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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.
The innovative process of open source software is led in greater part by the end-users; therefore this aspect of open source software remains significant beyond the realm of traditional software development. Open Source Software Dynamics, Processes, and Applications is a multidisciplinary collection of research and approaches on the applications and processes of open source software. Highlighting the development processes performed by software programmers, the motivations of its participants, and the legal and economic issues that have been raised; this book is essential for scholars, students, and practitioners in the fields of software engineering and management as well as sociology.
As is true of most technological fields, the software industry is constantly advancing and becoming more accessible to a wider range of people. The advancement and accessibility of these systems creates a need for understanding and research into their development. Optimizing Contemporary Application and Processes in Open Source Software is a critical scholarly resource that examines the prevalence of open source software systems as well as the advancement and development of these systems. Featuring coverage on a wide range of topics such as machine learning, empirical software engineering and management, and open source, this book is geared toward academicians, practitioners, and researchers seeking current and relevant research on the advancement and prevalence of open source software systems.
"Free/Open Source Software Development" uses a multitude of research approaches to explore free and open source software development processes, attributes of their products, and the workings within the development communities.
"This book reviews the development, design, and use of free and open source software, providing relevant topics of discussion for programmers, as well as researchers in human-computer studies, online and virtual collaboration, and e-learning"--Provided by publisher.
Computer software and technologies are advancing at an amazing rate. The accessibility of these software sources allows for a wider power among common users as well as rapid advancement in program development and operating information. Free and Open Source Software in Modern Data Science and Business Intelligence: Emerging Research and Opportunities is a critical scholarly resource that examines the differences between the two types of software, integral in the FOSS movement, and their effect on the distribution and use of software. Featuring coverage on a wide range of topics, such as FOSS Ecology, graph mining, and project tasks, this book is geared towards academicians, researchers, and students interested in current research on the growing importance of FOSS and its expanding reach in IT infrastructure.
In open innovation scenarios, firms are able to profit from technological developments that take place beyond the legal boundaries. However, in the absence of contract-based vertical command chains, such as in the case of open source software (OSS), it is difficult for firms to obtain control over the innovation project’s trajectory. In this book, the author suggests that firms have basically two options to control project work beyond their boundaries and beyond their vertical command chains. The assumption is discussed against various theories of the firm as well as control theory and empirically tested by analyzing firm engagement in Eclipse open source projects as well as communication work in the Linux kernel project.