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| data management and sharing plan: 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: Managing and Sharing Research Data Louise Corti, Veerle Van den Eynden, Libby Bishop, Matthew Woollard, 2014-02-04 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. |
| data management and sharing plan: Managing and Sharing Research Data Louise Corti, Veerle Van den Eynden, Libby Bishop, Matthew Woollard, 2014-03-01 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. |
| data management and sharing plan: 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: 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: 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: 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: 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: Managing Research Data Graham Pryor, 2012-01-20 This title defines what is required to achieve a culture of effective data management offering advice on the skills required, legal and contractual obligations, strategies and management plans and the data management infrastructure of specialists and services. Data management has become an essential requirement for information professionals over the last decade, particularly for those supporting the higher education research community, as more and more digital information is created and stored. As budgets shrink and funders of research demand evidence of value for money and demonstrable benefits for society, there is increasing pressure to provide plans for the sustainable management of data. Ensuring that important data remains discoverable, accessible and intelligible and is shared as part of a larger web of knowledge will mean that research has a life beyond its initial purpose and can offer real utility to the wider community. This edited collection, bringing together leading figures in the field from the UK and around the world, provides an introduction to all the key data issues facing the HE and information management communities. Each chapter covers a critical element of data management: • Why manage research data? • The lifecycle of data management • Research data policies: principles, requirements and trends • Sustainable research data • Data management plans and planning • Roles and responsibilities – libraries, librarians and data • Research data management: opportunities and challenges for HEIs • The national data centres • Contrasting national research data strategies: Australia and the USA • Emerging infrastructure and services for research data management and curation in the UK and Europe Readership: This is essential reading for librarians and information professionals working in the higher education sector, the research community, policy makers and university managers. It will also be a useful introduction for students taking courses in information management, archivists and national library services. |
| data management and sharing plan: 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: Creating Value from Data Sharing Anne Dreller, 2018-08-14 Anne Dreller shows that data sharing offers great opportunities and huge value creation potential for the business world. Despite many opportunities that data sharing promises, the business world has not fully operationalized this fact yet, due to various existing challenges. Thus, an exemplary, future-oriented, and platform-based data sharing business model is developed for the startup Quemey. This business model is also equipped with prioritized implementation advice, including measures like focusing on strong values for all platform participants, growing their business into a powerful monopolist position, and eliminating barriers of technological, contractual and legal or data privacy uncertainties. |
| data management and sharing plan: Data Sharing Using A Common Data Architecture Michael H. Brackett, 1994-03-28 Data Sharing Using a Common Data Architecture Wouldn’t it be a pleasure to know and understand all the data in your organization? Wouldn’t it be great to easily identify and readily share those data to develop information that supports business strategies? Wouldn’t it be wonderful to have a formal data resource that provides just-in-time data for developing just-in-time information to support just-in-time decision making? Data Sharing Using a Common Data Architecture shows you how by: Defining a common data architecture, its contents, and its uses Refining data to a common data architecture Discussing disparate data, its structure, quality, and how to identify it Describing how Data Sharing Reality is achieved Focusing on the importance of people and creating a win-win situation Providing a data lexicon and extensive glossary Data Sharing Using a Common Data Architecture is must reading for data administrators, database administrators, MIS project leaders, application programmers, systems analysts, MIS trainers and instructors, and graduate students. |
| data management and sharing plan: The Encyclopedia of Research Methods in Criminology and Criminal Justice, 2 Volume Set J. C. Barnes, David R. Forde, 2021-09-08 The Encyclopedia of RESEARCH METHODS IN CRIMINOLOGY & CRIMINAL JUSTICE The most comprehensive reference work on research designs and methods in criminology and criminal justice This Encyclopedia of Research Methods in Criminology and Criminal Justice offers a comprehensive survey of research methodologies and statistical techniques that are popular in criminology and criminal justice systems across the globe. With contributions from leading scholars and practitioners in the field, it offers a clear insight into the techniques that are currently in use to answer the pressing questions in criminology and criminal justice. The Encyclopedia contains essential information from a diverse pool of authors about research designs grounded in both qualitative and quantitative approaches. It includes information on popular datasets and leading resources of government statistics. In addition, the contributors cover a wide range of topics such as: the most current research on the link between guns and crime, rational choice theory, and the use of technology like geospatial mapping as a crime reduction tool. This invaluable reference work: Offers a comprehensive survey of international research designs, methods, and statistical techniques Includes contributions from leading figures in the field Contains data on criminology and criminal justice from Cambridge to Chicago Presents information on capital punishment, domestic violence, crime science, and much more Helps us to better understand, explain, and prevent crime Written for undergraduate students, graduate students, and researchers, The Encyclopedia of Research Methods in Criminology and Criminal Justice is the first reference work of its kind to offer a comprehensive review of this important topic. |
| data management and sharing plan: Climate Data Records from Environmental Satellites National Research Council, Division on Earth and Life Studies, Board on Atmospheric Sciences and Climate, Committee on Climate Data Records from NOAA Operational Satellites, 2004-08-26 The report outlines key elements to consider in designing a program to create climate-quality data from satellites. It examines historical attempts to create climate data records, provides advice on steps for generating, re-analyzing, and storing satellite climate data, and discusses the importance of partnering between agencies, academia, and industry. NOAA will use this report-the first in a two-part study-to draft an implementation plan for climate data records. |
| data management and sharing plan: 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: Visualizing Health and Healthcare Data Katherine Rowell, Lindsay Betzendahl, Cambria Brown, 2020-11-10 The only data visualization book written by and for health and healthcare professionals. In health and healthcare, data and information are coming at organizations faster than they can consume and interpret it. Health providers, payers, public health departments, researchers, and health information technology groups know the ability to analyze and communicate this vast array of data in a clear and compelling manner is paramount to success. However, they simply cannot find experienced people with the necessary qualifications. The quickest (and often the only) route to meeting this challenge is to hire smart people and train them. Visualizing Health and Healthcare Data: Creating Clear and Compelling Visualizations to See how You're Doing is a one-of-a-kind book for health and healthcare professionals to learn the best practices of data visualization specific to their field. It provides a high-level summary of health and healthcare data, an overview of relevant visual intelligence research, strategies and techniques to gather requirements, and how to build strong teams with the expertise required to create dashboards and reports that people love to use. Clear and detailed explanations of data visualization best practices will help you understand the how and the why. Learn how to build beautiful and useful data products that deliver powerful insights for the end user Follow along with examples of data visualization best practices, including table and graph design for health and healthcare data Learn the difference between dashboards, reports, multidimensional exploratory displays and infographics (and why it matters) Avoid common mistakes in data visualization by learning why they do not work and better ways to display the data Written by a top leader in the field of health and healthcare data visualization, this book is an excellent resource for top management in healthcare, as well as entry-level to experienced data analysts in any health-related organization. |
| data management and sharing plan: Sharing and reuse of health-related data for research purposes World Health Organization, 2022-04-06 This document sets out WHO policy on the sharing and reuse of health-related data for research purposes, and guidance on how to implement the policy. It clarifies for WHO staff the policy and practice on the reuse and onward sharing of health data collected under the auspices of WHO technical programmes for research purposes. Its scope includes research data generated by research undertaken directly by WHO, or funded by WHO, as well as the use of other health data for research purposes. This document also provides further references and resources to assist in the development of a data management and sharing plan that is in alignment with the vision of this policy. This covers both emergency and non-emergency situations and complements the following from the reuse perspective: Policy on use and sharing of data collected in Member States by the World Health Organization (WHO) outside the context of public health emergencies; the Policy Statement on Data Sharing by the World Health Organization in the Context of Public Health Emergencies and; the Joint statement on public disclosure of results from clinical trials. |
| data management and sharing plan: Data and Information in Online Environments Rogério Mugnaini, 2020-06-15 This book constitutes the refereed post-conference proceedings of the First International Conference on Data and Information in Online Environments, DIONE 2020, which took place in Florianópolis, Brazil, in March 2020. DIONE 2020 handles the growing interaction between the information sciences, communication sciences and computer sciences. The 18 revised full papers were carefully reviewed and selected from 37 submissions and focus on the production, dissemination and evaluation of contents in online environments. The goal is to improve cooperation between data science, natural language processing, data engineering, big data, research evaluation, network science, sociology of science and communication communities. |
| data management and sharing plan: A Practical Guide for Informationists Antonio P DeRosa, 2018-02-23 A Practical Guide for Informationists: Supporting Research and Clinical Practice guides new informationists to a successful career, giving them a pathway to this savvier, more technically advanced, domain-focused role in modern day information centers and libraries. The book's broad scope serves as an invaluable toolkit for healthcare professionals, researchers and graduate students in information management, library and information science, data management, informatics, etc. Furthermore, it is also ideal as a textbook for courses in medical reference services/medical informatics in MLIS programs. - Offer examples (e.g. case studies) of ways of delivering information services to end users - Includes recommendations, evidence and worksheets/take-aways/templates to be repurposed and adapted by the reader - Aimed at the broad area of healthcare and research libraries |
| data management and sharing plan: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| data management and sharing plan: Project Management for Researchers Shiri Noy, 2024-11-25 A step-by-step guide to developing a research organization system that works for you |
| data management and sharing plan: 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: Exploring Research Data Management Andrew Cox, Eddy Verbaan, 2018-05-11 Research Data Management (RDM) has become a professional topic of great importance internationally following changes in scholarship and government policies about the sharing of research data. Exploring Research Data Management provides an accessible introduction and guide to RDM with engaging tasks for the reader to follow and develop their knowledge. Starting by exploring the world of research and the importance and complexity of data in the research process, the book considers how a multi-professional support service can be created then examines the decisions that need to be made in designing different types of research data service from local policy creation, training, through to creating a data repository. Coverage includes: A discussion of the drivers and barriers to RDM Institutional policy and making the case for Research Data Services Practical data management Data literacy and training researchers Ethics and research data services Case studies and practical advice from working in a Research Data Service. This book will be useful reading for librarians and other support professionals who are interested in learning more about RDM and developing Research Data Services in their own institution. It will also be of value to students on librarianship, archives, and information management courses studying topics such as RDM, digital curation, data literacies and open science. |
| data management and sharing plan: Target-setting Methods and Data Management to Support Performance-based Resource Allocation by Transportation Agencies National Cooperative Highway Research Program, 2010 TRB's National Cooperative Highway Research Program (NCHRP) Report 666: Target Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies - Volume I: Research Report, and Volume II: Guide for Target-Setting and Data Management provides a framework and specific guidance for setting performance targets and for ensuring that appropriate data are available to support performance-based decision-making. Volume III to this report was published separately in an electronic-only format as NCHRP Web-Only Document 154. Volume III includes case studies of organizations investigated in the research used to develop NCHRP Report 666. |
| data management and sharing plan: Quality Management and Accreditation in Hematopoietic Stem Cell Transplantation and Cellular Therapy Mahmoud Aljurf, John A. Snowden, Patrick Hayden, Kim H. Orchard, Eoin McGrath, 2021-02-19 This open access book provides a concise yet comprehensive overview on how to build a quality management program for hematopoietic stem cell transplantation (HSCT) and cellular therapy. The text reviews all the essential steps and elements necessary for establishing a quality management program and achieving accreditation in HSCT and cellular therapy. Specific areas of focus include document development and implementation, audits and validation, performance measurement, writing a quality management plan, the accreditation process, data management, and maintaining a quality management program. Written by experts in the field, Quality Management and Accreditation in Hematopoietic Stem Cell Transplantation and Cellular Therapy: A Practical Guide is a valuable resource for physicians, healthcare professionals, and laboratory staff involved in the creation and maintenance of a state-of-the-art HSCT and cellular therapy program. |
| data management and sharing plan: Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems Mani, Nandita S., Cawley, Michelle A., 2022-05-06 Beyond providing space for data science activities, academic libraries are often overlooked in the data science landscape that is emerging at academic research institutions. Although some academic libraries are collaborating in specific ways in a small subset of institutions, there is much untapped potential for developing partnerships. As library and information science roles continue to evolve to be more data-centric and interdisciplinary, and as research using a variety of data types continues to proliferate, it is imperative to further explore the dynamics between libraries and the data science ecosystems in which they are a part. The Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems provides a global perspective on current and future trends concerning the integration of data science in libraries. It provides both a foundational base of knowledge around data science and explores numerous ways academicians can reskill their staff, engage in the research enterprise, contribute to curriculum development, and help build a stronger ecosystem where libraries are part of data science. Covering topics such as data science initiatives, digital humanities, and student engagement, this book is an indispensable resource for librarians, information professionals, academic institutions, researchers, academic libraries, and academicians. |
| data management and sharing plan: 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: Federal Register , 1970-06-16 |
| data management and sharing plan: Research Regulatory Compliance Mark A. Suckow, Bill Yates, 2015-06-14 Research Regulatory Compliance offers the latest information on regulations and compliance in the laboratory. With the increasing complexity of regulations and need for institutional infrastructure to deal with compliance of animal use issues, as well as a requirement surrounding human subjects, this publication provides reputable guidance and information. The book is extremely helpful as a resource for researchers, administrators, and technicians in the laboratory, and is also a great asset for faculty or new researchers coming in to the laboratory environment. It will help prepare users for the deluge of regulatory and compliance issues they will face while conducting their scientific programs. The book is edited and authored by known leaders in the field of compliance and regulations, and contains extensive research on the topics. It represents the new standard for information in every laboratory. - Provides a one-stop , go-to resource for the many regulatory and compliance issues that affect laboratory study and research models - Extremely helpful as a resource for researchers, administrators, and technicians in the laboratory, and also a great asset for faculty or new researchers coming in to the laboratory environment - Focuses on United States regulations, covering both animal models and human subjects - Written and edited by known leaders in the field of regulatory compliance who bring many years of collective experience to the book |
| data management and sharing plan: Evaluating and Measuring the Value, Use and Impact of Digital Collections Lorna M. Hughes, 2012 A huge investment has been made in digitizing scholarly and cultural heritage materials through initiatives based in museums, libraries and archives, as well as higher education institutions. The 'Digital Economy' is an important component of institutional planning, and much attention is given to the investment in digital projects and programmes. However, few initiatives have examined the actual use, value and impact of digital collections, and the role of digital collections in the changing information environment. As the creative, cultural and educational sector faces a period of restricted funding, it is timely to re-examine the use of the digital collections that have been created in the past twenty years, and to consider their value to the institutions that host them and to the communities of users they serve. This book brings together a group of international experts to consider the following key issues: What is the role of digital resources in the research life cycle? Do the arts and humanities face a 'data deluge'? How are digital collections to be sustained over the long term? How is use and impact to be assessed? What is the role of digital collections in the 'digital economy'? How is public engagement with digital cultural heritage materials to be assessed and supported? This book will be of interest to academics, librarians, archivists and the staff of cultural heritage organizations, as well as funders and other key stakeholders with an interest in the development and long term sustainability of digital collections.--Publisher's website. |
| data management and sharing plan: 100 Activities for Teaching Research Methods Catherine Dawson, 2016-08-08 A sourcebook of exercises, games, scenarios and role plays, this practical, user-friendly guide provides a complete and valuable resource for research methods tutors, teachers and lecturers. Developed to complement and enhance existing course materials, the 100 ready-to-use activities encourage innovative and engaging classroom practice in seven areas: finding and using sources of information planning a research project conducting research using and analyzing data disseminating results acting ethically developing deeper research skills. Each of the activities is divided into a section on tutor notes and student handouts. Tutor notes contain clear guidance about the purpose, level and type of activity, along with a range of discussion notes that signpost key issues and research insights. Important terms, related activities and further reading suggestions are also included. Not only does the A4 format make the student handouts easy to photocopy, they are also available to download and print directly from the book’s companion website for easy distribution in class. |
| data management and sharing plan: Audit and Accounting Guide AICPA, 2019-08-14 State and local government audit and accounting is changing rapidly. This title features insights, comparisons, and best practices for some of the more complex areas such as pensions and post-employment benefits other than pensions (OPEB), this authoritative guide provides complete coverage of audit and accounting considerations critical for both preparers and auditors. This edition includes dual guidance for accountants and auditors early implementing GASB Statement No. 84, Fiduciary Activities. Topics covered also include: • Financial reporting and the financial reporting entity • Revenue and expense recognition • Capital asset accounting • The elements of net position • Accounting for fair value • Municipal securities offerings • Tax abatements |
| data management and sharing plan: Farm data management, sharing and services for agriculture development Food and Agriculture Organization of the United Nations , 2021-02-26 This book aims to strengthen the skills of professionals who use, manage data for the benefit of farmers and farmers organizations by exposing them to the topics of importance of data in the agriculture value chain and how new and existing technologies, products and services can leverage farm level and global data to improve yield, reduce loss, add value and increase profitability and resilience. |
| data management and sharing plan: A-Z of Digital Research Methods Catherine Dawson, 2019-07-10 This accessible, alphabetical guide provides concise insights into a variety of digital research methods, incorporating introductory knowledge with practical application and further research implications. A-Z of Digital Research Methods provides a pathway through the often-confusing digital research landscape, while also addressing theoretical, ethical and legal issues that may accompany each methodology. Dawson outlines 60 chapters on a wide range of qualitative and quantitative digital research methods, including textual, numerical, geographical and audio-visual methods. This book includes reflection questions, useful resources and key texts to encourage readers to fully engage with the methods and build a competent understanding of the benefits, disadvantages and appropriate usages of each method. A-Z of Digital Research Methods is the perfect introduction for any student or researcher interested in digital research methods for social and computer sciences. |
| data management and sharing plan: Data Management for Libraries Laura Krier, Carly A. Strasser, 2014 Since the National Science Foundation joined the National Institutes of Health in requiring that grant proposals include a data management plan, academic librarians have been inundated with related requests from faculty and campus-based grant consulting offices. Data management is a new service area for many library staff, requiring careful planning and implementation. This guide offers a start-to-finish primer on understanding, building, and maintaining a data management service, showing another way the academic library can be invaluable to researchers. Krier and Strasser of the California Digital Library guide readers through every step of a data management plan by Offering convincing arguments to persuade researchers to create a data management plan, with advice on collaborating with them Laying out all the foundations of starting a service, complete with sample data librarian job descriptions and data management plans Providing tips for conducting successful data management interviews Leading readers through making decisions about repositories and other infrastructure Addressing sensitive questions such as ownership, intellectual property, sharing and access, metadata, and preservation This LITA guide will help academic librarians work with researchers, faculty, and other stakeholders to effectively organize, preserve, and provide access to research data. |
| data management and sharing plan: Sandy Beach Morphodynamics Derek Jackson, Andrew Short, 2020-05-19 Sandy beaches represent some of the most dynamic environments on Earth and examining their morphodynamic behaviour over different temporal and spatial scales is challenging, relying on multidisciplinary approaches and techniques. Sandy Beach Morphodynamics brings together the latest research on beach systems and their morphodynamics and the ways in which they are studied in 29 chapters that review the full spectrum of beach morphodynamics. The chapters are written by leading experts in the field and provide introductory level understanding of physical processes and resulting landforms, along with more advanced discussions. - Includes chapters that are written by the world's leading experts, including the latest up-to-date thinking on a variety of subject areas - Covers state-of-the-art techniques, bringing the reader the latest technologies/methods being used to understand beach systems - Presents a clear-and-concise description of processes and techniques that enables a clear understanding of coastal processes |
| data management and sharing plan: Encyclopedia of Ecology Brian D. Fath, 2018-08-23 Encyclopedia of Ecology, Second Edition, Four Volume Set continues the acclaimed work of the previous edition published in 2008. It covers all scales of biological organization, from organisms, to populations, to communities and ecosystems. Laboratory, field, simulation modelling, and theoretical approaches are presented to show how living systems sustain structure and function in space and time. New areas of focus include micro- and macro scales, molecular and genetic ecology, and global ecology (e.g., climate change, earth transformations, ecosystem services, and the food-water-energy nexus) are included. In addition, new, international experts in ecology contribute on a variety of topics. Offers the most broad-ranging and comprehensive resource available in the field of ecology Provides foundational content and suggests further reading Incorporates the expertise of over 500 outstanding investigators in the field of ecology, including top young scientists with both research and teaching experience Includes multimedia resources, such as an Interactive Map Viewer and links to a CSDMS (Community Surface Dynamics Modeling System), an open-source platform for modelers to share and link models dealing with earth system processes |
| data management and sharing plan: Information Literacy in the Workplace Serap Kurbanoğlu, Joumana Boustany, Sonja Špiranec, Esther Grassian, Diane Mizrachi, Loriene Roy, 2018-01-25 This book constitutes the refereed post-conference proceedings of the 5th European Conference on Information Literacy, ECIL 2017, held in Saint Malo, France, in September 2017. The 84 revised papers included in this volume were carefully reviewed and selected from 358 submissions. The papers cover a wide range of topics in the field of information literacy and focus on information literacy in the workplace. They are organized in the following topical sections: workplace information literacy, employibility and career readiness; data literacy and research data management; media literacy; copyright literacy; transliteracy, reading literacy, digital literacy, financial literacy, search engine literacy, civic literacy; science literacy; health information literacy; information behavior; information literacy in higher education; information literacy in K-12; information literacy instruction; information literacy and libraries; and theoretical framework. |
| data management and sharing plan: Anthropological Data in the Digital Age Jerome W. Crowder, Mike Fortun, Rachel Besara, Lindsay Poirier, 2019-11-01 For more than two decades, anthropologists have wrestled with new digital technologies and their impacts on how their data are collected, managed, and ultimately presented. Anthropological Data in the Digital Age compiles a range of academics in anthropology and the information sciences, archivists, and librarians to offer in-depth discussions of the issues raised by digital scholarship. The volume covers the technical aspects of data management—retrieval, metadata, dissemination, presentation, and preservation—while at once engaging with case studies written by cultural anthropologists and archaeologists returning from the field to grapple with the implications of producing data digitally. Concluding with thoughts on the new considerations and ethics of digital data, Anthropological Data in the Digital Age is a multi-faceted meditation on anthropological practice in a technologically mediated world. |
| data management and sharing plan: 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 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 Management Plan – EXAMPLE - Oregon State …
Data Management Plan – EXAMPLE . Proposal Title . Oregon State University is committed to ensuring excellent data management in their research with NSF. The data management plan in …
How to prepare a budget for your data management plan
Budgeting for Data Management & Sharing Unallowable costs: Infrastructure costs that are included in institutional overhead Facilities and Administrative costs: facilities operation and …
Guidelines for Data Management Plans Templates and …
The Data Management Plan you submit may be posted to the internet by NOAA, and serves to document how the recipient intends to comply with their award conditions related to collecting …
Data Management and Sharing Plan - wooster.edu
Data Management and Sharing Plan . Specific Proposal Considerations. Both the NSF and NIH require a Data Management and Sharing Plan to be included as part of all proposal …
Resource Sharing Plans - grants.nih.gov
address ‘Data Sharing’ or ‘Genomic Sharing Plan’ in their reviews. They will only address sharing of . Model Organisms and other Research Tools under the ‘Resource Sharing Plans’ …
Writing an Effective Data Management Plan - Rice University
Mar 11, 2016 · Writing an Effective Data Management Plan. Lisa Spiro, Melissa Wentz & Erik Engquist. Rice University. March 11, 2016. Outline. 1. Discuss challenges in developing data …
NIH Data Management and Sharing (DMS) Policy: Generalist …
Elements of a Data Management and Sharing Plan • Data type – Identifying data to be preserved and shared • Related tools, software, code – Tools and software needed to access and …
NIH Data Management and Sharing Policy: Applicable …
A comprehensive listing of all activity codes that generally require applicants to submit a Data Management and Sharing Plan. Read funding opportunities Read funding opportunities …
Data Sharing Plan Preparation Guidelines - era4health.eu
Making data sharing a reality. Describe research data. management and sharing (data. management plan). Researchers should ensure that data sharing is. considered from the very …
NIDDK Example Data Management and Sharing Plan Non …
Jan 19, 2023 · Element 4: Data Preservation, Access, and Associated Timelines . A. Repository where scientific data and metadata will be archived: The sample Data Management and …
How to Develop a Data Management and Sharing Plan
The content of a data management and sharing plan Management Plan The guidance in this section is structured around the six core themes of the DCC Checklist for a Data 8. Next to …
Federal Data Management Plans (DMPs) - research.arizona.edu
The NHLBI Supplement to the NIH Policy for Data Management and Sharing (NIH DMS Policy) is effective as of May 25, 2023.This NHLBI Supplement replaces the previous . NHLBI Policy for . …
The NIH Data Management and Sharing Policy: - Cancer
Data Management and Sharing Plans should maximize appropriate sharing: Justifiable ethical, legal, and technical factors for limiting sharing of data include: • Informed consent will not …
DATA MANAGEMENT AND SHARING PLAN - Perelman …
The Office of Sponsored Programs at University X has created a data management and sharing plan compliance system as part of their process for submitting the annual NIH progress report. …
NIDDK Example Data Management and Sharing Plan …
Dec 8, 2022 · Shared data generated from this project will report subject-specific kidney volumes by using the study assigned ID, which has already been de-identified. Element 6: Oversight of …
DATA MANAGEMENT AND SHARING PLAN A. Types and …
Element 6: Oversight of Data Management and Sharing: Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., …
NIH RPPR Instruction Guide - grants.nih.gov
reporting requirements for the Data Management and Sharing Plan; parallel updates made throughout Section 7 for specific RPPR types. • Updated 6.7 Section G Special Reporting …
Dissemination and Sharing of Research Results - University of …
NSF does not prescribe specific content for the data management plan. The data management plan is two pages maximum, and does not count against the 15-page limit Broadly, the data …
OMB No. 0925-0001 and 0925-0002, DMS Plan Format Page
The study PI will be overseeing execution of this Data Management and Sharing Plan. X PI will be assessing quality metrics and will determine when data are of a sufficient quality to be shared …
Tips for Writing a Data Management and Sharing (DMS) Plan
Tips for Writing a Data Management and Sharing (DMS) Plan Researchers: Use the following tips to create a DMS Plan for your NIH-funded research projects. Refer to the detailed instructions …
DATA MANAGEMENT AND SHARING PLAN
sharing.nih.gov. he Plan is recommended not to exceed two pages.T Text in italics should be deleted. There is no “form page” for the Data Management and Sharing Plan. The DMS Plan …
Data management plans - UK Data Service
• Many research funders require planning for data management and data sharing in research applications • Expect to cost sustainable data management and sharing into research • …
NIH Data Management & Sharing Policy (Effective 2023): A …
Oct 26, 2022 · The Data Management and Sharing (DMS) plan should be a one- to two-page document submitted with the general funding application as a PDF attachment. If a …
U.S. Office of Personnel Management Data Strategy
necessary data skills to improve data collection, management, analysis, sharing, and dissemination. In its central role leading Federal agencies in people management policies and …
Final NIH Policy for Data Management and Sharing
The new requirements will require a data management and sharing plan for ALL NIH-funded projects, an expansion from the current requirement for projects over $500K in annual direct …
Completing the Project Data Management Plan - NASA
• Directed Research projects will use a Condensed Data Management Plan in the Task Synopsis because a full DMP is too large for the scope of this research type. ... Software Sharing Plan …
Data Management Plan - Montana Health Alert Network
Data Management and Security section. Relevant sections of these documents are summarized in this Data Management Plan. CDCPB Data Security Policies and Guidance D ocuments 1) …
Data Management Sharing Plan: Fostering Effective Trans …
Data Management Sharing Plan: Fostering Effective Trans-Disciplinary Communication in Collaborative Research *Cristo Ernesto Yáñez León1, and James Lipuma2 1New Jersey …
DATA MANAGEMENT AND SHARING PLAN A. Types and …
Element 6: Oversight of Data Management and Sharing: All data management and sharing practices will be monitored, reviewed, and discussed by the PI who will assume the primary …
Budgeting tips for the new NIH Policy on Data Management …
When a DMS plan is required, you must include a “Data Management and Sharing Justification” within the budget justification. (For modular budgets, the additional narrative justification is …
Data Management Plan
Data Management Plan . Form and Instructions ... DMPs also enable supervisors to ensure that their staff have the required resources to comply with digital data management and sharing …
NHLBI Supplement to the NIH Policy for Data Management …
Dec 15, 2023 · repository according to its approved Data Management and Sharing Plan. NHLBI-administered parent studies must comply with the data management and sharing policies and …
Data and Information Sharing Plan Guidance and Resources
Apr 1, 2024 · 2025 Funding Opportunity must include a data and information sharing plan (DISP). A DISP describes how data and information sharing requirements specified in the funding …
Effective January 25,2023 NIH Data Management and …
NIH NOT-OD-21-014 Supplemental Information to the NIH Policy for Data Management and Sharing: Elements of an NIH Data Management and Sharing Plan This supplemental …
MWCCS Data Management and Sharing Plan for Ancillary …
with the Data Management and Sharing Plan approved by the funding Institute or Center. The DMS Policy applies to all research, funded or conducted in whole or in part by NIH, that results …
Data Management and Sharing What you need to know
1.Submission of a two-page data management and sharing plan:Research proposals without a Plan will not be considered for funding. 2.Compliance with the approved plan.Failure to provide …
NIH Data Management and Sharing Policy
An optional Data Management and Sharing Plan format page will be provided. A preview version of this format page is available now. • A final fillable version will be available by Fall 2022 and …
NIH Policy for Data Management and Sharing
Data Management and Sharing Plan (Plan): A plan describing the data management, preservation, and sharing of scientific data and accompanying metadata. Data Management: …
Data Management Standard Operating Procedure DMSOP) …
separate project-specific data management plans as well to sufficiently describe some of the project specific data management processes. SECTION 3: DATA SHARING a) Discuss data …
NIH Data Management & Sharing Policy - Medical …
• Elements to Include in a Data Management and Sharing Plan • Sample Plans • Assessment of Data Management and Sharing Plans • Revising Data Management and Sharing Plans • …
ARMY DATA PLAN
Policymaking Act of 2018 that set Federal goals for data sharing and management. Data enabled decisions, decisions that will outpace an adversary, will decide future battles.
DOD Data Strategy - U.S. Department of Defense
4 Essential Capabilities necessary to enable all goals: 1.) Architecture – DoD architecture, enabled by enterprise cloud and other technologies, must allow pivoting on data more rapidly …
Frequently Asked Questions(FAQ) for Contracts NIH Policy for …
Q: For contracts, is a separate Genomic Data Sharing (GDS) Plan still required? R: Separate Genomic Data Sharing (GDS) plans are no longer required, however, plans for the sharing …
Data Management & Sharing Plan - ctg.queensu.ca
Data Management & Sharing Plan Doc. No: CTG-POL-0043 Version: V006 Date: 2025FEB12 Page 6 of 7. 9 Release Conditions and Disclaimer . In circumstances where, for whatever …
Write a Data Management Plan - UK Data Service
• Many research funders require planning for data management and data sharing in research applications • Expect to cost sustainable data management and sharing into research • …
NIH Data Management and Sharing Policy 2023: Overview …
2003: Data Sharing Policy requires investigators seeking $500,000 or more in NIH funding to submit a data sharing plan (or rationale for not sharing). Superseded by the new policy in …
DATA MANAGEMENT AND SHARING PLAN An example …
sharing.nih.gov. The Plan is recommended not to exceed two pages. Text in italics should be deleted (but this has not been done in the sample below). There is no “form page” for the Data …
Data Management and Sharing Overview - National …
Writing a Data Management & Sharing Plan. See . Budgeting for Data Management & Sharing. DMS Plan Content Plan Elements Data Type. Related Tools, Software and/or Code. …
Sample DMS Plan – Human Genomic Data Project - Perelman …
OMB No. 0925-0001 and 0925-0002 (Rev. 07/2022 Approved Through TBD) Sample DMS Plan – Human Genomic Data Project . DATA MANAGEMENT AND SHARING PLAN If any of the …
Data Management and Sharing Overview - National …
Writing a Data Management & Sharing Plan. See . Budgeting for Data Management & Sharing. DMS Plan Content Plan Elements Data Type. Related Tools, Software and/or Code. …
