Navigating the Landscape of FAIR Data Sharing and Reuse: Repositories, Standards, and Resources

Navigating the Landscape of FAIR Data Sharing and Reuse: Repositories, Standards, and Resources PDF Author: Maaike M. H. Van Swieten
Publisher: Frontiers Media SA
ISBN: 2832545939
Category : Science
Languages : en
Pages : 136

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Book Description
The huge volume of neuroscience data and the wide variety of data formats generated across different neuroscience communities has posed a challenge to traditional methods of data management, data sharing and data mining. Mandates on data sharing and the demand for using open data has driven the development of advanced methodologies and tools to effectively explore, mine and integrate data. However, the growing number of resources make it harder for researchers to navigate this landscape. Awareness of these tools and resources is vital for effective data mining and unlocking new discoveries. The goal of this research collection is to provide an overview of available resources, centred around making data findable, accessible, interoperable and reusable (FAIR).

Navigating the Landscape of FAIR Data Sharing and Reuse: Repositories, Standards, and Resources

Navigating the Landscape of FAIR Data Sharing and Reuse: Repositories, Standards, and Resources PDF Author: Maaike M. H. Van Swieten
Publisher: Frontiers Media SA
ISBN: 2832545939
Category : Science
Languages : en
Pages : 136

Get Book Here

Book Description
The huge volume of neuroscience data and the wide variety of data formats generated across different neuroscience communities has posed a challenge to traditional methods of data management, data sharing and data mining. Mandates on data sharing and the demand for using open data has driven the development of advanced methodologies and tools to effectively explore, mine and integrate data. However, the growing number of resources make it harder for researchers to navigate this landscape. Awareness of these tools and resources is vital for effective data mining and unlocking new discoveries. The goal of this research collection is to provide an overview of available resources, centred around making data findable, accessible, interoperable and reusable (FAIR).

Data Sharing and Secondary Use of Scientific Data

Data Sharing and Secondary Use of Scientific Data PDF Author: Ann S. Zimmerman
Publisher:
ISBN:
Category : Ecology
Languages : en
Pages : 572

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Book Description


Curating Research Data

Curating Research Data PDF Author: Lisa R. Johnston
Publisher:
ISBN: 9780838988589
Category : Data curation in libraries
Languages : en
Pages : 285

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Book Description
Data are becoming the proverbial coin of the digital realm: a research commodity that might purchase reputation credit in a disciplinary culture of data sharing, or buy transparency when faced with funding agency mandates or publisher scrutiny. Unlike most monetary systems, however, digital data can flow in all too great an abundance. Not only does this currency actually grow on trees, but it comes from animals, books, thoughts, and each of us! And that is what makes data curation so essential. The abundance of digital research data challenges library and information science professionals to harness this flow of information streaming from research discovery and scholarly pursuit and preserve the unique evidence for future use. Volume One of Curating Research Data explores the variety of reasons, motivations, and drivers for why data curation services are needed in the context of academic and disciplinary data repository efforts. Twelve chapters, divided into three parts, take an in-depth look at the complex practice of data curation as it emerges around us. Part I sets the stage for data curation by describing current policies, data sharing cultures, and collaborative efforts currently underway that impact potential services. Part II brings several key issues, such as cost recovery and marketing strategy, into focus for practitioners when considering how to put data curation services in action. Finally, Part III describes the full lifecycle of data by examining the ethical and practical reuse issues that data curation practitioners must consider as we strive to prepare data for the future. Digital data is ubiquitous and rapidly reshaping how scholarship progresses now and into the future. The information expertise of librarians can help ensure the resiliency of digital data, and the information it represents, by addressing how the meaning, integrity, and provenance of digital data generated by researchers today will be captured and conveyed to future researchers.

Managing and Sharing Research Data

Managing and Sharing Research Data PDF Author: Louise Corti
Publisher: SAGE
ISBN: 144629773X
Category : Social Science
Languages : en
Pages : 258

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Book Description
Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today’s changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people’s research data, illustrated with six real-life case studies of data use.

Fundamentals of Clinical Data Science

Fundamentals of Clinical Data Science PDF Author: Pieter Kubben
Publisher: Springer
ISBN: 3319997130
Category : Medical
Languages : en
Pages : 218

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Book Description
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Reproducibility and Replicability in Science

Reproducibility and Replicability in Science PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309486165
Category : Science
Languages : en
Pages : 257

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Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.

The Practice of Reproducible Research

The Practice of Reproducible Research PDF Author: Justin Kitzes
Publisher: Univ of California Press
ISBN: 0520294742
Category : Computers
Languages : en
Pages : 364

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Book Description
The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.

Data Science for Undergraduates

Data Science for Undergraduates PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309475597
Category : Education
Languages : en
Pages : 139

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Book Description
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

Raw Data Is an Oxymoron

Raw Data Is an Oxymoron PDF Author: Lisa Gitelman
Publisher: MIT Press
ISBN: 0262312336
Category : Technology & Engineering
Languages : en
Pages : 203

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Book Description
Episodes in the history of data, from early modern math problems to today's inescapable “dataveillance,” that demonstrate the dependence of data on culture. We live in the era of Big Data, with storage and transmission capacity measured not just in terabytes but in petabytes (where peta- denotes a quadrillion, or a thousand trillion). Data collection is constant and even insidious, with every click and every “like” stored somewhere for something. This book reminds us that data is anything but “raw,” that we shouldn't think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted. The book's essays describe eight episodes in the history of data from the predigital to the digital. Together they address such issues as the ways that different kinds of data and different domains of inquiry are mutually defining; how data are variously “cooked” in the processes of their collection and use; and conflicts over what can—or can't—be “reduced” to data. Contributors discuss the intellectual history of data as a concept; describe early financial modeling and some unusual sources for astronomical data; discover the prehistory of the database in newspaper clippings and index cards; and consider contemporary “dataveillance” of our online habits as well as the complexity of scientific data curation. Essay Authors Geoffrey C. Bowker, Kevin R. Brine, Ellen Gruber Garvey, Lisa Gitelman, Steven J. Jackson, Virginia Jackson, Markus Krajewski, Mary Poovey, Rita Raley, David Ribes, Daniel Rosenberg, Matthew Stanley, Travis D. Williams

Preservation and the New Data Landscape

Preservation and the New Data Landscape PDF Author: Erica Avrami
Publisher: Issues in Preservation Policy
ISBN: 9781941332481
Category : Architecture
Languages : en
Pages : 220

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Book Description
This book explores how enhancing the collection, accuracy, and management of data can aid in identifying vulnerable neighborhoods, understanding the role of older buildings, and planning sustainable growth. For preservation to play a dynamic and inclusive role, policy must evolve beyond designation and regulation and use evidence-based research.