Data Management And Sharing Plan Example

  data management and sharing plan example: 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: 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: 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 example: 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: 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 example: 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 example: 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: 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 example: 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: 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: 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: 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 example: Guidelines for designing data collection and sharing systems for co-managed fisheries. 1. Practical guide Ashley S. Halls, 2005
  data management and sharing plan example: 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: 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 example: 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 example: Caring for Digital Data in Archaeology Archaeology Data Service, Digital Antiquity, 2013 A wide variety of organizations are both creating and retaining digital data from archaeological projects. While current methods for preservation and access to data vary widely, nearly all of these organizations agree that careful management of digital archaeological resources is an important aspect of responsible archaeological stewardship. The Archaeology Data Service and Digital Antiquity have produced this guide to provide information on the best way to create, manage, and document digital data files produced during the course of an archaeological project. This guide aims to improve the practice of depositing and preserving digital information safely within an archive for future use and is structured in three main parts: Digital Archiving - looks at the fundamentals of digital preservation and covers general preservation themes within the context of archaeological investigations, research, and resource management, with an overview of digital archiving practice and guidance.The Project Life cycle - looks at common project life cycle elements such as file naming, meta-data creation, and copyright and covers general, broad themes that should be considered at the outset of a project.Basic Components - looks at selected technique and file type-specific issues together with archive structuring and deposit. This section covers common file types that are frequently present in archaeological archives, irrespective of a project's primary technique or focus.The accompanying online Guides to Good Practice take these elements further and address the preservation of data resulting from common data collection, processing and analysis techniques such as aerial and geophysical survey, laser scanning, GIS and CAD.
  data management and sharing plan example: Audit and Accounting Guide AICPA, 2018-06-15 With all the recent changes in state and local government audit and accounting, including changes to some of the more complex areas such as pensions and post-employment benefits other than pensions (OPEB), accountants and financial managers can't afford to be without the most current guidance. This authoritative guide provides complete coverage of audit and accounting considerations critical for both preparers and auditors. This edition includes two new schedules: Governmental Employer Participation in Single-Employer Plans: Illustrative Schedule of Pension Amounts and Report; and, Illustrative Notes to Schedule of Employer Allocations and Schedule of Pension Amounts. It also provides insights, comparisons, and best practices for 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 and much more.
  data management and sharing plan example: Developing Librarian Competencies for the Digital Age Jeffrey G. Coghill, Roger G. Russell, 2016-11-29 Librarianship is both an art and a science. Librarians study the science of information and how to work with clients to help them find solutions to their information needs. They also learn quickly that there is an art to working with people, to finding the answers to tough questions using the resources available and knowing which information resources to use to find the information being sought in short order. But, what technical skills do librarians need to be successful in the future? How can library managers best develop their staffs for success? Developing Librarian Competencies for the Digital Age explores questions such as: What is the composition of a modern library collection? Will that collection look different in the future? What are the information sources and how do we manage those? What are the technical skills needed for a 21st century librarian? How will reference services change and adapt to embrace new ways to interact with library patrons or clients? What kinds of library skills are needed for the librarian of today to grow and thrive, now and into the future? How will service models change to existing clients and how will the model change going into the future of librarianship? What kinds of budgeting challenges are there for libraries and the administrators who oversee these libraries? What do the library professional organizations see as the core skills needed for new graduates and those practicing in the profession going into the future? In answering those questions, the book identifies specific digital skills needed for success, ways of developing those skills, and ways of assessing them.
  data management and sharing plan example: Engineering Research Herman Tang, 2020-12-30 Master the fundamentals of planning, preparing, conducting, and presenting engineering research with this one-stop resource Engineering Research: Design, Methods, and Publication delivers a concise but comprehensive guide on how to properly conceive and execute research projects within an engineering field. Accomplished professional and author Herman Tang covers the foundational and advanced topics necessary to understand engineering research, from conceiving an idea to disseminating the results of the project. Organized in the same order as the most common sequence of activities for an engineering research project, the book is split into three parts and nine chapters. The book begins with a section focused on proposal development and literature review, followed by a description of data and methods that explores quantitative and qualitative experiments and analysis, and ends with a section on project presentation and preparation of scholarly publication. Engineering Research offers readers the opportunity to understand the methodology of the entire process of engineering research in the real word. The author focuses on executable process and principle-guided exercise as opposed to abstract theory. Readers will learn about: An overview of scientific research in engineering, including foundational and fundamental concepts like types of research and considerations of research validity How to develop research proposals and how to search and review the scientific literature How to collect data and select a research method for their quantitative or qualitative experiment and analysis How to prepare, present, and submit their research to audiences and scholarly papers and publications Perfect for advanced undergraduate and engineering students taking research methods courses, Engineering Research also belongs on the bookshelves of engineering and technical professionals who wish to brush up on their knowledge about planning, preparing, conducting, and presenting their own scientific research.
  data management and sharing plan example: Preserving Digital Materials Ross Harvey, 2011-11-30 This book provides a single-volume introduction to the principles, strategies and practices currently applied by librarians and recordkeeping professionals to the critical issue of preservation of digital information. It incorporates practice from both the recordkeeping and the library communities, taking stock of current knowledge about digital preservation and describing recent and current research, to provide a framework for reflecting on the issues that digital preservation raises in professional practice.
  data management and sharing plan example: 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: Data Stewardship in Action Pui Shing Lee, 2024-02-16 Take your organization's data maturity to the next level by operationalizing data governance Key Features Develop the mindset and skills essential for successful data stewardship Apply practical advice and industry best practices, spanning data governance, quality management, and compliance, to enhance data stewardship Follow a step-by-step program to develop a data operating model and implement data stewardship effectively Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the competitive data-centric world, mastering data stewardship is not just a requirement—it's the key to organizational success. Unlock strategic excellence with Data Stewardship in Action, your guide to exploring the intricacies of data stewardship and its implementation for maximum efficiency. From business strategy to data strategy, and then to data stewardship, this book shows you how to strategically deploy your workforce, processes, and technology for efficient data processing. You’ll gain mastery over the fundamentals of data stewardship, from understanding the different roles and responsibilities to implementing best practices for data governance. You’ll elevate your data management skills by exploring the technologies and tools for effective data handling. As you progress through the chapters, you’ll realize that this book not only helps you develop the foundational skills to become a successful data steward but also introduces innovative approaches, including leveraging AI and GPT, for enhanced data stewardship. By the end of this book, you’ll be able to build a robust data governance framework by developing policies and procedures, establishing a dedicated data governance team, and creating a data governance roadmap that ensures your organization thrives in the dynamic landscape of data management.What you will learn Enhance your job prospects by understanding the data stewardship field, roles, and responsibilities Discover how to develop a data strategy and translate it into a functional data operating model Develop an effective and efficient data stewardship program Gain practical experience of establishing a data stewardship initiative Implement purposeful governance with measurable ROI Prioritize data use cases with the value and effort matrix Who this book is for This book is for professionals working in the field of data management, including business analysts, data scientists, and data engineers looking to gain a deeper understanding of the data steward role. Senior executives who want to (re)establish the data governance body in their organizations will find this resource invaluable. While accessible to both beginners and professionals, basic knowledge of data management concepts, such as data modeling, data warehousing, and data quality, is a must to get started.
  data management and sharing plan example: Ethics in Qualitative Research Tina Miller, Maxine Birch, Melanie Mauthner, Julie Jessop, 2012-09-13 This fresh, confident second edition expands its focus on the theoretical and practical aspects of doing qualitative research in light of new ethical dilemmas facing researchers today. In a climate of significant social and technological change, researchers must respond to increased ethical regulation and scrutiny of research. New sources, types of data and modes of accessing participants are all challenging and reconfiguring traditional ideas of the research relationship. This engaging textbook explores key ethical dilemmas - including research boundaries, informed consent, participation, rapport and analysis - within the context of a rapidly changing research environment. The book effectively covers the ethical issues related to the data collection process, helping readers to address the ethical considerations relevant to their research. This fully updated new edition: - Maps the changing and increasingly technology-reliant aspects of research relationships and practices - Provides researchers with guidance through practical examples, enabling those engaged in qualitative research to question and navigate in ethical ways This book is essential reading for all those engaged in qualitative research across the social sciences.
  data management and sharing plan example: 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 example: Data Information Literacy Jake Carlson, Lisa R. Johnston, 2015-01-15 Given the increasing attention to managing, publishing, and preserving research datasets as scholarly assets, what competencies in working with research data will graduate students in STEM disciplines need to be successful in their fields? And what role can librarians play in helping students attain these competencies? In addressing these questions, this book articulates a new area of opportunity for librarians and other information professionals, developing educational programs that introduce graduate students to the knowledge and skills needed to work with research data. The term data information literacy has been adopted with the deliberate intent of tying two emerging roles for librarians together. By viewing information literacy and data services as complementary rather than separate activities, the contributors seek to leverage the progress made and the lessons learned in each service area. The intent of the publication is to help librarians cultivate strategies and approaches for developing data information literacy programs of their own using the work done in the multiyear, IMLS-supported Data Information Literacy (DIL) project as real-world case studies. The initial chapters introduce the concepts and ideas behind data information literacy, such as the twelve data competencies. The middle chapters describe five case studies in data information literacy conducted at different institutions (Cornell, Purdue, Minnesota, Oregon), each focused on a different disciplinary area in science and engineering. They detail the approaches taken, how the programs were implemented, and the assessment metrics used to evaluate their impact. The later chapters include the DIL Toolkit, a distillation of the lessons learned, which is presented as a handbook for librarians interested in developing their own DIL programs. The book concludes with recommendations for future directions and growth of data information literacy. More information about the DIL project can be found on the project's website: datainfolit.org.
  data management and sharing plan example: 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: OECD Urban Studies Smart City Data Governance Challenges and the Way Forward OECD, 2023-10-13 Smart cities leverage technologies, in particular digital, to generate a vast amount of real-time data to inform policy- and decision-making for an efficient and effective public service delivery. Their success largely depends on the availability and effective use of data.
  data management and sharing plan example: Big Data Management, Technologies, and Applications Hu, Wen-Chen, 2013-10-31 This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data--Provided by publisher.
  data management and sharing plan example: 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 example: 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 example: Caring is Sharing — Exploiting the Value in Data for Health and Innovation M. Hägglund, M. Blusi, S. Bonacina, 2023-06-22 Modern information and communication technologies make it easier for individuals to be involved in their own health and social care. They also facilitate contact between individuals and service providers and deliver more efficient tools for healthcare staff. Artificial Intelligence (AI) promises to bring even more benefits in the future, with more effectiveness and the provision of decision support. This book presents the proceedings of the 33rd Medical Informatics Europe Conference, MIE2023, held in Gothenburg, Sweden, from 22 to 25 May 2023. The theme of MIE2023 was ‘Caring is Sharing – Exploiting Value in Data for Health and Innovation’, stressing the increasing importance of sharing digital-health data and the related challenges. The sharing of health data is developing rapidly, both in Europe and beyond, so the focus of the conference was on the enabling of trustworthy sharing of data to improve health. Topics covered include healthcare, community care, self-care, public health, and the innovation and development of future-proof digital-health solutions, and the almost 300 papers divided into 10 chapters also cover important advances in the sub domains of biomedical informatics: decision support systems, clinical information systems, clinical research informatics, knowledge management and representation, consumer health informatics, natural language processing, public health informatics, privacy, ethical and societal aspects among them. Describing innovative approaches to the collection, organization, analysis, and data-sharing related to health and wellbeing, the book contributes to the expertise required to take medical informatics to the next level, and will be of interest to all those working in the field.
  data management and sharing plan example: National Science Research Data Processing and Information Retrieval System, Hearings Before the General Subcommittee on Education....91-1, on H.R. 8809, April 29, 30, 1969 United States. Congress. House. Education and Labor, United States. Congress. House. Committee on Education and Labor. General Subcommittee on Education, 1969
  data management and sharing plan example: AICPA Audit and Accounting Guide State and Local Governments AICPA, 2017-09-25 With all the recent changes in state and local government audit and accounting, including changes to some of the more complex areas such as pensions and postemployment benefits other than pensions (OPEB), you can't afford to be without the most current guidance. This authoritative guide provides complete coverage of audit and accounting considerations critical for both preparers and auditors. This 2017 edition includes a new chapter on best practices for OPEB accounting, reporting, and auditing. It also provides insights, comparisons, and best practices for financial reporting and the financial reporting entity, revenue and expense recognition, capital asset accounting, the elements of net position, accounting for fair value, and much more.
  data management and sharing plan example: Research Methods Made Simple Catherine Dawson, 2024-10-30 Practical. Interactive. Engaging. This book provides an imaginative alternative to doing research methods. With visual prompts and easy-to-follow activities, it will help you understand the basic foundations of the research process in bite-sized pieces that suit your way of learning. Including activities such as word searches, crosswords, spider charts and puzzles, this book will help you gain a wider understanding of how, and why, specific research methods are used. Complete with a variety of learning features, this book will: Build your understanding of the core principles of research. Help you to interpret different methods and their practicalities. Aid you in identifying your weakness and adapting useful techniques to combat these. Stand as a visual toolkit that sets content out in bite-sized pieces. Perfect for beginners, this user-friendly guide will give you a deeper understanding of research methods through action, images, and visualization.
  data management and sharing plan example: Handbook on Using Administrative Data for Research and Evidence-based Policy Shawn Cole, Iqbal Dhaliwal, Anja Sautmann, 2021 This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.
  data management and sharing plan example: Hearings United States. Congress. House, 1969
  data management and sharing plan example: Hearings, Reports, Public Laws United States. Congress. House. Committee on Education and Labor, 1967
  data management and sharing plan example: Hearings United States. Congress. House. Committee on Education, 1969
  data management and sharing plan example: Information Literacy for Science and Engineering Students Mary DeJong, 2024-08-22 This engaging handbook gives students and working scientists and engineers the information literacy skills they need to find, evaluate, and use information. Beginning with a strong foundation in the utility, structure, and packaging of information, this useful handbook helps students and working professionals decode real-world information literacy problems. Mary DeJong provides a compelling context and rationale for the skills scientists and engineers need to succeed in challenging careers that rely on the successful discovering and sharing of complex information. Students will appreciate the in-depth information on sources, especially those needed for research assignments, and scientists and engineers who write for publication will benefit from chapters on searching databases and organizing and citing sources. Written with science and engineering students and professionals in mind, this book is thorough, well-paced, engaging, and even funny.
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 …

How to Develop a Data Management and Sharing Plan
This guide outlines the process of developing a data management and sharing plan. Planning for the effective creation, management and sharing of your data enables you to get the most out …

DATA MANAGEMENT AND SHARING PLAN
DATA MANAGEMENT AND SHARING PLAN . If any of the proposed research in the application involves the generation of scientific data, this application is subject to the NIH Policy for Data …

Data Management Plan - ACDM
The Data Management Plan (DMP) has multiple purposes and is used to comprehensively document the collection and handling of the data. This should represent the accountability ...

EXAMPLE DATA MANAGEMENT AND SHARING PLAN (in …
EXAMPLE DATA MANAGEMENT AND SHARING PLAN (in compliance with SF-424 Forms H) EXAMPLE FOR SINGLE CELL TRANSCRIPTOMICS ELEMENT 1: DATA TYPE A. Types and …

EXAMPLE DATA MANAGEMENT AND SHARING PLAN (in …
EXAMPLE DATA MANAGEMENT AND SHARING PLAN (in compliance with SF-424 Forms H) EXAMPLE FOR SECONDARY PHENOTYPIC AND CLINICAL DATA ELEMENT 1: DATA …

DATA SHARING PLANS - National Sea Grant College Program
Data Management Plan FAQs This document is for Qs and As about NOAA’s new data management plan requirements. It was ... single Program-wide data sharing plan, individual …

NIDDK Example Data Management and Sharing Plan …
NIDDK Example Data Management and Sharing Plan – Secondary Data Analysis Element 1: Data Type: A. Types and amount of scientific data expected to be generated in the project: This …

DATA MANAGEMENT AND SHARING PLAN
Sample DMS Plan – Survey/Interview Data Project . DATA MANAGEMENT AND SHARING PLAN If any of the proposed research in the application involves the generation of scientific …

DATA MANAGEMENT AND SHARING PLAN - NICHD
There is no “form page” for the Data Management and Sharing Plan. The DMS Plan may be provided in the format shown below. Public reporting burden for this collection of information is …

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 …

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 …

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. ... Some Principles Underlying Data Management/ …

Template for NSF Data Management Plan. In general, the …
policies regarding the release of data for access, for example, whether data are posted before or after formal publication. “Data sharing” refers to the release of data in response to a specific …

Guide to Developing Your NIH Data Management and …
The “Sample Text” sections are designed to provide example language, not for investigators to use as a template ... • Consult the sample plans listed in Writing a Data Management and …

NIDDK Example Data Management and Sharing Plan Non …
NIDDK Example Data Management and Sharing Plan – Non-Human Basic Research Element 1: Data Type : A. Types and amount of scientific data expected to be generated in the project: …

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 • …

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 …

DATA MANAGEMENT AND SHARING PLAN A. Types and …
DATA MANAGEMENT AND SHARING PLAN An example from an application focusing on secondary data analysis on data from human subjects. Element 1: Data Type A. Types and …

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 AND SHARING PLAN - University of …
Policy for Data Management and Sharing and requires submission of a Data Management and Sharing Plan. If the proposed research in the application will generate large-scale genomic …

Data Management Plan
A data management plan (DMP) describes how scientists will handle digital data both during research and after a research project is completed. Preparing a DMP before digital data are …

Data Management Plan - Open University
who hold ultimate responsibility for data management. Preparation of data for sharing and archiving 1. The institutional data drawn from the DIA’s server will be placed on the UniDrive …

NIH Office of Intramural Research (OIR)
plan must be submitted as part of the quadrennial review. If the proposed research will generate large-scale genomic data, the Genomic Data Sharing Policy also applies and should be …

Supplemental Information for the NIH Human Data Sharing …
DRAFT EXAMPLE DATA SHARING PLANS Example 1 –Checklist with or without sharing Data Sharing Plan for _____ What data will be shared? I will share human data generated in this …

Indiana University Guidance on NSF Data Management Plans
Data Management plans endorsed by the Office of the Vice President for Research and offered in a manner that is consistent with the Indiana University Information Technology Strategic Plan …

How to Develop a Data Management and Sharing Plan
This guide outlines the process of developing a data management and sharing plan. Planning for the effective creation, management and sharing of your data enables you to get the most out …

Dissemination and Sharing of Research Results - University …
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 …

Converting a resource sharing plan into a DMS Plan
This is an example of a resource sharing plan written by a PI prior to the 2023 NIH DMSP. Data Sharing Plan. ... DATA MANAGEMENT AND SHARING PLAN This is an example of the …

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. ... infrastructure necessary to provide local …

Data Management Plans for Archaeological Research – 2017
The DMP template provided in this guide will help you complete your data management plan. For example, you . 2 can use the template to address the requirement for such plans for NEH and …

Guide to Data Management Plans - Nutrition Incentive Hub
long-term preservation may be the same that are used to provide Data Sharing and Public Access. Estimate how much data will be preserved and state the planned retention period. …

DATA MANAGEMENT AND SHARING PLAN A. Types and …
The National Institute on Aging (NIA) Division of Neuroscience (DN) provides the following sample Data Management and Sharing Plan for a hypothetical project involving physiological study of …

Horizon Europe Data Management Plan Template - OpenAIRE
The Horizon Europe Model Grant Agreement requires that a data management plan (‘DMP’) is established and regularly updated. ... For example, X is regulator of Y is a much more qualified …

DATA MANAGEMENT AND SHARING PLAN - ImmPort
NIH guidance for writing a DMS plan is located here. DATA MANAGEMENT AND SHARING PLAN If any of the proposed research in the application involves the generation of scientific …

Data Management Plan example: - Leeds University Library
5 Plans for management and archiving of collected data As required by ESRC, this data management plan seeks to prepare the project data for future sharing and potential secondary …

Data Management Planning BBSRC funding applicants
Data Management Plan may be offered a conditional award; alternatively, a redrafted Data Management Plan may be requested. In individual cases, BBSRC reserves the right to take a …

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 …

BBSRC DATA SHARING POLICY - UK Research and …
All applications seeking research grant funding from BBSRC must submit a data management plan. This should include concise plans for data management and sharing as part of research …

Data Management Plan (DMP) Template - IITA
A data management plan 1is a formal statement describing how research ... departmental or group policies, for example in terms of the legal jurisdiction in which data are held or the ...

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 …

DOD Information Sharing Implementation Plan - U.S.
envisioned in the Strategy. Additionally, this plan provides amplifying guidance on achieving Goal 2, Information as a Strategic Asset, of the DoD Information Management (IM)/Information …

Example Data Management Plan - University of Oxford
ESRC-DFID Example Data Management Plan Existing data The research objectives require qualitative data that are not available from other sources. Some data exist that can be used to …

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 …

Guide to writing a Research Data Management Plan
folders or using a database management system to keep your data organized. 2. Associate data to rich metadata: Metadata provide the contextualization and description of a data object, …

How to write a data management plan (DMP) - TU Wien
1 Data description and collection or reuse of existing data 5 2 Documentation and data quality 8 3 Storage and backup during the research process 13 4 Legal and ethical requirements, codes …

Guidance for Review of Data Management Plans - National …
conduct of scientific research submit a data management plan (DMP) that includes, at a minimum: 1. a summary of activities that generate data 2. a summary of the types of data generated by …

Office of Research & Development Data Management and …
Data Management and Access Plan (DMAP) Template (Version: 7/29/16) ... NOTE: Where practicable, sharing should take place under a written agreement prohibiting the recipient from …

Sample NIH Modular Budget Justifications INSTRUCTIONS
months of effort per year in years two through five). Dr. Johnson will assist with software development and data analysis efforts. His effort is higher in year one because software …

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 …

Writing a Wellcome Trust Data Management & Sharing Plan
Data Management & Sharing Plan Report Version Control Version Date Author Change Description 1.3 02 September 2014 Gareth Knight ... Are any limits to data sharing required - …