Ensuring The Integrity Accessibility And Stewardship Of Research Data In The Digital Age

As digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data; standards that do not keep pace with the high rate of innovation; restrictions on data sharing that reduce the ability of researchers to verify results and build on previous research; and huge increases in the amount of data being generated, creating severe challenges in preserving that data for long-term use. Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects. The report recommends that all researchers receive appropriate training in the management of research data, and calls on researchers to make all research data, methods, and other information underlying results publicly accessible in a timely manner. The book also sees the stewardship of research data as a critical long-term task for the research enterprise and its stakeholders. Individual researchers, research institutions, research sponsors, professional societies, and journals involved in scientific, engineering, and medical research will find this book an essential guide to the principles affecting research data in the digital age.

The digital era provides researchers with greatly enhanced ability to analyze and share data, but a new report warns that technology also makes it easier for data to be distorted. The report, from the National Academy of Sciences, National Academy of Engineering, and Institute of Medicine, recommends that research institutions ensure that every investigator receives appropriate training on managing data responsibly. Further, the report urges these institutions, along with professional societies, journals and research sponsors, to develop standards for ensuring the integrity of research data and specific data-management guidelines to account for new technologies.

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.

This report contains the proceedings of a one-day workshop organized by the National Research Council's Board on Science, Technology, and Economic Policy (STEP), in conjunction with a study by a panel of the NRC Committee on National Statistics (CNSTAT). This combined activity was commissioned by the Science Resources Statistics Division (SRS) of the National Science Foundation (NSF) to recommend improvements in the Foundation's portfolio of surveys of research and development spending by the federal government, state governments, private industry, the nation's universities and colleges, and other nonprofit institutions.

The integrity of knowledge that emerges from research is based on individual and collective adherence to core values of objectivity, honesty, openness, fairness, accountability, and stewardship. Integrity in science means that the organizations in which research is conducted encourage those involved to exemplify these values in every step of the research process. Understanding the dynamics that support â€" or distort â€" practices that uphold the integrity of research by all participants ensures that the research enterprise advances knowledge. The 1992 report Responsible Science: Ensuring the Integrity of the Research Process evaluated issues related to scientific responsibility and the conduct of research. It provided a valuable service in describing and analyzing a very complicated set of issues, and has served as a crucial basis for thinking about research integrity for more than two decades. However, as experience has accumulated with various forms of research misconduct, detrimental research practices, and other forms of misconduct, as subsequent empirical research has revealed more about the nature of scientific misconduct, and because technological and social changes have altered the environment in which science is conducted, it is clear that the framework established more than two decades ago needs to be updated. Responsible Science served as a valuable benchmark to set the context for this most recent analysis and to help guide the committee's thought process. Fostering Integrity in Research identifies best practices in research and recommends practical options for discouraging and addressing research misconduct and detrimental research practices.

In a rapidly changing technological environment, the difficult task of ensuring long-term access to digital information is increasingly important. The Digital Curation Bibliography: Preservation and Stewardship of Scholarly Works presents over 665 English-language articles, books, and technical reports that are useful in understanding digital curation and preservation. This selective bibliography covers digital curation and preservation copyright issues, digital formats (e.g., data, media, and e-journals), metadata, models and policies, national and international efforts, projects and institutional implementations, research studies, services, strategies, and digital repository concerns. Most sources have been published from 2000 through 2011; however, a limited number of key sources published prior to 2000 are also included. The bibliography includes links to freely available versions of included works, such as e-prints and open access articles.

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.

The growth of electronic publishing of literature has created new challenges, such as the need for mechanisms for citing online references in ways that can assure discoverability and retrieval for many years into the future. The growth in online datasets presents related, yet more complex challenges. It depends upon the ability to reliably identify, locate, access, interpret, and verify the version, integrity, and provenance of digital datasets. Data citation standards and good practices can form the basis for increased incentives, recognition, and rewards for scientific data activities that in many cases are currently lacking in many fields of research. The rapidly-expanding universe of online digital data holds the promise of allowing peer-examination and review of conclusions or analysis based on experimental or observational data, the integration of data into new forms of scholarly publishing, and the ability for subsequent users to make new and unforeseen uses and analyses of the same data-either in isolation, or in combination with, other datasets. The problem of citing online data is complicated by the lack of established practices for referring to portions or subsets of data. There are a number of initiatives in different organizations, countries, and disciplines already underway. An important set of technical and policy approaches have already been launched by the U.S. National Information Standards Organization (NISO) and other standards bodies regarding persistent identifiers and online linking. The workshop summarized in For Attribution-Developing Data Attribution and Citation Practices and Standards: Summary of an International Workshop was organized by a steering committee under the National Research Council's (NRC's) Board on Research Data and Information, in collaboration with an international CODATA-ICSTI Task Group on Data Citation Standards and Practices. The purpose of the symposium was to examine a number of key issues related to data identification, attribution, citation, and linking to help coordinate activities in this area internationally, and to promote common practices and standards in the scientific community.