The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an 'omics' platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems

This handbook of research is one of the few texts to combine Open Source Software (OSS) in public and private sector activities into a single reference source. It examines how the use of OSS affects practices in society, business, government, education, and law.

Open-Source Lab: How to Build Your Own Hardware and Reduce Scientific Research Costs details the development of the free and open-source hardware revolution. The combination of open-source 3D printing and microcontrollers running on free software enables scientists, engineers, and lab personnel in every discipline to develop powerful research tools at unprecedented low costs.After reading Open-Source Lab, you will be able to: - Lower equipment costs by making your own hardware - Build open-source hardware for scientific research - Actively participate in a community in which scientific results are more easily replicated and cited - Numerous examples of technologies and the open-source user and developer communities that support them - Instructions on how to take advantage of digital design sharing - Explanations of Arduinos and RepRaps for scientific use - A detailed guide to open-source hardware licenses and basic principles of intellectual property

With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.

This book constitutes the thoroughly refereed proceedings of the 16th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2021, held in Kristiansand, Norway, in August 2021.* The 24 revised full research papers, included in the volume together with 6 short contributions and 7 prototype papers, were carefully reviewed and selected from 78 submissions. They are organized in the following topical sections: ​impactful sociotechnical design; problem and contribution articulation; design knowledge for reuse; emerging methods and frameworks for DSR; DSR and governance; the new boundaries of DSR. *Apart from the planned on-site event, the hybrid conference model was explored due to the Covid-19 pandemic.

Leading Free and Open Source software researchers and analysts consider the status of the open source revolution and its effect on industry and society.

Despite recent advances in our understanding of how innovation and entrepreneurship impact the creation and appropriation of value, numerous questions remain unanswered. This volume draws together scholars working at the forefront of entrepreneurship-, strategy-, and innovation-related domains to explore these questions.

Over the last two decades, ‘neoliberalism’ has emerged as a key concept within a range of social science disciplines including sociology, political science, human geography, anthropology, political economy, and cultural studies. The SAGE Handbook of Neoliberalism showcases the cutting edge of contemporary scholarship in this field by bringing together a team of global experts. Across seven key sections, the handbook explores the different ways in which neoliberalism has been understood and the key questions about the nature of neoliberalism: Part 1: Perspectives Part 2: Sources Part 3: Variations and Diffusions Part 4: The State Part 5: Social and Economic Restructuring Part 6: Cultural Dimensions Part 7: Neoliberalism and Beyond This handbook is the key reference text for scholars and graduate students engaged in the growing field of neoliberalism.