine optimization (SEO), and the intermingling of organic and sponsored search results. Next, the chapter on search skills presents techniques for improving searches through advanced search interfaces and commands. Following that, the Deep Web and how its content can be accessed is explained. The two subsequent chapters cover ways to improve the quality of search results, while the next chapter describes how to access the Deep Web. Last but not least, the following chapter deals with the societal role of search engines before the final chapter concludes the book with an outlook on the future of Web search.With this book, students and professionals in disciplines like computer science, online marketing, or library and information science will learn how search engines work, what their main shortcomings are at present, and what prospects there are for their further development. The different views presented will help them to understand not only the basic technologies but also the implications the current implementations have concerning economic exploitation and societal impact.Table of Contents- 1. Introduction. - 2. Ways of Searching the Web. - 3. How Search Engines Capture and Process Content from the Web. - 4. User Interaction with Search Engines. - 5. Ranking Search Results. - 6. Vertical Search. - 7. Search Result Presentation. - 8. The Search Engine Market. - 9. Search Engine Optimization (SEO). - 10. Search Engine Advertising (SEA). - 11. Alternatives to Google. - 12. Search Skills. - 13. Search Result Quality. - 14. The Deep Web. - 15. Search Engines Between Bias and Neutrality. - 16. The Future of Search.

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Book SynopsisThe three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, 12 reproducibility papers consortium papers, 7 tutorial papers, and 10 doctorial consortium papers were carefully reviewed and selected from 489 submissions. The book also contains, 8 workshop summaries and 13 CLEF Lab descriptions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.Table of ContentsFull Papers.- Automatic Summarization of Financial Earnings Calls Transcript.- Parameter-Efficient Sparse Retrievers and Rerankers using Adapters.- Feature Differentiation and Fusion for Semantic Text Matching.- Multivariate Powered Dirichlet-Hawkes Process.- Fragmented Visual Attention in Web Browsing: Weibull Analysis of Item Visit Times.- Topic-Enhanced Personalized Retrieval-based Chatbot.- Improving the Generalizability of the Dense Passage Retriever Using Generated Datasets.- SegmentCodeList: Unsupervised Representation Learning for Human Skeleton Data Retrieval.- Knowing What and How: A Multi-modal Aspect-Based Framework for Complaint Detection.- What is your cause for concern? Towards Interpretable Complaint Cause Analysis.- DeCoDE: DEtection of COgnitive Distortion and Emotion cause extraction in clinical conversations.- Domain-aligned Data Augmentation for Low-resource and Imbalanced Text Classification.- Privacy-Preserving Fair Item Ranking.- Multimodal Geolocation Estimation of News Photos.- Topics in Contextualised Attention Embeddings.- New Metrics to Encourage Innovation and Diversity in Information Retrieval Approaches.- Probing BERT for Ranking Abilities.- Clustering of Bandit with Frequency-Dependent Information Sharing.- Contrastive Graph Learning with Positional Representation for Recommendation.- Domain Adaptation for Anomaly Detection on Heterogeneous Graphs in E-Commerce.- Short PapersImproving Neural Topic Models with Wasserstein Knowledge Distillation.- Towards Effective Paraphrasing for Information Disguise.- Generating Topic Pages for Scientific Concepts Using Scientific Publications.- Relevance Judgements for Fair Ranking.- A Study of Term-Topic Embeddings for Ranking.- Topic Refinement in Multi-Level Hate Speech Detection.- Is Cross-modal Information Retrieval Possible without Training?.- Adversarial Adaptation for French Named Entity Recognition.- Exploring Fake News Detection with Heterogeneous Social Media Context Graphs.- Justifying Multi-Label Text Classifications for Healthcare Applications.- Doc2Query–: When Less is More.- Towards Quantifying The Privacy Of Redacted Text. -Detecting Stance of Authorities towards Rumors in Arabic Tweets: A Preliminary Study.- Leveraging Comment Retrieval for Code Summarization.- CPR: Cross-domain Preference Ranking with User Transformation.- Colbert-FairPRF: Towards Fair Pseudo-Relevance Feedback in Dense Retrieval.- C2LIR: Continual Cross-lingual Transfer for Low-Resource Information Retrieval.- Joint Extraction and Classification of Danish Competences for Job Matching.- A Study on FGSM Adversarial Training for Neural Retrieval.- Dialogue-to-Video Retrieval.- Time-dependent next-basket recommendations.- Investigating the Impact of Query Representation on Medical Information Retrieval.- Where a Little Change Makes a Big Difference: A Preliminary Exploration of Children’s Queries.- Multi-document QA with GPT-3 and Neural Reranking .- Towards Detecting Interesting Ideas Expressed in Text.- Towards Linguistically Informed Multi-Objective Transformer Pre-Training for Natural Language Inference.- Dirichlet-Survival Process: Scalable Inference of Topic-Dependent Diffusion Networks.- Consumer Health Question Answering Using Off-the-shelf Components.- MOO-CMDS+NER: Named Entity Recognition-based Extractive Comment-oriented Multi-document Summarization.- Don’t Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments.- Learning Query-Space Document Representations for High-Recall Retrieval.- Investigating Conversational Search Behavior For Domain Exploration.- Evaluating Humorous Response Generation to Playful Shopping Requests.- Joint Span Segmentation and Rhetorical Role Labeling with Data Augmentation for Legal Documents.- Trigger or not Trigger: Dynamic Thresholding for Few Shot Event Detection.- The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance.- Neural Ad hoc Retrieval Meets Information Extraction.- Augmenting Graph Convolutional Networks with Textual Data for Recommendations.- Utilising Twitter Metadata for Hate Classification.- Evolution of Filter Bubbles and Polarization in News Recommendation.- Capturing Cross-platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns.

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Book SynopsisThis book constitutes the refereed proceedings of the 16th International Conference on Similarity Search and Applications, SISAP 2023, held in A Coruña, Spain, during October 9–11, 2023.The 16 full papers and 4 short papers included in this book were carefully reviewed and selected from 33 submissions. They were organized in topical sections as follows: similarity queries, similarity measures, indexing and retrieval, data management, feature extraction, intrinsic dimensionality, efficient algorithms, similarity in machine learning and data mining.Table of Contents​Keynotes.- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View.- The Rise of HNSW: Understanding Key Factors Driving the Adoption.- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks.- Research Track.- Finding HSP Neighbors via an Exact, Hierarchical Approach.- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash.- Mutual nearest neighbor graph for data analysis: Application to metric space clustering.- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search.- Unbiased Similarity Estimators using Samples.- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies.- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification.- Runs of Side-Sharing Tandems in Rectangular Arrays.- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions.- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification.- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval.- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback.- Accelerating k-Means Clustering with Cover Trees.- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality.- Minwise-Independent Permutations with Insertion and Deletion of Features.- SDOclust: Clustering with Sparse Data Observers.- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing.- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval.- Similarity Search with Multiple-Object Queries.- Diversity Similarity Join for Big Data.- Indexing Challenge.- Overview of the SISAP 2023 Indexing Challenge.- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction.- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo.- SISAP 2023 Indexing Challenge – Learned Metric Index.- Computational Enhancements of HNSW Targeted to Very Large Datasets.- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.

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Book SynopsisThis book offers a comprehensive guide to the world of metadata, from its origins in the ancient cities of the Middle East, to the Semantic Web of today. The author takes us on a journey through the centuries-old history of metadata up to the modern world of crowdsourcing and Google, showing how metadata works and what it is made of. The author explores how it has been used ideologically and how it can never be objective. He argues how central it is to human cultures and the way they develop. Metadata: Shaping Knowledge from Antiquity to the Semantic Web is for all readers with an interest in how we humans organize our knowledge and why this is important. It is suitable for those new to the subject as well as those know its basics. It also makes an excellent introduction for students of information science and librarianship. Trade Review“In Metadata: Shaping Knowledge from Antiquity to the Semantic Web, Gartner, the digital librarian at the Warburg Institute at the University of London, thoroughly covers not only the history of metadata, but how it affects and forms knowledge and culture. … The author concludes the work with recent advances in metadata creation—metadata produced via Web 2.0, crowdsourcing, and folksonomies. This is a meticulous overview of metadata and its history and application. Summing Up: Recommended. Graduate students, faculty, and professionals.” (A. Hollister, Choice, Vol. 54 (9), May, 2017)“The book presents an enjoyable bird’s-eye view of metadata and related concepts, with outstanding examples accessible to non-experts. … I highly recommend the book.” (H. I. Kilov, Computing Reviews, May, 2017)“The book covers continuous evolution of metadata from the history of cataloguing to the modern forms … . This book will attract readers interested in metadata, the semantic web, metadata ontologies, digital libraries, and semantic retrieval. So, it is highly recommended to information professionals, digital librarians and students. The book is well structured and motivating. The results of Gartner’s effort are very much worth reading due to his librarianship perspective on metadata.” (Elaheh Hossseini, Information Research, informationr.net, Vol. 22 (1), March, 2017)“All of the usual elements of a book on metadata are present and correct … I would urge you to read this book if you are new to cataloguing or if you are old in cataloguing and world-weary about our professional mission. It’s a book to provoke your own thoughts, and quite possibly to give to your manager if you suspect they are unsure why metadata, why cataloguing and, therefore, why you and your team matter.” (Anne Welsh, Catalogue and Index, cilip.org.uk, Issue 186, March, 2017) “The book provides an overview of existing metadata approaches and standards such as MARC, Dublin Core, MIX and EAD. This book also offers a succinct history of metadata and discusses emerging metadata approaches. … This book can be read by both technical and non-technical people as it uses a rather accessible language. Metadata makes information finding easier. This is an excellent read and I highly recommend it to my colleagues and friends.” (Getaneh Alemu, Linkedin.com, January, 2017)“This slim volume aims to provide the reader with an overview of the history and development of metadata from the earliest times to the present day, and it offers a straightforward and readable account of metadata for the novice or the non-professional. … There is plenty here to intrigue and entertain for those wanting a lightweight introduction to the subject, at a very attractive price … .” (Vanda Broughton, Library & Information History, Vol. 33 (2), 2017)Table of ContentsWhat Metadata is and why it Matters.- Clay, Goats and Trees: Metadata before the Byte.- Metadata Becomes Digital.- Metadata as Ideology.- The Ontology of Metadata.- The Taxonomic Urge.- From Hierarchies to Networks.- Breaking the Silos.- Democratizing Metadata.- Knowledge and Uncertainty.

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Book SynopsisWhat is the uniquely human factor in finding and using information to produce new knowledge? Is there an underlying aspect of our thinking that cannot be imitated by the AI-equipped machines that will increasingly dominate our lives? This book answers these questions, and tells us about our consciousness – its drive or intention in seeking information in the world around us, and how we are able to construct new knowledge from this information. The book is divided into three parts, each with an introduction and a conclusion that relate the theories and models presented to the real-world experience of someone using a search engine. First, Part I defines the exceptionality of human consciousness and its need for new information and how, uniquely among all other species, we frame our interactions with the world. Part II then investigates the problem of finding our real information need during information searches, and how our exceptional ability to frame our interactions with the world blocks us from finding the information we really need. Lastly, Part III details the solution to this framing problem and its operational implications for search engine design for everyone whose objective is the production of new knowledge.In this book, Charles Cole deliberately writes in a conversational style for a broader readership, keeping references to research material to the bare minimum. Replicating the structure of a detective novel, he builds his arguments towards a climax at the end of the book. For our video-game, video-on-demand times, he has visualized the ideas that form the book’s thesis in over 90 original diagrams. And above all, he establishes a link between information need and knowledge production in evolutionary psychology, and thus bases his arguments in our origins as a species: how we humans naturally think, and how we naturally search for new information because our consciousness drives us to need it.Trade Review“This is an important book, well worth the effect necessary to absorb the, at times, complex arguments. It certainly ought to be a candidate for the ASIST Best Information Science Book Award … I am sure it will become a highly cited text and of great value to researchers in the field … . It is well written, dealing with complex topics in a readily understandable fashion, with the aid many diagrams and illustrations.” (T. D. Wilson, Information Research, Vol. 23 (04), December, 2018)Table of Contents1 Human Exceptionality: How We See Ourselves in Relation to the World.- 2 Framing - Lessons from Vermeer.- 3 Episodic Memory: Lessons from the Scrub Jays.- 4 Episodic Memory: Subjective Time-travel.- 5 Episodic-to-Mimetic Transition.- 6 Framing: The Mimetic-to-Mythic Transition.- 7 Framing: The Mythic-to-Theoretic Transition.- 8 Problem Set-Up: Minsky’s Frame Theory.- 9 Individual Frame Level: Meno’s Paradox.- 10 Group Frame Level: Information Avoidance.- 11 Nation Frame Level: The Dark Side.- 12 Solution: Opening the Information Loop: Constructing Information Channels.- 13 Solution: Belief-Begets-Knowledge: Definitions.- 14 Belief-based Information Search.- 15 The Model of the Consciousness’ Drive: Information Need and the Search for Meaning.

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Book SynopsisDaten und Datenbanken sind quasi überall. Mit der Standardabfragesprache SQL können Daten in relationalen Datenbanken einfach, strukturiert und zielsicher abgefragt werden. Erfahren Sie in diesem Buch, das kein Vorwissen voraussetzt, wie Sie Datenbanken erstellen, Daten ordnen und abfragen und wie Sie SQL-Anweisungen in Programme und Websites einbinden. Nutzen Sie dieses Buch auch als Nachschlagewerk. Ganz wichtig: Sie lernen auch, wie Sie Ihre Datenbanken und Daten schützen und wie Sie typische Fehler vermeiden.Table of ContentsÜber den Autor 9 Einleitung 25 Teil I: Grundbegriffe 29 Kapitel 1: Grundlagen relationaler Datenbanken 31 Kapitel 2: SQL-Grundlagen 45 Kapitel 3: Die Komponenten von SQL 77 Teil II: Datenbanken mit SQL erstellen 105 Kapitel 4: Eine einfache Datenbankstruktur erstellen und verwalten 107 Kapitel 5: Eine relationale Datenbank mit mehreren Tabellen erstellen 131 Teil III: Daten speichern und abrufen 163 Kapitel 6: Daten einer Datenbank bearbeiten 165 Kapitel 7: Temporale Daten verarbeiten 183 Kapitel 8: Das Angeben von Datenwerten 197 Kapitel 9: SQL-Wertausdrücke – fortgeschrittener Teil 225 Kapitel 10: Daten zielsicher finden 237 Kapitel 11: Relationale Operatoren 267 Kapitel 12: Mit verschachtelten Abfragen tief schürfen 289 Kapitel 13: Rekursive Abfragen 307 Teil IV: Kontrollmechanismen 317 Kapitel 14: Datenbanken schützen 319 Kapitel 15: Daten schützen 335 Kapitel 16: SQL in Anwendungen nutzen 355 Teil V: SQL in der Praxis 369 Kapitel 17: Datenzugriffe mit ODBC und JDBC 371 Kapitel 18: SQL und XML 381 Teil VI: SQL für Fortgeschrittene 401 Kapitel 19: Cursor 403 Kapitel 20: Prozedurale Möglichkeiten mit dauerhaft gespeicherten Modulen schaffen 413 Kapitel 21: Fehlerbehandlung 431 Kapitel 22: Trigger 443 Teil VII: Der Top-Ten-Teil 449 Kapitel 23: Zehn häufige Fehler 451 Kapitel 24: Zehn Tipps für Abfragen 455 Anhang A: Wie kommt man zu einer Datenbankumgebung? 459 Anhang B: SQL: Reservierte Wörter 465 Abbildungsverzeichnis 467 Stichwortverzeichnis 471

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Book SynopsisFormanyyearstheintersectionofcomputing anddataanalysiscontainedme- based statistics packages and not much else. Recently, statisticians have - braced computing, computer scientists have started using statistical theories and methods, and researchers in all corners have invented algorithms to nd structure in vast online datasets. Data analysts now have access to tools for exploratory data analysis, decision tree induction, causal induction, function - timation,constructingcustomizedreferencedistributions,andvisualization,and thereareintelligentassistantsto adviseonmatters ofdesignandanalysis.There aretoolsfortraditional,relativelysmallsamples,andalsoforenormousdatasets. In all, the scope for probing data in new and penetrating ways has never been so exciting. The IDA-99 conference brings together a wide variety of researchers c- cerned with extracting knowledge from data, including people from statistics, machine learning, neural networks, computer science, pattern recognition, da- base management, and other areas.The strategiesadopted by people from these areas are often di erent, and a synergy results if this is recognized. The IDA series of conferences is intended to stimulate interaction between these di erent areas,sothatmorepowerfultoolsemergeforextractingknowledgefromdataand a better understanding is developed of the process of intelligent data analysis. The result is a conference that has a clear focus (one application area:intelligent data analysis) and a broad scope (many di erent methods and techniques).Table of ContentsLearning.- From Theoretical Learnability to Statistical Measures of the Learnable.- ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis.- A “Top-Down and Prune” Induction Scheme for Constrained Decision Committees.- Mining Clusters with Association Rules.- Evolutionary Computation to Search for Strongly Correlated Variables in High-Dimensional Time-Series.- The Biases of Decision Tree Pruning Strategies.- Feature Selection as Retrospective Pruning in Hierarchical Clustering.- Discriminative Power of Input Features in a Fuzzy Model.- Learning Elements of Representations for Redescribing Robot Experiences.- “Seeing“ Objects in Spatial Datasets.- Intelligent Monitoring Method Using Time Varying Binomial Distribution Models for Pseudo-Periodic Communication Traffic.- Visualization.- Monitoring Human Information Processing via Intelligent Data Analysis of EEG Recordings.- Knowledge-Based Visualization to Support Spatial Data Mining.- Probabilistic Topic Maps: Navigating through Large Text Collections.- 3D Grand Tour for Multidimensional Data and Clusters.- Classification and Clustering.- A Decision Tree Algorithm for Ordinal Classification.- Discovering Dynamics Using Bayesian Clustering.- Integrating Declarative Knowledge in Hierarchical Clustering Tasks.- Nonparametric Linear Discriminant Analysis by Recursive Optimization with Random Initialization.- Supervised Classification Problems: How to Be Both Judge and Jury.- Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification.- Exploiting Similarity for Supporting Data Analysis and Problem Solving.- Multiple Prototype Model for Fuzzy Clustering.- A Comparison of Genetic Programming Variants for Data Classification.- Fuzzy Clustering Based on Modified Distance Measures.- Building Classes in Object-Based Languages by Automatic Clustering.- Integration.- Adjusted Estimation for the Combination of Classifiers.- Data-Driven Theory Refinement Using KBDistAl.- Reasoning about Input-Output Modeling of Dynamical Systems.- Undoing Statistical Advice.- A Method for Temporal Knowledge Conversion.- Applications.- Intrusion Detection through Behavioral Data.- Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry.- Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with Kd-Trees.- Pump Failure Detection Using Support Vector Data Descriptions.- Data Mining for the Detection of Turning Points in Financial Time Series.- Computer-Assisted Classification of Legal Abstracts.- Sequential Control Logic Inferring Method from Observed Plant I/O Data.- Evaluating an Eye Screening Test.- Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.- Media Mining.- Exploiting Structural Information for Text Classification on the WWW.- Multi-agent Web Information Retrieval: Neural Network Based Approach.- Adaptive Information Filtering Algorithms.- A Conceptual Graph Approach for Video Data Representation and Retrieval.

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Book SynopsisDieses Buch stellt Methoden der Begrifflichen Wissensverarbeitung vor und präsentiert Anwendungen aus unterschiedlichen Praxisfeldern. Im Methodenteil wird in moderne Techniken der Begrifflichen Datenanalyse und Wissensverarbeitung eingeführt. Hierbei werden die mathematischen Grundlagen abgehandelt und durch zahlreiche Beispiele anschaulich gemacht. Der zweite Teil des Buches richtet sich verstärkt an potentielle Anwender. An ausgewählten Anwendungen wird die Vorgehensweise bei der Datenanalyse und dem Information Retrieval mit den Methoden der Begrifflichen Wissensverarbeitung vorgestellt und ihr Potential aufgezeigt.Table of ContentsI: Methoden der Begrifflichen Wissensverarbeitung.- Begriffe und Implikationen.- ConImp - Ein Programm zur Formalen Begriffsanalyse.- Ähnlichkeit als Distanz in Begriffsverbänden.- Datenanalyse mit Fuzzy-Begriffen.- Terminologische Merkmalslogik in der Formalen Begriffsanalyse.- II: Anwendungen der Begrifflichen Wissensverarbeitung.- Formale Begriffsanalyse im Software Engineering.- Zugriffskontrolle bei Programmsystemen und im Datenschutz mittels Formaler Begriffsanalyse.- Inhaltliche Erschließung des Bereichs 'Sozialorientierte Gestaltung von Informationstechnik' - Ein begriffsanalytischer Ansatz.- Wissensdarstellungen in Informationssystemen, Fragetypen und Anforderungen an Retrievalkomponenten.- Ein TOSCANA-Erkundungssystem zur Literatursuche.- Ein Erkundungssystem zum Baurecht: Methoden der Entwicklung eines TOSCANA-Systems.- Begriffliche Erkundung semantischer Strukturen von Sprechaktverben.- Grundwerte, Ziele und Maßnahmen in einem regionalen Krankenhaus - Eine Anwendung des Verfahrens GABEK.- Normen- und regelgeleitete internationale Kooperationen - Formale Begriffsanalyse in der Politikwissenschaft.- Entwicklung eines kontextuellen Methodenkonzeptes mit Hilfe der Formalen Begriffsanalyse an Beispielen zum Risikoverständnis.- Über Möglichkeiten der Formalen Begriffsanalyse in der Mathematischen Archäochemie.

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Book SynopsisThis book constitutes the thoroughly refereed joint post-proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments, MUSE 2012, held in Bristol, UK, in September 2012, and the Third International Workshop on Modeling Social Media, MSM 2012, held in Milwaukee, WI, USA, in June 2012. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. They cover a wide range of topics organized in three main themes: communities and group structure in ubiquitous social media; ubiquitous modeling and aspects of social interactions and influence.Table of ContentsHow to Carve up the World: Learning and Collaboration for Structure Recommendation.- A Topological Approach for Detecting Twitter Communities with Common Interests.- Using Geographic Cost Functions to Discover Vessel Itineraries from AIS Messages.- Social Media as a Source of Sensing to Study City Dynamics and Urban Social Behavior: Approaches, Models and Opportunities.- An Analysis of Interactions within and between Extreme Right Communities in Social Media.- Who will Interact with Whom? A Case-Study in Second Life Using Online Social Network and Location-Based Social Network Features to Predict Interactions between Users.- Identifying Influential Users by Their Postings in Social Networks.- Modeling a Web Forum Ecosystem into an Enriched Social Graph.

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Book SynopsisThis is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.Trade Review“The author of the book, Wil van der Aalst, is very knowledgeable in the area. … His research interests are workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. … I enjoyed reading the book and learned about process mining. It will be helpful to researchers and industry professionals working on fields related to business processes such as business intelligence and workflow management.” (Gulustan Dogan, Computing Reviews, March, 2017)Table of ContentsIntroduction.- Preliminaries.- From Event Logs to Process Models.- Beyond Process Discovery.- Putting Process Mining to Work.- Reflection.- Epilogue.

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Book SynopsisThis Data Guide is aimed at those engaged in the cycle of social science research, from applying for a research grant, through the data collection phase, and ultimately to preparation of the data for deposit in the DANS data archive, or any other data repository. This publication is an adaption of the 4th edition of the Guide to social science data preparation and archiving of 2009, published by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan in the United States. The publication is intended to help researchers manage and document their data to prepare them for archival deposit, as well as think more broadly about the types of digital content that should be deposited in an archive. DANS (Data Archiving and Networked Services) is the national organization in the Netherlands for storing and providing permanent access to research data from the humanities and social sciences. DANS comprises existing data archives but also works on further developments of the data infrastructure in new fields.Table of ContentsContents - 8 1. Introduction - 12 2. Proposal planning and writing phase - 16 3. Project start-up and data management phase - 22 4. Data collection and file creation phase - 26 5. Data analysis phase - 42 6. Final project phase – preparing data forsharing - 48 7. Data publishing - 52 References - 58 Contributors to the fourth edition - 60

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Book SynopsisBuild petabyte-scale data lakes using S3 and Lake Formation. Implement real-time streaming pipelines with Kinesis and Lambda. Design cost-optimized data warehouses using Amazon Redshift. Create modern data mesh architectures on AWS.

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Book SynopsisThis open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one.Table of ContentsChapter 1. Graded Relevance.- Chapter 2. Experiments on Cross-Language Information Retrieval using Comparable Corpora of Chinese, Japanese, and Korean Languages.- Chapter 3. Text Summarization Challenge.- Chapter 4. Challenges in Patent Information Retrieval.- Chapter 5. Multi-Modal Summarization.- Chapter 6. Opinion Analysis Corpora Across Languages.- Chapter 7. Patent Translation.- Chapter 8. Component-Based Evaluation for Question Answering.- Chapter 9. Temporal Information Access.- Chapter 10. SogouQ.- Chapter 11. Evaluation of Information Access with Smartphones.- Chapter 12. Mathematical Information Retrieval.- Chapter 13. Experiments in Lifelog Organisation and Retrieval at NTCIR.- Chapter 14. The Future of Information Retrieval Evaluation.

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Book SynopsisThis book gathers a collection of high-quality peer-reviewed research papers presented at International Conference on Cyber Intelligence and Information Retrieval (CIIR 2021), held at Institute of Engineering & Management, Kolkata, India during 20–21 May 2021. The book covers research papers in the field of privacy and security in the cloud, data loss prevention and recovery, high-performance networks, network security and cryptography, image and signal processing, artificial immune systems, information and network security, data science techniques and applications, data warehousing and data mining, data mining in dynamic environment, higher-order neural computing, rough set and fuzzy set theory, and nature-inspired computing techniques. Table of ContentsDTNMA: Identifying Routing Attacks in Delay-Tolerant Network.- Classification Framework for Fraud Detection Using Hidden Markov Model.- Analysis of the Beaufort Cipher Expansion Technique and Its Usage in Providing Data Security in Cloud.- Virtual Keyboard Using Image Processing & Computer Vision.- Next Step to the Future of Restaurants Through Artificial Intelligence and Facial Recognition.- A Comparative Study into Stock Market Prediction Through Various Sentiment Analysis Algorithms.- Bangla Document Categorization Using Deep RNN Model with Attention Mechanism.- Bangla Handwritten Digit Recognition.- A Comparative Study on Sentiment Analysis Influencing Word Embedding Using SVM and KNN.- COVID-19 Pandemic Diagnosis and Analysis Using Clinical Decision Support Systems.- Predictive Analysis of the Recovery Rate from Corona Virus(Covid-19).- Deep Learning Approaches for Spatio-Temporal Clues Modelling.- The Practical Enactment of Robotics and Artificial Intelligence Technologies in E-COMMERCE.- Comparative Analysis of Brain Tumor Segmentation with Fuzzy C-Means Using Multi-Core CPU and CUDA on GPU.- Multiregional Segmentation of High-Grade Glioma Using Modified Deep UNET Model with Edge-detected Multimodal MRI Images.

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