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Ping – Repository of the Future
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Bioinformatics Data Skills : Reproducible and Robust Research with Open Source Tools
Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings.With this practical guide, you'll learn how to use freely available open source tools to extract meaning from large complex biological data sets.At no other point in human history has our ability to understand life's complexities been so dependent on our skills to work with and analyze data.This intermediate-level book teaches the general computational and data skills you need to analyze biological data.If you have experience with a scripting language like Python, you're ready to get started.Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles
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Big Data for the Public Good : Regulating Access to Public Sector Big Data for Research and Innovation
Can researchers and innovators use UK public sector data to produce knowledge that improves policy making, scrutinises government work and promotes the public interest?This book looks at interactions between UK public sector officials and researchers/innovators to shed light on barriers to data access and use.It asks: what are the frameworks that govern access to public sector big datasets for researchers and innovators?How are these frameworks applied in practice? What are the governance solutions for policy makers interested in harnessing the untapped potential of public sector big data to improve their policies and create public benefit?Public sector data is a valuable resource that can help researchers and innovators create knowledge and solutions that benefit society.As public bodies collect increasingly more data about us, UK policy makers try to maximise the use of public sector big data for the benefit of the public.But accessing this data is not easy. There are many legal, technical, and ethical barriers that prevent the use of public sector data for research and innovation.This book is for researchers and innovators who want to understand and overcome the barriers to accessing UK public sector data.It is also for policy makers who are interested in how public sector data can be used to improve decision-making, scrutinise government work, and promote the public interest.
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Wyeth's Repository of Sacred Music : Selected From the Most Eminent and Approved Authors in That Science, for the Use of Christian Churches, of Every Denomination, Singing-schools & Private Societies,
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What is the best solution for a data repository?
The best solution for a data repository depends on the specific needs and requirements of the organization. However, a cloud-based data repository offers many advantages, including scalability, accessibility, and cost-effectiveness. Cloud-based solutions also provide built-in security measures and the ability to easily integrate with other cloud services. Additionally, using a managed data repository service can offload the burden of maintenance and management, allowing the organization to focus on utilizing the data for their business needs.
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Is the data repository updated monthly or one-time?
The data repository is updated monthly.
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How can I delete a GitHub repository?
To delete a GitHub repository, you need to go to the repository's page on GitHub. Then, click on the "Settings" tab, scroll down to the "Danger Zone" section, and click on the "Delete this repository" button. You will be prompted to confirm the deletion by typing in the name of the repository, and then clicking the "I understand the consequences, delete this repository" button. Once confirmed, the repository and all its contents will be permanently deleted. Keep in mind that this action cannot be undone, so make sure you really want to delete the repository before proceeding.
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Will we find a nuclear waste repository?
The search for a nuclear waste repository is ongoing, and it is likely that a suitable site will eventually be found. However, the process of siting and constructing a nuclear waste repository is complex and can take many years due to technical, political, and public acceptance challenges. It is important to continue the search for a safe and secure repository to ensure the long-term management of nuclear waste. With continued research and collaboration, it is possible that a suitable repository will be found in the future.
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Repository of Sacred Music : Selected From the Most Eminent and Approved Authors in That Science, for the Use of Christian Churches of Every Denomination, Singing Schools and Private Societies; Togeth
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface.We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
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Managing Cloud Native Data on Kubernetes : Architecting Cloud Native Data Services Using Open Source Technology
Kubernetes has become the primary platform for deploying and managing cloud native applications.But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging.If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll discover open source technologies that are designed and built for the cloud.Delve into case studies to avoid the pitfalls others have faced and explore new use cases.Get an insider's view of what's coming from the innovators who are creating next-generation architectures and infrastructure. And you'll learn how to: Manage different data use cases on Kubernetes Reduce costs and simplify application development Leverage data and infrastructure to create new use cases and business models Make data infrastructure choices that are cost-efficient, secure, scalable, and elastic And more
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Open Source Software for Statistical Analysis of Big Data : Emerging Research and Opportunities
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.
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Open Source Software for Statistical Analysis of Big Data : Emerging Research and Opportunities
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.
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Is there a central repository for studies?
Yes, there are several central repositories for studies, such as PubMed, which is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. Another example is the Cochrane Library, which is a collection of databases that contain high-quality, independent evidence to inform healthcare decision-making. These repositories provide access to a wide range of studies and research articles, making it easier for researchers and professionals to find relevant information.
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What is the difference between the Data Dictionary and the Repository?
The Data Dictionary is a centralized repository of information about data such as data definitions, data relationships, data usage, and data constraints. It provides a comprehensive view of the data within an organization. On the other hand, the Repository is a broader term that refers to a centralized location for storing and managing various types of data, including data models, metadata, code, and other artifacts related to software development. While the Data Dictionary focuses specifically on data-related information, the Repository encompasses a wider range of information and artifacts related to software development and data management.
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What went wrong with the nuclear waste repository?
The nuclear waste repository at Yucca Mountain in Nevada faced several challenges that ultimately led to its failure. One major issue was the opposition from local communities and environmental groups, who raised concerns about the potential for groundwater contamination and the transportation of nuclear waste to the site. Additionally, there were technical and scientific challenges in demonstrating the long-term safety and stability of the repository. The project also faced political obstacles, with changes in leadership and shifting priorities leading to funding cuts and ultimately the termination of the project. These factors combined to prevent the successful establishment of the nuclear waste repository at Yucca Mountain.
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What is the problem when adding a repository?
The problem when adding a repository can vary depending on the specific situation. Some common issues include entering the wrong repository URL, encountering authentication errors, or facing compatibility issues with the operating system or package manager. Additionally, repository servers may be down or experiencing connectivity issues, leading to difficulties in adding the repository. It is important to carefully follow the instructions provided by the repository maintainer and troubleshoot any errors that may arise during the process.
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