The Future Of Scientific Knowledge Discovery In Open Networked Environments

Digital technologies and networks are now part of everyday work in the sciences, and have enhanced access to and use of scientific data, information, and literature significantly. They offer the promise of accelerating the discovery and communication of knowledge, both within the scientific community and in the broader society, as scientific data and information are made openly available online. The focus of this project was on computer-mediated or computational scientific knowledge discovery, taken broadly as any research processes enabled by digital computing technologies. Such technologies may include data mining, information retrieval and extraction, artificial intelligence, distributed grid computing, and others. These technological capabilities support computer-mediated knowledge discovery, which some believe is a new paradigm in the conduct of research. The emphasis was primarily on digitally networked data, rather than on the scientific, technical, and medical literature. The meeting also focused mostly on the advantages of knowledge discovery in open networked environments, although some of the disadvantages were raised as well. The workshop brought together a set of stakeholders in this area for intensive and structured discussions. The purpose was not to make a final declaration about the directions that should be taken, but to further the examination of trends in computational knowledge discovery in the open networked environments, based on the following questions and tasks: 1. Opportunities and Benefits: What are the opportunities over the next 5 to 10 years associated with the use of computer-mediated scientific knowledge discovery across disciplines in the open online environment? What are the potential benefits to science and society of such techniques? 2. Techniques and Methods for Development and Study of Computer-mediated Scientific Knowledge Discovery: What are the techniques and methods used in government, academia, and industry to study and understand these processes, the validity and reliability of their results, and their impact inside and outside science? 3. Barriers: What are the major scientific, technological, institutional, sociological, and policy barriers to computer-mediated scientific knowledge discovery in the open online environment within the scientific community? What needs to be known and studied about each of these barriers to help achieve the opportunities for interdisciplinary science and complex problem solving? 4. Range of Options: Based on the results obtained in response to items 1-3, define a range of options that can be used by the sponsors of the project, as well as other similar organizations, to obtain and promote a better understanding of the computer-mediated scientific knowledge discovery processes and mechanisms for openly available data and information online across the scientific domains. The objective of defining these options is to improve the activities of the sponsors (and other similar organizations) and the activities of researchers that they fund externally in this emerging research area. The Future of Scientific Knowledge Discovery in Open Networked Environments: Summary of a Workshop summarizes the responses to these questions and tasks at hand.

This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.

How the internet and powerful online tools are democratizing and accelerating scientific discovery Reinventing Discovery argues that we are living at the dawn of the most dramatic change in science in more than three hundred years. This change is being driven by powerful cognitive tools, enabled by the internet, which are greatly accelerating scientific discovery. There are many books about how the internet is changing business, the workplace, or government. But this is the first book about something much more fundamental: how the internet is transforming our collective intelligence and our understanding of the world. From the collaborative mathematicians of the Polymath Project to the amateur astronomers of Galaxy Zoo, Reinventing Discovery tells the exciting story of the unprecedented new era in networked science. It will interest anyone who wants to learn about how the online world is revolutionizing scientific discovery—and why the revolution is just beginning.

Knowledge discovery in ubiquitous environments is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. It aims to provide a unifying framework for systematically investigating the mutual dependencies of otherwise quite unrelated technologies employed in building next-generation intelligent systems: machine learning, data mining, sensor networks, grids, peer-to-peer networks, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others. This state-of-the-art survey is the outcome of a large number of workshops, summer schools, tutorials and dissemination events organized by KDubiq (Knowledge Discovery in Ubiquitous Environments), a networking project funded by the European Commission to bring together researchers and practitioners of this emerging community. It provides in its first part a conceptual foundation for the new field of ubiquitous knowledge discovery - highlighting challenges and problems, and proposing future directions in the area of 'smart', 'adaptive', and 'intelligent' learning. The second part of this volume contains selected approaches to ubiquitous knowledge discovery and treats specific aspects in detail. The contributions have been carefully selected to provide illustrations and in-depth discussions for some of the major findings of Part I.

True stories of everyday volunteers participating in scientific research that “may well prompt readers to join the growing community” (Booklist). Think you need a degree in science to contribute to important scientific discoveries? Think again. All around the world, in fields ranging from meteorology to ornithology to public health, millions of everyday people are choosing to participate in the scientific process. Working in cooperation with scientists in pursuit of information, innovation, and discovery, these volunteers are following protocols, collecting and reviewing data, and sharing their observations. They’re our neighbors, in-laws, and coworkers. Their story, along with the story of the social good that can result from citizen science, has largely been untold, until now. Citizen scientists are challenging old notions about who can conduct research, where knowledge can be acquired, and even how solutions to some of our biggest societal problems might emerge. In telling their story, Caren Cooper just might inspire you to rethink your own assumptions about the role that individuals can play in gaining scientific understanding—and putting that understanding to use as a steward of our world. “Engaging.” —Library Journal (starred review)

This guidebook on e-science presents real-world examples of practices and applications, demonstrating how a range of computational technologies and tools can be employed to build essential infrastructures supporting next-generation scientific research. Each chapter provides introductory material on core concepts and principles, as well as descriptions and discussions of relevant e-science methodologies, architectures, tools, systems, services and frameworks. Features: includes contributions from an international selection of preeminent e-science experts and practitioners; discusses use of mainstream grid computing and peer-to-peer grid technology for “open” research and resource sharing in scientific research; presents varied methods for data management in data-intensive research; investigates issues of e-infrastructure interoperability, security, trust and privacy for collaborative research; examines workflow technology for the automation of scientific processes; describes applications of e-science.

Recently, nature has stimulated many successful techniques, algorithms, and computational applications allowing conventionally difficult problems to be solved through novel computing systems. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering provides the latest findings in nature-inspired algorithms and their applications for breakthroughs in a wide range of disciplinary fields. This defining reference collection contains chapters written by leading researchers and well-known academicians within the field, offering readers a valuable and enriched accumulation of knowledge.

The use of bibliometrics for the analysis of technology management is on the rise in our increasingly technological societies. Many are using these tools to document or record the rise of various technologies, making it necessary to take stock of the value and application of scientometric methods and their measures. Innovation Discovery shows the current state of play within the field of management of technology, and discusses how we can use networks to explore, understand and generate theory around the innovation process. It looks at the different streams of analysis used to understand bibliometric data, and presents alternative and novel ways of applying these techniques. Written as a comprehensive review of approaches by leading researchers in the field, this book is suitable for graduate and post-graduate students and researches looking to expand their knowledge and embark on further investigations in technology management. Contents: Part 1: Bibliometrics: The Case of Comparing an Ecosystem Using System and Network Approaches (Marco Tregua, Anna D'Auria, Tiziana Russo Spena, and Francesco Bifulco)Bibliometrics and Patents: Case of Forecasting of Biosensor Technologies for Emerging Point-of-Care and Medical IoT Applications (Nasir Jamil Sheikh, and Omar Sheikh)Patents: The Case of Exploitation of the Patent System Among SMEs and Private Inventors in Finland (J Talvela, M Karvonen, and T Kässi)Patents: Case of Analyzing Technological Knowledge Diffusion Among Technological Fields Using Patent Data: The Example of Microfluidics (Zheng Qiao, Lu-Cheng Huang, Fei-Fei Wu, Dan Wu, and Hui Zhang)Part 2: Patents and Networks: Case of Discerning the Evolutionary Nature of Technological Change in the Complex Product Industry (Fei Yuan and Kumiko Miyazaki)Patents and Networks: Case of Identification of Core Industry Actors for Electric Vehicle Battery by Application of Knowledge Flow (Yuan Yuan Shi and Tugrul Daim)Patents and Networks: Case of Social Network Analysis for Innovation (Antonello Cammarano, Mauro Caputo, Emilia Lamberti, and Francesca Michelino)Patents and Networks: Case of Cochlear Implant Technology Evolution Using Patent Classification Data (Srigowtham Arunagiri and Mary Mathew)Part 3: Bibliometrics and Networks: Case of a Multinational Perspective on How Eco-Innovation has Evolved in Academic Literature (Blanca de-Miguel-Molina, María de-Miguel-Molina, María-del-Val Segarra-Oña, and Ángel Peiró-Signes)Bibliometrics and Social Network Analysis Supporting the Research Development of Emerging Areas: Case Studies from Thailand (Nathasit Gerdsri and Alisa Kongthon)Bibliometrics and Networks: Trends and Typology of Emerging Antenna Propagation Technologies (Yasutomo Takano, Yuya Kajikawa, and Makoto Ando)Bibliometrics and Networks: Case of Project Management and the Emergence of a Knowledge-Based Discipline (Alan Pilkington, Kah-Hin Chai, and Le Yang)Part 4: Emerging Networking Methods: Innovation Intermediaries in Technological Alliances (Calvin S Weng)Emerging Networking Methods: Analysing Funding Patterns and Their Evolution in Two Medical Research Topics (Blanca de-Miguel-Molina, Scott W Cunningham, and Fernando Palop)Part 5: Advanced Methods: Identifying the Technology Profiles of R&D Performing Firms — A Matching of R&D and Patent Data (Peter Neuhäusler, Rainer Frietsch, Carolin Mund, and Verena Eckl)Advanced Methods: Identification of Promising High-Tech Solutions with Semantic Technologies: Energy, Pha