Stream Data Management

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Data Stream Management

Author : Lukasz Golab
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608452727
Total Pages : 65 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Data Stream Management by : Lukasz Golab

Download or read book Data Stream Management written by Lukasz Golab and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this lecture many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs). A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization. The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage. Table of Contents: Introduction / Data Stream Management Systems / Streaming Data Warehouses / Conclusions

Stream Data Management

Author : Nauman Chaudhry
Publisher : Springer
ISBN 13 : 9781441937384
Total Pages : 0 pages
Book Rating : 4.9/5 (373 download)

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Book Synopsis Stream Data Management by : Nauman Chaudhry

Download or read book Stream Data Management written by Nauman Chaudhry and published by Springer. This book was released on 2010-12-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.

Data Stream Management

Author : Minos Garofalakis
Publisher : Springer
ISBN 13 : 354028608X
Total Pages : 537 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Data Stream Management by : Minos Garofalakis

Download or read book Data Stream Management written by Minos Garofalakis and published by Springer. This book was released on 2016-07-11 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.

Stream Data Management

Author : Nauman Chaudhry
Publisher : Springer Science & Business Media
ISBN 13 : 0387252290
Total Pages : 179 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Stream Data Management by : Nauman Chaudhry

Download or read book Stream Data Management written by Nauman Chaudhry and published by Springer Science & Business Media. This book was released on 2005-09-19 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.

Stream Data Processing: A Quality of Service Perspective

Author : Sharma Chakravarthy
Publisher : Springer Science & Business Media
ISBN 13 : 0387710035
Total Pages : 341 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Stream Data Processing: A Quality of Service Perspective by : Sharma Chakravarthy

Download or read book Stream Data Processing: A Quality of Service Perspective written by Sharma Chakravarthy and published by Springer Science & Business Media. This book was released on 2009-04-09 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.

Machine Learning for Data Streams

Author : Albert Bifet
Publisher : MIT Press
ISBN 13 : 026254783X
Total Pages : 289 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Machine Learning for Data Streams by : Albert Bifet

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2023-05-09 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Real-Time & Stream Data Management

Author : Wolfram Wingerath
Publisher : Springer
ISBN 13 : 3030105555
Total Pages : 77 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Real-Time & Stream Data Management by : Wolfram Wingerath

Download or read book Real-Time & Stream Data Management written by Wolfram Wingerath and published by Springer. This book was released on 2019-01-02 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: While traditional databases excel at complex queries over historical data, they are inherently pull-based and therefore ill-equipped to push new information to clients. Systems for data stream management and processing, on the other hand, are natively pushoriented and thus facilitate reactive behavior. However, they do not retain data indefinitely and are therefore not able to answer historical queries. The book provides an overview over the different (push-based) mechanisms for data retrieval in each system class and the semantic differences between them. It also provides a comprehensive overview over the current state of the art in real-time databases. It sfirst includes an in-depth system survey of today's real-time databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the high-level classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field, it helps readers build a mental model of the available options.

Stream Processing with Apache Flink

Author : Fabian Hueske
Publisher : O'Reilly Media
ISBN 13 : 1491974265
Total Pages : 311 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Stream Processing with Apache Flink by : Fabian Hueske

Download or read book Stream Processing with Apache Flink written by Fabian Hueske and published by O'Reilly Media. This book was released on 2019-04-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Apache Flink, the open source framework that powers some of the world’s largest stream processing applications. With this practical book, you’ll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing. Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink’s DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them. Learn concepts and challenges of distributed stateful stream processing Explore Flink’s system architecture, including its event-time processing mode and fault-tolerance model Understand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperators Read data from and write data to external systems with exactly-once consistency Deploy and configure Flink clusters Operate continuously running streaming applications

Data Management and Query Processing in Semantic Web Databases

Author : Sven Groppe
Publisher : Springer Science & Business Media
ISBN 13 : 3642193579
Total Pages : 273 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Data Management and Query Processing in Semantic Web Databases by : Sven Groppe

Download or read book Data Management and Query Processing in Semantic Web Databases written by Sven Groppe and published by Springer Science & Business Media. This book was released on 2011-04-29 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (RDF), which provides a general method for conceptual descriptions for Web resources, and SPARQL, an RDF querying language. Recent examples of large RDF data with billions of facts include the UniProt comprehensive catalog of protein sequence, function and annotation data, the RDF data extracted from Wikipedia, and Princeton University’s WordNet. Clearly, querying performance has become a key issue for Semantic Web applications. In his book, Groppe details various aspects of high-performance Semantic Web data management and query processing. His presentation fills the gap between Semantic Web and database books, which either fail to take into account the performance issues of large-scale data management or fail to exploit the special properties of Semantic Web data models and queries. After a general introduction to the relevant Semantic Web standards, he presents specialized indexing and sorting algorithms, adapted approaches for logical and physical query optimization, optimization possibilities when using the parallel database technologies of today’s multicore processors, and visual and embedded query languages. Groppe primarily targets researchers, students, and developers of large-scale Semantic Web applications. On the complementary book webpage readers will find additional material, such as an online demonstration of a query engine, and exercises, and their solutions, that challenge their comprehension of the topics presented.

Fundamentals of Stream Processing

Author : Henrique C. M. Andrade
Publisher : Cambridge University Press
ISBN 13 : 1107434009
Total Pages : 559 pages
Book Rating : 4.1/5 (74 download)

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Book Synopsis Fundamentals of Stream Processing by : Henrique C. M. Andrade

Download or read book Fundamentals of Stream Processing written by Henrique C. M. Andrade and published by Cambridge University Press. This book was released on 2014-02-13 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.

Data Streams

Author : S. Muthukrishnan
Publisher : Now Publishers Inc
ISBN 13 : 193301914X
Total Pages : 136 pages
Book Rating : 4.9/5 (33 download)

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Book Synopsis Data Streams by : S. Muthukrishnan

Download or read book Data Streams written by S. Muthukrishnan and published by Now Publishers Inc. This book was released on 2005 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.

Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing

Author : Simon James Fong
Publisher : Springer Nature
ISBN 13 : 981156695X
Total Pages : 228 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing by : Simon James Fong

Download or read book Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing written by Simon James Fong and published by Springer Nature. This book was released on 2020-08-25 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.

Streaming Systems

Author : Tyler Akidau
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491983825
Total Pages : 391 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Streaming Systems by : Tyler Akidau

Download or read book Streaming Systems written by Tyler Akidau and published by "O'Reilly Media, Inc.". This book was released on 2018-07-16 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

Big Data Management and Analysis for Cyber Physical Systems

Author : Loon Ching Tang
Publisher : Springer Nature
ISBN 13 : 3031175484
Total Pages : 208 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Big Data Management and Analysis for Cyber Physical Systems by : Loon Ching Tang

Download or read book Big Data Management and Analysis for Cyber Physical Systems written by Loon Ching Tang and published by Springer Nature. This book was released on 2022-09-23 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of selected and peer-reviewed papers presented at 2022 4th International Conference on Big Data Engineering and Technology (BDET), held during April 22–24, 2022, in Singapore. As IT infrastructure and data management technologies have become critical assets and capabilities for today’s enterprises, this book aims to be part of the effort in contributing to their development. In particular, the BDET conference series aims to provide the much needed forum for researchers and practitioners across the world who are actively engaged in advancing research and raising awareness of the many challenges in the diverse field of big data engineering and technology to share their research outcomes and bounce ideas off their international colleagues. Over the last few years, the conference series has brought together the latest developments of novel theory in big data, algorithm and applications, emerging standards for big data, big data infrastructure, MapReduce and cloud computing, big data visualization, big data curation and management, big data semantics, scientific discovery and intelligence, which collectively form parts of the cyber-physical systems of interest. It is hoped that the book will prove useful to students, researchers, and professionals working in the field of big data engineering and applications in cyber-physical systems.

Frontiers in Massive Data Analysis

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 191 pages
Book Rating : 4.3/5 (92 download)

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Book Synopsis Frontiers in Massive Data Analysis by : National Research Council

Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Scientific Data Management

Author : Arie Shoshani
Publisher : CRC Press
ISBN 13 : 1420069810
Total Pages : 592 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Scientific Data Management by : Arie Shoshani

Download or read book Scientific Data Management written by Arie Shoshani and published by CRC Press. This book was released on 2009-12-16 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping

Key Technologies for Data Management

Author : Howard Williams
Publisher : Springer Science & Business Media
ISBN 13 : 3540223827
Total Pages : 277 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Key Technologies for Data Management by : Howard Williams

Download or read book Key Technologies for Data Management written by Howard Williams and published by Springer Science & Business Media. This book was released on 2004-06-25 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st British National Conference on Databases, BNCOD 2004, held in Edinburgh, Scotland, UK in July 2004. The 21 revised full papers presented together with an invited paper and the abstract of an invited talk were carefully reviewed and selected from more than 70 submissions. The papers are organized in topical sections on data streams, integration and heterogeneity, data analytics and manipulation, XML, interfaces and visualization, spatial data, and TLAD workshop papers.