Managing Science

What is science? How is it performed? Is science only a method or is it also an institution? These are questions at the core of Managing Science, a handbook on how scientific research is conducted and its results disseminated. Knowledge creation occurs through scientific research in universities, industrial laboratories, and government agencies. Any knowledge management system needs to promote effective research processes to foster innovation, and, ultimately, to channel that innovation into economic competitiveness and wealth. However, science is a complicated topic. It includes both methodological aspects and organizational aspects, which have traditionally been discussed in isolation from each other. In Managing Science, Frederick Betz presents a holistic approach to science, incorporating both philosophical and practical elements, in a framework that integrates scientific method, content, administration and application. Illustrating all of the key concepts with illustrative case studies (both historical and contemporary, and from a wide spectrum of fields), Betz provides in-depth discussion of the process of science. He addresses the social, organizational, institutional, and infrastructural context through which research projects are designed and their results applied, along the path from experimentation to innovation to commercialization of new products, services, and processes. This practical approach to science is the foundation of today's knowledge-intensive and technology-enabled industries, and positions the management of science within the broader context of knowledge management and its implications for organizations, industries, and regional and national technology management policies. Managing Science will be an essential resource for students in all areas of research, industry scientists and R&D specialists, policymakers and university administrators, and anyone concerned with the application of research to economic growth and development.

Can technical paradigms help managers lead technical companies? In Managing and Leading for Science Professionals, Bertrand Liang explains that they can, as he explores real issues of importance for technical students and managers who want to move into leadership positions. A CEO with an MBA, Liang originally trained as a neurology and oncology clinician and later earned a PhD in molecular biology and genetics. In this book, he emphasizes what he wishes he had known as he advanced through the organization. His practitioner's point of view is perfectly suited to those who are moving, or want to move, from the technical side to the business side. Focusing on the experiences of scientists and engineers, he teaches ways to speak top management's language. His insights deliver essential knowledge, empowering technical staff to succeed using the skills they know best. Describes "what I wish I’d known" as a manager with a technical background Focuses on using skills other than risk analysis to make decisions Explores ways to lead and manage innovation, particularly in relation to executives' responsibilities, skills, and tolerance for risk

Leadership and management are general skills that apply in most walks of life, but in the scientific domain they require some special characteristics. Science thrives on challenge, whether it is the technical challenge of trying to do something which has not been done before or challenging a widely held but poorly supported hypothesis. Scientists are trained to challenge, and for the manager of science this can itself be a challenge. In the past, when science was on a much smaller scale and less subject to public scrutiny, a less formal 'back-of-the-envelope' management style was acceptable, but those days are long-gone. Science costs much more and is rightly more accountable. Excellent scientists, however, do not necessarily make good managers and may not make good leaders. Nevertheless, like all skills, leadership and management can be enhanced and developed and even instinctively good managers can improve. While the science of management and leadership is well developed, the management and leadership of science is less so. This book aims to introduce the working research scientist to the art and techniques of management and the skills necessary to be a good and effective manager and leader of science and scientists. This includes understanding the organization and functioning of scientific research establishments (universities, laboratories, research councils, etc.) and how to deal with the associated committee work, recruiting, and team building; how to deal with difficulties managing projects and handling risks. The approach is pragmatic not dogmatic. Leadership and management are people skills, and each person is different and needs to be treated differently. The focus is on the principle and practice. While the subject is serious, the approach is conversational, with anecdotes and practical examples.

Why we organize our personal digital data the way we do and how design of new PIM systems can help us manage our information more efficiently. Each of us has an ever-growing collection of personal digital data: documents, photographs, PowerPoint presentations, videos, music, emails and texts sent and received. To access any of this, we have to find it. The ease (or difficulty) of finding something depends on how we organize our digital stuff. In this book, personal information management (PIM) experts Ofer Bergman and Steve Whittaker explain why we organize our personal digital data the way we do and how the design of new PIM systems can help us manage our collections more efficiently. Bergman and Whittaker report that many of us use hierarchical folders for our personal digital organizing. Critics of this method point out that information is hidden from sight in folders that are often within other folders so that we have to remember the exact location of information to access it. Because of this, information scientists suggest other methods: search, more flexible than navigating folders; tags, which allow multiple categorizations; and group information management. Yet Bergman and Whittaker have found in their pioneering PIM research that these other methods that work best for public information management don't work as well for personal information management. Bergman and Whittaker describe personal information collection as curation: we preserve and organize this data to ensure our future access to it. Unlike other information management fields, in PIM the same user organizes and retrieves the information. After explaining the cognitive and psychological reasons that so many prefer folders, Bergman and Whittaker propose the user-subjective approach to PIM, which does not replace folder hierarchies but exploits these unique characteristics of PIM.

A unique "how-to" manual for the management of scientific laboratories This book presents a complete set of tools for the management of research and development laboratories and projects. With an emphasis on knowledge rather than profit as a measure of output and performance, the authors apply standard management principles and techniques to the needs of high-flux, open-ended, separately funded science and technology enterprises. They also propose the novel idea that failure, and incipient failure, is an important measure of an organization's potential. From the management of complex, round-the-clock, high-tech operations to strategies for long-term planning, Managing Science: Management for R&D Laboratories discusses how to build projects with the proper research and development, obtain and account for funding, and deal with rapidly changing technologies, facilities, and trends. The entire second part of the book is devoted to personnel issues and the impact of workplace behavior on the various functions of a knowledge-based organization. Drawing on four decades of involvement with the management of scientific laboratories, the authors thoroughly illustrate their philosophy with real-world examples from the physics field and provide tables and charts. Managers of scientific laboratories as well as scientists and engineers expecting to move into management will find Managing Science: Management for R&D Laboratories an invaluable practical guide.

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learnUnderstand the underlying problems of building a strong data science pipelineExplore the different tools for building and deploying data science solutionsHire, grow, and sustain a data science teamManage data science projects through all stages, from prototype to productionLearn how to use ModelOps to improve your data science pipelinesGet up to speed with the model testing techniques used in both development and production stagesWho this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.

Innovative technologies are changing the way research is performed, preserved, and communicated. Managing Scientific Information and Research Data explores how these technologies are used and provides detailed analysis of the approaches and tools developed to manage scientific information and data. Following an introduction, the book is then divided into 15 chapters discussing the changes in scientific communication; new models of publishing and peer review; ethics in scientific communication; preservation of data; discovery tools; discipline-specific practices of researchers for gathering and using scientific information; academic social networks; bibliographic management tools; information literacy and the information needs of students and researchers; the involvement of academic libraries in eScience and the new opportunities it presents to librarians; and interviews with experts in scientific information and publishing. Promotes innovative technologies for creating, sharing and managing scientific content Presents new models of scientific publishing, peer review, and dissemination of information Serves as a practical guide for researchers, students, and librarians on how to discover, filter, and manage scientific information Advocates for the adoption of unique author identifiers such as ORCID and ResearcherID Looks into new tools that make scientific information easy to discover and manage Shows what eScience is and why it is becoming a priority for academic libraries Demonstrates how Electronic Laboratory Notebooks can be used to record, store, share, and manage research data Shows how social media and the new area of Altmetrics increase researchers’ visibility and measure attention to their research Directs to sources for datasets Provides directions on choosing and using bibliographic management tools Critically examines the metrics used to evaluate research impact Aids strategic thinking and informs decision making

This book provides a timely analysis of the role that information-particularly scientific information-plays in the policy-making and decision-making processes in coastal and ocean management. It includes contributions from global experts in marine environmental science, marine policy, fisheries, public policy and administration, resource management