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| data management and sharing plan example nih: Sharing Clinical Trial Data Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Responsible Sharing of Clinical Trial Data, 2015-04-20 Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients. |
| data management and sharing plan example nih: Discussion Framework for Clinical Trial Data Sharing Committee on Strategies for Responsible Sharing of Clinical Trial Data, Institute of Medicine, Board on Health Sciences Policy, 2014 Sharing data generated through the conduct of clinical trials offers the promise of placing evidence about the safety and efficacy of therapies and clinical interventions on a firmer basis and enhancing the benefits of clinical trials. Ultimately, such data sharing - if carried out appropriately - could lead to improved clinical care and greater public trust in clinical research and health care. Discussion Framework for Clinical Trial Data Sharing: Guiding Principles, Elements, and Activities is part of a study of how data from clinical trials might best be shared. This document is designed as a framework for discussion and public comment. This framework is being released to stimulate reactions and comments from stakeholders and the public. The framework summarizes the committee's initial thoughts on guiding principles that underpin responsible sharing of clinical trial data, defines key elements of clinical trial data and data sharing, and describes a selected set of clinical trial data sharing activities. |
| data management and sharing plan example nih: The Data Book Meredith Zozus, 2017-07-12 The Data Book: Collection and Management of Research Data is the first practical book written for researchers and research team members covering how to collect and manage data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data. The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing, and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods. |
| data management and sharing plan example nih: Data Management in Large-Scale Education Research Crystal Lewis, 2024-07-09 Research data management is becoming more complicated. Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices. Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection. While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well. The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies. The book starts by describing the research life cycle and how data management fits within this larger picture. The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase. Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features: Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaboratively Can be read in its entirety, or referenced as needed throughout the life cycle Includes relatable examples specific to education research Includes a discussion on how to organize and document data in preparation for data sharing requirements Contains links to example documents as well as templates to help readers implement practices |
| data management and sharing plan example nih: The Medical Library Association Guide to Data Management for Librarians Lisa Federer, 2016-09-15 Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians. |
| data management and sharing plan example nih: Sharing Research Data to Improve Public Health in Africa National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on Population, 2015-09-18 Sharing research data on public health issues can promote expanded scientific inquiry and has the potential to advance improvements in public health. Although sharing data is the norm in some research fields, sharing of data in public health is not as firmly established. In March 2015, the National Research Council organized an international conference in Stellenbosch, South Africa, to explore the benefits of and barriers to sharing research data within the African context. The workshop brought together public health researchers and epidemiologists primarily from the African continent, along with selected international experts, to talk about the benefits and challenges of sharing data to improve public health, and to discuss potential actions to guide future work related to public health research data sharing. Sharing Research Data to Improve Public Health in Africa summarizes the presentations and discussions from this workshop. |
| data management and sharing plan example nih: Data Management Margaret E. Henderson, 2016-10-25 Libraries organize information and data is information, so it is natural that librarians should help people who need to find, organize, use, or store data. Organizations need evidence for decision making; data provides that evidence. Inventors and creators build upon data collected by others. All around us, people need data. Librarians can help increase the relevance of their library to the research and education mission of their institution by learning more about data and how to manage it. Data Management will guide readers through: Understanding data management basics and best practices. Using the reference interview to help with data management Writing data management plans for grants. Starting and growing a data management service. Finding collaborators inside and outside the library. Collecting and using data in different disciplines. |
| data management and sharing plan example nih: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. |
| data management and sharing plan example nih: Principles and Obstacles for Sharing Data from Environmental Health Research National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Roundtable on Environmental Health Sciences, Research, and Medicine, 2016-05-29 On March 19, 2014, the National Academies of Sciences, Engineering, and Medicine held a workshop on the topic of the sharing of data from environmental health research. Experts in the field of environmental health agree that there are benefits to sharing research data, but questions remain regarding how to effectively make these data available. The sharing of data derived from human subjects-making them both transparent and accessible to others-raises a host of ethical, scientific, and process questions that are not always present in other areas of science, such as physics, geology, or chemistry. The workshop participants explored key concerns, principles, and obstacles to the responsible sharing of data used in support of environmental health research and policy making while focusing on protecting the privacy of human subjects and addressing the concerns of the research community. Principles and Obstacles for Sharing Data from Environmental Health Research summarizes the presentations and discussions from the workshop. |
| data management and sharing plan example nih: Neuroscience Data in the Cloud National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Sciences Policy, Forum on Neuroscience and Nervous System Disorders, 2020-05-06 The cloud model of data sharing has led to a vast increase in the quantity and complexity of data and expanded access to these data, which has attracted many more researchers, enabled multi-national neuroscience collaborations, and facilitated the development of many new tools. Yet, the cloud model has also produced new challenges related to data storage, organization, and protection. Merely switching the technical infrastructure from local repositories to cloud repositories is not enough to optimize data use. To explore the burgeoning use of cloud computing in neuroscience, the National Academies Forum on Neuroscience and Nervous System Disorders hosted a workshop on September 24, 2019. A broad range of stakeholders involved in cloud-based neuroscience initiatives and research explored the use of cloud technology to advance neuroscience research and shared approaches to address current barriers. This publication summarizes the presentation and discussion of the workshop. |
| data management and sharing plan example nih: Fundamentals of Clinical Data Science Pieter Kubben, Michel Dumontier, Andre Dekker, 2018-12-21 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. |
| data management and sharing plan example nih: Data Management for Researchers Kristin Briney, 2015-09-01 A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline. —Robert Buntrock, Chemical Information Bulletin |
| data management and sharing plan example nih: Principles and Practice of Clinical Trials Steven Piantadosi, Curtis L. Meinert, 2022-07-19 This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference. |
| data management and sharing plan example nih: Writing Dissertation and Grant Proposals Lisa Chasan-Taber, 2014-04-28 This text targets effective grant proposal writing in epidemiology, preventive medicine, and biostatistics. It provides summary checklists and step-by-step guidelines for grant structure and style, critical do's and don'ts that aid in writing solid grant proposals, and broader strategies for developing a research funding portfolio. Written by an established NIH reviewer with an impressive track record of funding, the book demonstrates proven tactics with extensive examples from successfully funded proposals. It serves as a virtual cookbook of the ingredients needed to construct a winning grant proposal. |
| data management and sharing plan example nih: Guidelines for the Conduct of Research Involving Human Subjects at the National Institutes of Health National Institutes of Health (U.S.), 1993 |
| data management and sharing plan example nih: Principles and Practice of Clinical Research John I. Gallin, Frederick P Ognibene, Laura Lee Johnson, 2017-11-17 Principles and Practice of Clinical Research, Fourth Edition has been thoroughly revised to provide a comprehensive look at both the fundamental principles and expanding practice of clinical research. New to this edition of this highly regarded reference, authors have focused on examples that broadly reflect clinical research on a global scale while including a discussion of international regulations, studies, and implications. In addition to key topics such as bioethics, clinical outcome data, cultural diversity, protocol guidelines, and omic platforms, this edition contains new chapters devoted to electronic health records and information resources for clinical researchers, as well as the many opportunities associated with big data. Covering a vast number of topics and practical advice for both novice and advanced clinical investigators, this book is a highly relevant and essential resource for all those involved in conducting research. - Features input from experts in the field dedicated to translating scientific research from bench to bedside and back - Provides expanded coverage of global clinical research - Contains hands-on, practical suggestions, illustrations, and examples throughout - Includes new chapters on the international regulation of drugs and biologics, the emergence of the important role of comparative effectiveness research and how to identify clinical risks and manage patient safety in a clinical research setting |
| data management and sharing plan example nih: Research Data Management Joyce M. Ray, 2014 It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations. |
| data management and sharing plan example nih: Responsible Conduct of Research Adil E. Shamoo, David B. Resnik, 2009-02-12 Recent scandals and controversies, such as data fabrication in federally funded science, data manipulation and distortion in private industry, and human embryonic stem cell research, illustrate the importance of ethics in science. Responsible Conduct of Research, now in a completely updated second edition, provides an introduction to the social, ethical, and legal issues facing scientists today. |
| data management and sharing plan example nih: The Oxford Handbook of Integrative Health Science Carol D. Ryff, Robert F. Krueger, 2018-10-03 Most health research to date has been pursued within the confines of scientific disciplines that are guided by their own targeted questions and research strategies. Although useful, such inquiries are inherently limited in advancing understanding the interplay of wide-ranging factors that shape human health. The Oxford Handbook of Integrative Health Science embraces an integrative approach that seeks to put together sociodemographic factors (age, gender, race, socioeconomic status) known to contour rates of morbidity and mortality with psychosocial factors (emotion, cognition, personality, well-being, social connections), behavioral factors (health practices) and stress exposures (caregiving responsibilities, divorce, discrimination) also known to influence health. A further overarching theme is to explicate the biological pathways through which these various effects occur. The biopsychosocial leitmotif that inspires this approach demands new kinds of studies wherein wide-ranging assessments across different domains are assembled on large population samples. The MIDUS (Midlife in the U.S.) national longitudinal study exemplifies such an integrative study, and all findings presented in this collection draw on MIDUS. The way the study evolved, via collaboration of scientists working across disciplinary lines, and its enthusiastic reception from the scientific community are all part of the larger story told. Embedded within such tales are important advances in the identification of key protective or vulnerability factors: these pave the way for practice and policy initiatives seeking to improve the nation's health. |
| data management and sharing plan example nih: Research Administration and Management Elliott Kulakowski, Lynne U. Chronister, 2006 This reference text addresses the basic knowledge of research administration and anagement, and includes everything from a review of research administration and the infrastructure that is necessary to support research, to project development and post-project plans. Examples of concepts, case studies, a glossary of terms and acronyms, and references to books, journal articles, monographs, and federal regulations are also included. |
| data management and sharing plan example nih: Principles of Scientific Writing and Biomedical Publication Phil B. Fontanarosa, Annette Flanagin, Philip Greenland, 2024 Publication of biomedical research is essential for improvement and advancement of medical science and clinical practice. The history of scientific publication, including journals devoted to medical science, dates to the 1600s. The number of peer-reviewed scientific journals is estimated to be in the tens of thousands, and the number of journals, especially with the increasing creation of open access publications, continues to expand. Yet, despite the long history of and ubiquitous nature of scientific publications, the core principles involved in biomedical publication as well as the specific skills of writing and manuscript preparation are not commonly taught in a formal or comprehensive way in medicine, public health, or research curricula-- |
| data management and sharing plan example nih: Personal Genome Medicine Michael J. Malinowski, 2023-08-31 In the years following FDA approval of direct-to-consumer, genetic-health-risk testing, millions of people in the United States have sent their DNA to companies to receive personal genetic health risk information without physician or other learned medical professional involvement. In Personal Genome Medicine, Michael J. Malinowski examines the ethical, legal, and social implications of this development. Drawing from the past and present of medicine in the U.S., Malinowski applies law, policy, public and private sector practices, and governing norms to analyze the commercial personal genome sequencing and testing sectors and to assess their impact on the future of U.S. medicine. Written in relatable and accessible language, the book also proposes regulatory reforms for government and medical professionals that will enable technological advancements while maintaining personal and public health standards. |
| data management and sharing plan example nih: Big Data and Business Analytics Jay Liebowitz, 2013-06-13 The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’ —From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee Company With the growing barrage of big data, it becomes vitally important for organizations to make sense of this data and information in a timely and effective way. That’s where analytics come into play. Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity. Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive. Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation. Understand the trends, potential, and challenges associated with big data and business analytics Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits Big data problems are complex. This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage. Author Jay Liebowitz recently had an article published in The World Financial Review. www.worldfinancialreview.com/?p=1904 |
| data management and sharing plan example nih: Information and Data Literacy Joyce Hagen-McIntosh, 2016-01-05 In an age where data flows non-stop, across all geographic borders and accessible to many, the job of providing information literacy has become much more exciting, more complicated, and more necessary. Information and Data Literacy: The Role of the Library takes a comprehensive look at the changing role of today’s librarians and libraries in an increasingly tech-driven world. You’ll find the authors of this book represent public and academic libraries, countries around the globe, and differences of opinion as to the definition, purpose, charge, and success of providing information and data literacy. The book is divided into several parts, covering: Understanding the role of information and data literacy in the library The new and changing roles for librarians Methods for promoting information and data literacy New challenges for the library in the new information environment The need for information and data literacy for marginalized populations, including the homeless, those in rural settings, sexual minorities, and others Addressing the trends and challenges at different types of libraries, the volume provides an overview of information and data literacy in the library and offers an array of perspectives. Topics cover: The role of the public library as a community hub Student information literacy in the mobile environment Information literacy in schools How the information landscape has changed library reference services Library instruction and exercises to promote information literacy for both traditional students and those in continuing education Edited by a consultant with the Freedom to Read Foundation who is a former outreach and assistive technology librarian, the book offers a wealth of information for beginning librarians as well as for seasoned library professionals looking for new methods to evaluate and promote data and information literacy. |
| data management and sharing plan example nih: Clinical Research Informatics Rachel L. Richesson, James E. Andrews, Kate Fultz Hollis, 2023-06-14 This extensively revised new edition comprehensively reviews the rise of clinical research informatics (CRI). It enables the reader to develop a thorough understanding of how CRI has developed and the evolving challenges facing the biomedical informatics professional in the modern clinical research environment. Emphasis is placed on the changing role of the consumer and the need to merge clinical care delivery and research as part of a changing paradigm in global healthcare delivery. Clinical Research Informatics presents a detailed review of using informatics in the continually evolving clinical research environment. It represents a valuable textbook reference for all students and practising healthcare informatics professional looking to learn and expand their understanding of this fast-moving and increasingly important discipline. |
| data management and sharing plan example nih: Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age Institute of Medicine, National Academy of Engineering, National Academy of Sciences, Committee on Science, Engineering, and Public Policy, Committee on Ensuring the Utility and Integrity of Research Data in a Digital Age, 2009-12-17 As digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data; standards that do not keep pace with the high rate of innovation; restrictions on data sharing that reduce the ability of researchers to verify results and build on previous research; and huge increases in the amount of data being generated, creating severe challenges in preserving that data for long-term use. Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects. The report recommends that all researchers receive appropriate training in the management of research data, and calls on researchers to make all research data, methods, and other information underlying results publicly accessible in a timely manner. The book also sees the stewardship of research data as a critical long-term task for the research enterprise and its stakeholders. Individual researchers, research institutions, research sponsors, professional societies, and journals involved in scientific, engineering, and medical research will find this book an essential guide to the principles affecting research data in the digital age. |
| data management and sharing plan example nih: Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations for 1997 United States. Congress. House. Committee on Appropriations. Subcommittee on the Departments of Labor, Health and Human Services, Education, and Related Agencies, 1996 |
| data management and sharing plan example nih: Demystifying eResearch Victoria Martin, 2014-10-17 eResearch presents new challenges in managing data. This book explains to librarians and other information specialists what eResearch is, how it impacts library services and collections, and how to contribute to eResearch activities at their parent institutions. Today's librarians need to be technology-savvy information experts who understand how to manage datasets. Demystifying eResearch: A Primer for Librarians prepares librarians for careers that involve eResearch, clearly defining what it is and how it impacts library services and collections, explaining key terms and concepts, and explaining the importance of the field. You will come to understand exactly how the use of networked computing technologies enhances and supports collaboration and innovative methods particularly in scientific research, learn about eResearch library initiatives and best practices, and recognize the professional development opportunities that eResearch offers. This book takes the broad approach to the complex topic of eResearch and how it pertains to the library community, providing an introduction that will be accessible to readers without a background in electronic research. The author presents a conceptual overview of eResearch with real-world examples of electronic research activities to quickly increase your familiarity with eResearch and awareness of the current state of eResearch librarianship. |
| data management and sharing plan example nih: Digitalization of Medicine in Low- and Middle-Income Countries Zisis Kozlakidis, |
| data management and sharing plan example nih: The Role of NIH in Drug Development Innovation and Its Impact on Patient Access National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Sciences Policy, Board on Health Care Services, 2020-01-27 To explore the role of the National Institutes of Health (NIH) in innovative drug development and its impact on patient access, the Board on Health Care Services and the Board on Health Sciences Policy of the National Academies jointly hosted a public workshop on July 24â€25, 2019, in Washington, DC. Workshop speakers and participants discussed the ways in which federal investments in biomedical research are translated into innovative therapies and considered approaches to ensure that the public has affordable access to the resulting new drugs. This publication summarizes the presentations and discussions from the workshop. |
| data management and sharing plan example nih: 108-1 Hearings: Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations For 2004, Part 4B, 2003, * , 2003 |
| data management and sharing plan example nih: Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations for 2004 United States. Congress. House. Committee on Appropriations. Subcommittee on the Departments of Labor, Health and Human Services, Education, and Related Agencies, 2003 |
| data management and sharing plan example nih: The Complete Guide to Open Scholarship Victoria Martin, 2022-05-24 Choice Outstanding Academic Title 2023 Offers librarians an authoritative overview of the full spectrum of significant issues and controversies related to open scholarship in a candid and fair-minded manner. There has long been a debate about openness in scholarship, and even the term itself continues to be debated. Openness is a complex and multidimensional concept, and its nature in scholarship continually evolves. One of the hindrances to the transition to greater openness in academia is this lack of clear understanding about how it fits into the practice of scholarly communication. To ensure that librarians as knowledge managers can better educate scholars about the benefits and challenges of open scholarship, Victoria Martin's The Complete Guide to Open Scholarship brings clarity to the concept of openness, tests assumptions concerning it, and strikes the right balance between breaking down complex ideas into simpler ones and honoring the reader's intelligence and previous knowledge of the subject. Readers will learn the history of openness in scholarship as well as several ways in which openness can be perceived. Drawing on specific examples, Martin discusses the most prominent scholarly models based on openness, barriers to openness, concerns about openness in scholarship, and the future of open scholarship. |
| data management and sharing plan example nih: Reflections on Sharing Clinical Trial Data National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Board on Health Sciences Policy, Roundtable on Genomics and Precision Health, National Cancer Policy Forum, Forum on Neuroscience and Nervous System Disorders, Forum on Drug Discovery, Development, and Translation, 2020-10-20 On November 18 and 19, 2019, the National Academies of Sciences, Engineering, and Medicine hosted a public workshop in Washington, DC, titled Sharing Clinical Trial Data: Challenges and a Way Forward. The workshop followed the release of the 2015 Institute of Medicine (IOM) consensus study report Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk, and was designed to examine the current state of clinical trial data sharing and reuse and to consider ways in which policy, technology, incentives, and governance could be leveraged to further encourage and enhance data sharing. This publication summarizes the presentations and discussions from the workshop. |
| data management and sharing plan example nih: Conducting Biosocial Surveys National Research Council, Division of Behavioral and Social Sciences and Education, Committee on Population, Committee on National Statistics, Panel on Collecting, Storing, Accessing, and Protecting Biological Specimens and Biodata in Social Surveys, 2010-10-02 Recent years have seen a growing tendency for social scientists to collect biological specimens such as blood, urine, and saliva as part of large-scale household surveys. By combining biological and social data, scientists are opening up new fields of inquiry and are able for the first time to address many new questions and connections. But including biospecimens in social surveys also adds a great deal of complexity and cost to the investigator's task. Along with the usual concerns about informed consent, privacy issues, and the best ways to collect, store, and share data, researchers now face a variety of issues that are much less familiar or that appear in a new light. In particular, collecting and storing human biological materials for use in social science research raises additional legal, ethical, and social issues, as well as practical issues related to the storage, retrieval, and sharing of data. For example, acquiring biological data and linking them to social science databases requires a more complex informed consent process, the development of a biorepository, the establishment of data sharing policies, and the creation of a process for deciding how the data are going to be shared and used for secondary analysis-all of which add cost to a survey and require additional time and attention from the investigators. These issues also are likely to be unfamiliar to social scientists who have not worked with biological specimens in the past. Adding to the attraction of collecting biospecimens but also to the complexity of sharing and protecting the data is the fact that this is an era of incredibly rapid gains in our understanding of complex biological and physiological phenomena. Thus the tradeoffs between the risks and opportunities of expanding access to research data are constantly changing. Conducting Biosocial Surveys offers findings and recommendations concerning the best approaches to the collection, storage, use, and sharing of biospecimens gathered in social science surveys and the digital representations of biological data derived therefrom. It is aimed at researchers interested in carrying out such surveys, their institutions, and their funding agencies. |
| data management and sharing plan example nih: The Oxford Textbook of Clinical Research Ethics Ezekiel J. Emanuel, Christine C. Grady, Robert A. Crouch, Reidar K. Lie, Franklin G. Miller, David D. Wendler, 2011-02 The Oxford Textbook of Clinical Research Ethics is the first comprehensive and systematic reference on clinical research ethics. Under the editorship of experts from the U.S. National Institutes of Health of the United States, the book's 73 chapters offer a wide-ranging and systematic examination of all aspects of research with human beings. Considering the historical triumphs of research as well as its tragedies, the textbook provides a framework for analyzing the ethical aspects of research studies with human beings. Through both conceptual analysis and systematic reviews of empirical data, the contributors examine issues ranging from scientific validity, fair subject selection, risk benefit ratio, independent review, and informed consent to focused consideration of international research ethics, conflicts of interests, and other aspects of responsible conduct of research. The editors of The Oxford Textbook of Clinical Research Ethics offer a work that critically assesses and advances scholarship in the field of human subjects research. Comprehensive in scope and depth, this book will be a crucial resource for researchers in the medical sciences, as well as teachers and students. |
| data management and sharing plan example nih: Building the Infrastructure for Data Access and Reuse in Collaborative Research Anne Fitzgerald, Kylie Pappalardo, Brian F. Fitzgerald, OAK Law Project, 2007 This report examines the legal framework within which research data is generated, managed, disseminated and used. It provides an overview of the operation of copyright law, contract and confidentiality laws, as well as a range of legislation - privacy, public records and freedom of information legislation - that is of relevance to research data. |
| data management and sharing plan example nih: Integrating Social Care into the Delivery of Health Care National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation's Health, 2020-01-30 Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health was released in September 2019, before the World Health Organization declared COVID-19 a global pandemic in March 2020. Improving social conditions remains critical to improving health outcomes, and integrating social care into health care delivery is more relevant than ever in the context of the pandemic and increased strains placed on the U.S. health care system. The report and its related products ultimately aim to help improve health and health equity, during COVID-19 and beyond. The consistent and compelling evidence on how social determinants shape health has led to a growing recognition throughout the health care sector that improving health and health equity is likely to depend †at least in part †on mitigating adverse social determinants. This recognition has been bolstered by a shift in the health care sector towards value-based payment, which incentivizes improved health outcomes for persons and populations rather than service delivery alone. The combined result of these changes has been a growing emphasis on health care systems addressing patients' social risk factors and social needs with the aim of improving health outcomes. This may involve health care systems linking individual patients with government and community social services, but important questions need to be answered about when and how health care systems should integrate social care into their practices and what kinds of infrastructure are required to facilitate such activities. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health examines the potential for integrating services addressing social needs and the social determinants of health into the delivery of health care to achieve better health outcomes. This report assesses approaches to social care integration currently being taken by health care providers and systems, and new or emerging approaches and opportunities; current roles in such integration by different disciplines and organizations, and new or emerging roles and types of providers; and current and emerging efforts to design health care systems to improve the nation's health and reduce health inequities. |
| data management and sharing plan example nih: Epidemiology of Drug Abuse Zili Sloboda, 2006-06-02 As the drug abuse epidemic evolves, so do the tools needed to understand and treat it. Accordingly, Epidemiology of Drug Abuse takes the long view, cogently outlining what the book calls the natural history of drug abuse and redefining its complex phenomena to reflect our present-day knowledge. Twenty-six eminent contributors discuss the state and future of the field, balancing the practical concerns involved in gathering drug abuse data with the ethics of using the information. - Current thinking on pathways and etiology, as well as medical, psychological, and social sequelae of drug abuse - Proven, up-to-date methodologies for assessment - Challenges of gathering data from high-risk and other user populations - Sampling and application issues - Uses, sources, and limitations of treatment data - Analytical papers applying the methodologies to specific and global studies - The role of epidemiology studies in developing prevention strategies With this multifaceted approach to the subject, Epidemiology of Drug Abuse provides researchers and educators with a reference that sheds significant light on infrequently covered areas. In addition, its breadth and accessibility of coverage make it a teaching text suitable to courses in epidemiology, public health, and drug abuse. |
| data management and sharing plan example nih: Style and Ethics of Communication in Science and Engineering Jay D. Humphrey, Jeffrey W. Holmes, 2023-10-10 This book serves as a valuable aid for scientists and engineers who seek to discover and disseminate knowledge so that it can be used to improve the human condition. This book can be used as a textbook for undergraduate or graduate courses on technical communication and ethics, a reference book for senior design courses, or a handbook for young investigators and beginning faculty members. In addition to presenting methods for writing clearly and concisely and improving oral or poster presentations, this compact book provides practical guidelines for preparing theses, dissertations, journal papers for publication, and proposals for research funding. Issues of authorship, peer review, plagiarism, recordkeeping, transparency, and copyright are addressed in detail, and case studies of research misconduct highlight the need for proactive attention to scientific integrity. Ample exercises cause the reader to stop and think. The authors motivate the reader to develop an effective, individual style of communication and a personal commitment to integrity, each of which are essential to success in the workplace. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
