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This book is the third of a three-part series on taxonomies, and covers putting your taxonomy into use in as many ways as possible to maximize retrieval for your users. Chapter 1 suggests several items to research and consider before you start your implementation and integration process. It explores the different pieces of software that you will need for your system and what features to look for in each. Chapter 2 launches with a discussion of how taxonomy terms can be used within a workflow, connecting twöor more¿taxonomies, and intelligent coordination of platforms and taxonomies. Microsoft SharePoint is a widely used and popular program, and I consider their use of taxonomies in this chapter. Following that is a discussion of taxonomies and semantic integration and then the relationship between indexing and the hierarchy of a taxonomy. Chapter 3 (¿How is a Taxonomy Connected to Search?¿) provides discussions and examples of putting taxonomies into use in practical applications. Itdiscusses displaying content based on search, how taxonomy is connected to search, using a taxonomy to guide a searcher, tools for search, including search engines, crawlers and spiders, and search software, the parts of a search-capable system, and then how to assemble that search-capable system. This chapter also examines how to measure quality in search, the different kinds of search, and theories on search from several famous theoreticians¿two from the 18th and 19th centuries, and two contemporary. Following that is a section on inverted files, parsing, discovery, and clustering. While you probably don¿t need a comprehensive understanding of these concepts to build a solid, workable system, enough information is provided for the reader to see how they fit into the overall scheme. This chapter concludes with a look at faceted search and some possibilities for search interfaces. Chapter 4, ¿Implementing a Taxonomy in a Database or on a Website,¿ starts where many content systems really should¿with the authors, or at least the people who create the content. This chapter discusses matching up various groups of related data to form connections, data visualization and text analytics, and mobile and e-commerce applications for taxonomies. Finally, Chapter 5 presents some educated guesses about the future of knowledge organization. Table of Contents: List of Figures / Preface / Acknowledgments / On Your Mark, Get Ready ¿. WAIT! Things to Know Before You Start the Implementation Step / Taxonomy and Thesaurus Implementation / How is a Taxonomy Connected to Search? / Implementing a Taxonomy in a Database or on a Website / What Lies Ahead for Knowledge Organization? / Glossary / End Notes / Author Biography

We are well into a second age of digital information. Our information is moving from the desktop to the laptop to the "palmtop" and up into an amorphous cloud on the Web. How can one manage both the challenges and opportunities of this new world of digital information? What does the future hold? This book provides an important update on the rapidly expanding field of personal information management (PIM). Part I (Always and Forever) introduces the essentials of PIM. Information is personal for many reasons. It's the information on our hard drives we couldn't bear to lose. It's the information about us that we don't want to share. It's the distracting information demanding our attention even as we try to do something else. It's the information we don't know about but need to. Through PIM, we control personal information. We integrate information into our lives in useful ways. We make it "ours." With basics established, Part I proceeds to explore a critical interplay between personal information "always" at hand through mobile devices and "forever" on the Web. How does information stay "ours" in such a world?Part II (Building Places of Our Own for Digital Information) will be available in the Summer of 2012, and will consist of the following chapters:Chapter 5. Technologies to eliminate PIM?: We have seen astonishing advances in the technologies of information management -- in particular, to aid in the storing, structuring and searching of information. These technologies will certainly change the way we do PIM; will they eliminate the need for PIM altogether?Chapter 6. GIM and the social fabric of PIM: We don't (and shouldn't) manage our information in isolation. Group information management (GIM) -- especially the kind practiced more informally in households and smaller project teams -- goes hand in glove with good PIM.Chapter 7. PIM by design: Methodologies, principles, questions and considerations as we seek to understand PIM better and to build PIM into our tools, techniques and training.Chapter 8. To each of us, our own.: Just as we must each be a student of our own practice of PIM, we must also be a designer of this practice. This concluding chapter looks at tips, traps and tradeoffs as we work to build a practice of PIM and "places" of our own for personal information.Table of Contents: A New Age of Information / The Basics of PIM / Our Information, Always at Hand / Our Information, Forever on the Web

Everybody knows what relevance is. It is a "ya'know" notion, concept, ideäno need to explain whatsoever. Searching for relevant information using information technology (IT) became a ubiquitous activity in contemporary information society. Relevant information means information that pertains to the matter or problem at hand¿it is directly connected with effective communication. The purpose of this book is to trace the evolution and with it the history of thinking and research on relevance in information science and related fields from the human point of view. The objective is to synthesize what we have learned about relevance in several decades of investigation about the notion in information science. This book deals with how people deal with relevance¿it does not cover how systems deal with relevance; it does not deal with algorithms. Spurred by advances in information retrieval (IR) and information systems of various kinds in handling of relevance, a number of basic questionsare raised: But what is relevance to start with? What are some of its properties and manifestations? How do people treat relevance? What affects relevance assessments? What are the effects of inconsistent human relevance judgments on tests of relative performance of different IR algorithms or approaches? These general questions are discussed in detail.

Let us start with a simple scenario: a man asks a woman "e;how high is Mount Everest?"e; The woman replies "e;29,029 feet."e; Nothing could be simpler. Now let us suppose that rather than standing in a room, or sitting on a bus, the man is at his desk and the woman is 300 miles away with the conversation taking place using e-mail. Still simple? Certainly--it happens every day. So why all the bother about digital (virtual, electronic, chat, etc.) reference?If the man is a pilot flying over Mount Everest, the answer matters. If you are a lawyer going to court, the identity of the woman is very important. Also, if you ever want to find the answer again, how that transaction took place matters a lot. Digital reference is a deceptively simple concept on its face: "e;the incorporation of human expertise into the information system."e; This lecture seeks to explore the question of how human expertise is incorporated into a variety of information systems, from libraries, to digital libraries, to information retrieval engines, to knowledge bases. What we learn through this endeavor, begun primarily in the library context, is that the models, methods, standards, and experiments in digital reference have wide applicability. We also catch a glimpse of an unfolding future in which ubiquitous computing makes the identification, interaction, and capture of expertise increasingly important. It is a future that is much more complex than we had anticipated. It is a future in which documents and artifacts are less important than the contexts of their creation and use. Table of Contents: Defining Reference in a Digital Age / Conversations / Digital Reference in Practice / Digital Reference an a New Future / Conclusion

As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world. Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks

We live in an information age that requires us, more than ever, to represent, access, and use information. Over the last several decades, we have developed a modern science and technology for information retrieval, relentlessly pursuing the vision of a "e;memex"e; that Vannevar Bush proposed in his seminal article, "e;As We May Think."e;Faceted search plays a key role in this program. Faceted search addresses weaknesses of conventional search approaches and has emerged as a foundation for interactive information retrieval. User studies demonstrate that faceted search provides more effective information-seeking support to users than best-first search. Indeed, faceted search has become increasingly prevalent in online information access systems, particularly for e-commerce and site search. In this lecture, we explore the history, theory, and practice of faceted search. Although we cannot hope to be exhaustive, our aim is to provide sufficient depth and breadth to offer a useful resource to both researchers and practitioners. Because faceted search is an area of interest to computer scientists, information scientists, interface designers, and usability researchers, we do not assume that the reader is a specialist in any of these fields. Rather, we offer a self-contained treatment of the topic, with an extensive bibliography for those who would like to pursue particular aspects in more depth. Table of Contents: I. Key Concepts / Introduction: What Are Facets? / Information Retrieval / Faceted Information Retrieval / II. Research and Practice / Academic Research / Commercial Applications / III. Practical Concerns / Back-End Concerns / Front-End Concerns / Conclusion / Glossary

This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References

The design space of information services evolved from seminal works through a set of prototypical hypermedia systems and matured in open and widely accessible web-based systems. The original concepts of hypermedia systems are now expressed in different forms and shapes. The first works on hypertext invented the term itself, laid out the foundational concept of association or link, and highlighted navigation as the core paradigm for the future information systems. The first engineered systems demonstrated architectural requirements and models and fostered the emergence of the conceptual model related with the information systems and the information design. The artifacts for interaction, navigation, and search, grew from the pioneering systems. Multimedia added a new dimension to hypertext, and mutated the term into hypermedia. The adaptation of the primitive models and mechanisms to the space of continuous media led to a further conceptual level and to the reinvention of information design methods. Hypermedia systems also became an ideal space for collaboration and cooperative work. Information access and sharing, and group work were enabled and empowered by distributed hypermedia systems. As with many technologies, a winning technical paradigm, in our case the World Wide Web, concentrated the design options, the architectural choices and the interaction and navigation styles. Since the late nineties, the Web became the standard framework for hypermedia systems, and integrated a large number of the initial concepts and techniques. Yet, other paths are still open. This lecture maps a simple "e;genome"e; of hypermedia systems, based on an initial survey of primitive systems that established architectural and functional characteristics, or traits. These are analyzed and consolidated using phylogenetic analysis tools, to infer families of systems and evolution opportunities. This method may prove to be inspiring for more systematic perspectives of technological landscapes. Table of Contents: Introduction / Original Visions and Concepts / Steps in the Evolution / Information and Structured Documents / Web-Based Environments / Some Research Trends / A Framework of Traits / A Phylogenetic Analysis / Conclusion

Developments over the last twenty years have fueled considerable speculation about the future of the book and of reading itself. This book begins with a gloss over the history of electronic books, including the social and technical forces that have shaped their development. The focus then shifts to reading and how we interact with what we read: basic issues such as legibility, annotation, and navigation are examined as aspects of reading that ebooks inherit from their print legacy. Because reading is fundamentally communicative, I also take a closer look at the sociality of reading: how we read in a group and how we share what we read. Studies of reading and ebook use are integrated throughout the book, but Chapter 5 "e;goes meta"e; to explore how a researcher might go about designing his or her own reading-related studies. No book about ebooks is complete without an explicit discussion of content preparation, i.e., how the electronic book is written. Hence, Chapter 6 delves into the underlying representation of ebooks and efforts to create and apply markup standards to them. This chapter also examines how print genres have made the journey to digital and how some emerging digital genres might be realized as ebooks. Finally, Chapter 7 discusses some beyond-the-book functionality: how can ebook platforms be transformed into portable personal libraries? In the end, my hope is that by the time the reader reaches the end of this book, he or she will feel equipped to perform the next set of studies, write the next set of articles, invent new ebook functionality, or simply engage in a heated argument with the stranger in seat 17C about the future of reading. Table of Contents: Preface / Figure Credits / Introduction / Reading / Interaction / Reading as a Social Activity / Studying Reading / Beyond the Book / References / Author Biography

This lecture introduces fundamental principles of online multiplayer games, primarily massively multiplayer online role-playing games (MMORPGs), suitable for students and faculty interested both in designing games and in doing research on them. The general focus is human-centered computing, which includes many human-computer interaction issues and emphasizes social computing, but also, looks at how the design of socio-economic interactions extends our traditional notions of computer programming to cover human beings as well as machines. In addition, it demonstrates a range of social science research methodologies, both quantitative and qualitative, that could be used by students for term papers, or by their professors for publications. In addition to drawing upon a rich literature about these games, this lecture is based on thousands of hours of first-hand research experience inside many classic examples, including World of Warcraft, The Matrix Online, Anarchy Online, Tabula Rasa, Entropia Universe, Dark Age of Camelot, Age of Conan, Lord of the Rings Online, Tale in the Desert, EVE Online, Star Wars Galaxies, Pirates of the Burning Sea, and the non-game virtual world Second Life. Among the topics covered are historical-cultural origins of leading games, technical constraints that shape the experience, rolecoding and social control, player personality and motivation, relationships with avatars and characters, virtual professions and economies, social relations inside games, and the implications for the external society. Table of Contents: Introduction / Historical-Cultural Origins / Technical Constraints / Rolecoding and Social Control / Personality and Motivation / Avatars and Characters / Virtual Professions and Economies / Social Relations Inside Games / Implications for External Society

At its very core multimedia information retrieval means the process of searching for and finding multimedia documents; the corresponding research field is concerned with building the best possible multimedia search engines. The intriguing bit here is that the query itself can be a multimedia excerpt: For example, when you walk around in an unknown place and stumble across an interesting landmark, would it not be great if you could just take a picture with your mobile phone and send it to a service that finds a similar picture in a database and tells you more about the building -- and about its significance, for that matter? This book goes further by examining the full matrix of a variety of query modes versus document types. How do you retrieve a music piece by humming? What if you want to find news video clips on forest fires using a still image? The text discusses underlying techniques and common approaches to facilitate multimedia search engines from metadata driven retrieval, via piggy-back text retrieval where automated processes create text surrogates for multimedia, automated image annotation and content-based retrieval. The latter is studied in great depth looking at features and distances, and how to effectively combine them for efficient retrieval, to a point where the readers have the ingredients and recipe in their hands for building their own multimedia search engines. Supporting users in their resource discovery mission when hunting for multimedia material is not a technological indexing problem alone. We look at interactive ways of engaging with repositories through browsing and relevance feedback, roping in geographical context, and providing visual summaries for videos. The book concludes with an overview of state-of-the-art research projects in the area of multimedia information retrieval, which gives an indication of the research and development trends and, thereby, a glimpse of the future world. Table of Contents: What is Multimedia Information Retrieval? / Basic Multimedia Search Technologies / Content-based Retrieval in Depth / Added Services / Multimedia Information Retrieval Research / Summary

Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.

Knowledge Management (KM) is an effort to increase useful knowledge in the organization. It is a natural outgrowth of late twentieth century movements to make organizational management and operations more effective, of higher quality, and more responsive to constituents in a rapidly changing global environment. This document traces the evolution of KM in organizations, summarizing the most influential research and literature in the field. It also presents an overview of selected common and current practices in knowledge management, including the relationship between knowledge management and decision making, with the intention of making a case for KM as a series of processes and not necessarily a manipulation of things. The final section highlights the use of social networking and commonly adopted Web applications to increase the value of social capital and to connect practitioners with clients and colleagues. Table of Contents: Introduction / Background Bibliographic Analysis / Theorizing Knowledge in Organizations / Conceptualizing Knowledge Emergence / Knowledge "e;Acts"e; / Knowledge Management in Practice / Knowledge Management Issues / Knowledge Management and Decision Making / Social Network Analysis and KM / Implications for the Future / Conclusion

This is the second book based on the 5S (Societies, Scenarios, Spaces, Structures, Streams) approach to digital libraries (DLs). Leveraging the first volume, on Theoretical Foundations, we focus on the key issues of evaluation and integration. These cross-cutting issues serve as a bridge for those interested in DLs, connecting the introduction and formal discussion in the first book, with the coverage of key technologies in the third book, and of illustrative applications in the fourth book. These two topics have central importance in the DL field, allowing it to be treated scientifically as well as practically. In the scholarly world, we only really understand something if we know how to measure and evaluate it. In the Internet era of distributed information systems, we only can be practical at scale if we integrate across both systems and their associated content. Evaluation of DLs must take place atmultiple levels,so we can address the different entities and their associated measures. Thus, for digital objects, we assess accessibility, pertinence, preservability, relevance, significance, similarity, and timeliness. Other measures are specific to higher-level constructs like metadata, collections, catalogs, repositories, and services.We tie these together through a case study of the 5SQual tool, which we designed and implemented to perform an automatic quantitative evaluation of DLs. Thus, across the Information Life Cycle, we describe metrics and software useful to assess the quality of DLs, and demonstrate utility with regard to representative application areas: archaeology and education. Though integration has been a challenge since the earliest work on DLs, we provide the first comprehensive 5S-based formal description of the DL integration problem, cast in the context of related work. Since archaeology is a fundamentally distributed enterprise, we describe ETANADL, for integrating Near Eastern Archeology sites and information. Thus, we show how 5S-based modeling can lead to integrated services and content. While the first book adopts a minimalist and formal approach to DLs, and provides a systematic and functional method to design and implement DL exploring services, here we broaden to practical DLs with richer metamodels, demonstrating the power of 5S for integration and evaluation.

Digital libraries (DLs) have evolved since their launch in 1991 into an important type of information system, with widespread application. This volume advances that trend further by describing new research and development in the DL field that builds upon the 5S (Societies, Scenarios, Spaces, Structures, Streams) framework, which is discussed in three other DL volumes in this series.While the 5S framework may be used to describe many types of information systems, and is likely to have even broader utility and appeal, we focus here on digital libraries. Drawing upon six (Akbar, Kozievitch, Leidig, Li, Murthy, Park) completed and two (Chen, Fouh) in-process dissertations, as well as the efforts of collaborating researchers, and scores of related publications, presentations, tutorials, and reports, this book demonstrates the applicability of 5S in five digital library application areas, that also have importance in the context of the WWW, Web 2.0, and innovative information systems. By integrating surveys of the state-of-the-art, newresearch, connections with formalization, case studies, and exercises/projects, this book can serve as a textbook for those interested in computing, information, and/or library science. Chapter 1 focuses on images, explaining how they connect with information retrieval, in the context of CBIR systems. Chapter 2 gives two case studies of DLs used in education, which is one of the most common applications of digital libraries. Chapter 3 covers social networks, which are at the heart of work onWeb 2.0, explaining the construction and use of deduced graphs, that can enhance retrieval and recommendation. Chapter 4 demonstrates the value of DLs in eScience, focusing, in particular, on cyber-infrastructure for simulation. Chapter 5 surveys geospatial information in DLs, with a case study on geocoding. Given this rich content, we trust that any interested in digital libraries, or in related systems, will find this volume to be motivating, intellectually satisfying, and useful. We hope it will help move digital libraries forward into a science as well as a practice. We hope it will help build community that will address the needs of the next generation of DLs.

User engagement refers to the quality of the user experience that emphasizes the positive aspects of interacting with an online application and, in particular, the desire to use that application longer and repeatedly. User engagement is a key concept in the design of online applications (whether for desktop, tablet or mobile), motivated by the observation that successful applications are not just used, but are engaged with. Users invest time, attention, and emotion in their use of technology, and seek to satisfy pragmatic and hedonic needs. Measurement is critical for evaluating whether online applications are able to successfully engage users, and may inform the design of and use of applications. User engagement is a multifaceted, complex phenomenon; this gives rise to a number of potential measurement approaches. Common ways to evaluate user engagement include using self-report measures, e.g., questionnaires; observational methods, e.g. facial expression analysis, speech analysis; neuro-physiological signal processing methods, e.g., respiratory and cardiovascular accelerations and decelerations, muscle spasms; and web analytics, e.g., number of site visits, click depth. These methods represent various trade-offs in terms of the setting (laboratory versus ``in the wild''), object of measurement (user behaviour, affect or cognition) and scale of data collected. For instance, small-scale user studies are deep and rich, but limited in terms of generalizability, whereas large-scale web analytic studies are powerful but negate users' motivation and context. The focus of this book is how user engagement is currently being measured and various considerations for its measurement. Our goal is to leave readers with an appreciation of the various ways in which to measure user engagement, and their associated strengths and weaknesses. We emphasize the multifaceted nature of user engagement and the unique contextual constraints that come to bear upon attempts to measure engagement in different settings, and across different user groups and web domains. At the same time, this book advocates for the development of ``good'' measures and good measurement practices that will advance the study of user engagement and improve our understanding of this construct, which has become so vital in our wired world.

This book introduces fundamentals of information communication. At first, concepts and characteristics of information and information communication are summarized. And then five classic models of information communication are introduced. The mechanisms and fundamental laws of the information transmission process are also discussed. In order to realize information communication, impediments in information communication process are identified and analyzed. For the purpose of investigating implications of Internet information communication, patterns and characteristics of information communication in the Internet and Web 2.0 environment are also analyzed. In the end, case studies are provided for readers to understand the theory.

The study of people, information, and communication technologies and the contexts in which these technologies are designed, implemented, and used has long interested scholars in a wide range of disciplines, including the social study of computing, science and technology studies, the sociology of technology, and management information systems. As ICT use has spread from organizations into the larger world, these devices have become routine information appliances in our social lives, researchers have begun to ask deeper and more profound questions about how our lives have become bound up with technologies. A common theme running through this research is that the relationships among people, technology, and context are dynamic, complex, and critically important to understand. This book explores social informatics (SI), one important and dynamic approach that researchers have used to study these complex relationships. SI is "e;the interdisciplinary study of the design, uses and consequences of information technology that takes into account their interaction with institutional and cultural contexts"e; (Kling 1998, p. 52; 1999). SI provides flexible frameworks to explore complex and dynamic socio-technical interactions. As a domain of study related largely by common vocabulary and conclusions, SI critically examines common conceptions of and expectations for technology, by providing contextual evidence. This book describes the evolution of SI research and identifies challenges and opportunities for future research. In what might be seen as an example of socio-technical "e;natural selection,"e; SI emerged in six different locations during the 1980s and 1990s: Norway, Slovenia, Japan, the former Soviet Union, the UK and, last, the U.S. As SI evolved, the version popularized in the US became globally dominant. The evolution of SI is presented in five stages: emergence, foundational, expansion, coherence, and transformation. Thus, we divide SI research into five major periods: an emergence stage, when various forms of SI emerged around the globe, an early period of foundational work which grounds SI (Pre-1990s), a period of expansion (1990s), a robust period of coherence and influence by Rob Kling (2000-2005), and a period of transformation (2006-present). Following the description of the five periods we discuss the evolution throughout the periods under five sections: principles, concepts, approaches, topics, and findings. Principles refer to the overarching motivations and labels employed to describe scholarly work. Approaches describe the theories, frameworks, and models employed in analysis, emphasizing the multi-disciplinary and interdisciplinary nature of SI. Concepts include specific processes, entities, themes, and elements of discourse within a given context, revealing a shared SI language surrounding change, complexity, consequences, and social elements of technology. Topics label the issues and general domains studied within social informatics, ranging from scholarly communication to online communities to information systems. Findings from seminal SI works illustrate growing insights over time and demonstrate how repeatable explanations unify SI. In the concluding remarks, we raise questions about the possible futures of SI research.

Collaboration among scholars has always been recognized as a fundamental feature of scientific discovery. The ever-increasing diversity among disciplines and complexity of research problems makes it even more compelling to collaborate in order to keep up with the fast pace of innovation and advance knowledge. Along with the rapidly developing Internet communication technologies and the increasing popularity of the social web, we have observed many important developments of scholarly collaboration on the academic social web. In this book, we review the rapid transformation of scholarly collaboration on various academic social web platforms and examine how these platforms have facilitated academics throughout their research lifecycle-from forming ideas, collecting data, and authoring articles to disseminating findings. We refer to the term "e;academic social web platforms"e; in this book as a category of Web 2.0 tools or online platforms (such as CiteULike, Mendeley, Academia.edu, and ResearchGate) that enable and facilitate scholarly information exchange and participation. We will also examine scholarly collaboration behaviors including sharing academic resources, exchanging opinions, following each other's research, keeping up with current research trends, and, most importantly, building up their professional networks. Inspired by the model developed Olson et al. [2000] on factors for successful scientific collaboration, our examination of the status of scholarly collaboration on the academic social web has four emphases: technology readiness, coupling work, building common ground, and collaboration readiness. Finally, we talk about the insights and challenges of all these online scholarly collaboration activities imposed on the research communities who are engaging in supporting online scholarly collaboration. This book aims to help researchers and practitioners understand the development of scholarly collaboration on the academic social web, and to build up an active community of scholars who are interested in this topic.

With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. Learning across multiple social networks brings opportunities to new services and applications as well as new insights on user online behaviors, yet it raises tough challenges: (1) How can we map different social network accounts to the same social users? (2) How can we complete the item-wise and block-wise missing data? (3) How can we leverage the relatedness among sources to strengthen the learning performance? And (4) How can we jointly model the dual-heterogeneities: multiple tasks exist for the given application and each task has various features from multiple sources? These questions have been largely unexplored to date. We noticed this timely opportunity, and in this book we present some state-of-the-art theories and novel practical applications on aggregation of multiple social networks. In particular, we first introduce multi-source dataset construction. We then introduce how to effectively and efficiently complete the item-wise and block-wise missing data, which are caused by the inactive social users in some social networks. We next detail the proposed multi-source mono-task learning model and its application in volunteerism tendency prediction. As a counterpart, we also present a mono-source multi-task learning model and apply it to user interest inference. We seamlessly unify these models with the so-called multi-source multi-task learning, and demonstrate several application scenarios, such as occupation prediction. Finally, we conclude the book and figure out the future research directions in multiple social network learning, including the privacy issues and source complementarity modeling. This is preliminary research on learning from multiple social networks, and we hope it can inspire more active researchers to work on this exciting area. If we have seen further it is by standing on the shoulders of giants.

Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.

A trustworthy repository provides assurance in the form of management documents, event logs, and audit trails that digital objects are being managed correctly. The assurance includes plans for the sustainability of the repository, the accession of digital records, the management of technology evolution, and the mitigation of the risk of data loss. A detailed assessment is provided by the ISO-16363:2012 standard, "e;Space data and information transfer systems-Audit and certification of trustworthy digital repositories."e; This book examines whether the ISO specification for trustworthiness can be enforced by computer actionable policies. An implementation of the policies is provided and the policies are sorted into categories for procedures to manage externally generated documents, specify repository parameters, specify preservation metadata attributes, specify audit mechanisms for all preservation actions, specify control of preservation operations, and control preservation properties as technology evolves. An application of the resulting procedures is made to enforce trustworthiness within National Science Foundation data management plans.

In recent years there has been an increasing demand for research evaluation within universities and other research-based organisations. In parallel, there has been an increasing recognition that traditional citation-based indicators are not able to reflect the societal impacts of research and are slow to appear. This has led to the creation of new indicators for different types of research impact as well as timelier indicators, mainly derived from the Web. These indicators have been called altmetrics, webometrics or just web metrics. This book describes and evaluates a range of web indicators for aspects of societal or scholarly impact, discusses the theory and practice of using and evaluating web indicators for research assessment and outlines practical strategies for obtaining many web indicators. In addition to describing impact indicators for traditional scholarly outputs, such as journal articles and monographs, it also covers indicators for videos, datasets, software and other non-standard scholarly outputs. The book describes strategies to analyse web indicators for individual publications as well as to compare the impacts of groups of publications. The practical part of the book includes descriptions of how to use the free software Webometric Analyst to gather and analyse web data. This book is written for information science undergraduate and Master's students that are learning about alternative indicators or scientometrics as well as Ph.D. students and other researchers and practitioners using indicators to help assess research impact or to study scholarly communication.

Rapid technological changes and availability of news anywhere and at any moment have changed how people seek out news. Increasingly, consumers no longer take deliberate actions to read the news, instead stumbling upon news online. While the emergence of serendipitous news discovery online has been recognized in the literature, there is a limited understanding about how people experience this behavior. Based on the mixed method study that investigated online news reading behavior of residents in a Midwestern U.S. town, we explore how people accidentally discover news when engaged in various online activities. Employing the grounded theory approach, we define Incidental Exposure to Online News (IEON) as individual's memorable experiences of chance encounters with interesting, useful, or surprising news while using the Internet for news browsing or for non-news-related online activities, such as checking email or visiting social networking sites. The book presents a conceptual framework of IEON that advances research and an understanding of serendipitous news discovery from people's holistic experiences of news consumption in their everyday lives. The proposed IEON Process Model identifies key steps in an IEON experience that could help news reporters and developers of online news platforms create innovative storytelling and design strategies to catch consumers' attention during their online activities. Finally, this book raises important methodological questions for further investigation: how should serendipitous news discovery be studied, measured, and observed, and what are the essential elements that differentiate this behavior from other types of online news consumption and information behaviors?