Board on Research Data and Information – författare

The National Academies Roundtable on Aligning Incentives for Open Science, established in 2019, has taken on an important role in addressing issues with open science. The roundtable convenes critical stakeholders to discuss the effectiveness of current incentives for adopting open science practices, current barriers of all types, and ways to move forward in order to align reward structures and institutional values. The Roundtable convened a virtual public workshop on fostering open science practices on November 5, 2020. The broad goal of the workshop was to identify paths to growing the nascent coalition of stakeholders committed to reenvisioning credit/reward systems (e.g., academic hiring, tenure and promotion, and grants)to fully incentivize open science practices. The workshop explored the information and resource needs of researchers, research institutions, government agencies, philanthropies, professional societies, and other stakeholders interested in further supporting and implementing open science practices. This publication summarizes the presentations and discussion of the workshop.

While governments throughout the world have different approaches to how they make their public sector information (PSI) available and the terms under which the information may be reused, there appears to be a broad recognition of the importance of digital networks and PSI to the economy and to society. However, despite the huge investments in PSI and the even larger estimated effects, surprisingly little is known about the costs and benefits of different information policies on the information society and the knowledge economy.By understanding the strengths and weaknesses of the current assessment methods and their underlying criteria, it should be possible to improve and apply such tools to help rationalize the policies and to clarify the role of the internet in disseminating PSI. This in turn can help promote the efficiency and effectiveness of PSI investments and management, and to improve their downstream economic and social results. The workshop that is summarized in this volume was intended to review the state of the art in assessment methods and to improve the understanding of what is known and what needs to be known about the effects of PSI activities.

While governments throughout the world have different approaches to how they make their public sector information (PSI) available and the terms under which the information may be reused, there appears to be a broad recognition of the importance of digital networks and PSI to the economy and to society. However, despite the huge investments in PSI and the even larger estimated effects, surprisingly little is known about the costs and benefits of different information policies on the information society and the knowledge economy.By understanding the strengths and weaknesses of the current assessment methods and their underlying criteria, it should be possible to improve and apply such tools to help rationalize the policies and to clarify the role of the internet in disseminating PSI. This in turn can help promote the efficiency and effectiveness of PSI investments and management, and to improve their downstream economic and social results. The workshop that is summarized in this volume was intended to review the state of the art in assessment methods and to improve the understanding of what is known and what needs to be known about the effects of PSI activities.

Recent decades have witnessed an ever-increasing range and volume of digital data. All elements of the pillars of science—whether observation, experiment, or theory and modeling—are being transformed by the continuous cycle of generation, dissemination, and use of factual information. This is even more so in terms of the re-using and re-purposing of digital scientific data beyond the original intent of the data collectors, often with dramatic results.

We all know about the potential benefits and impacts of digital data, but we are also aware of the barriers, the challenges in maximizing the access, and use of such data. There is thus a need to think about how a data infrastructure can enhance capabilities for finding, using, and integrating information to accelerate discovery and innovation. How can we best implement an accessible, interoperable digital environment so that the data can be repeatedly used by a wide variety of users in different settings and with different applications?

With this objective: to use the microbial communities and microbial data, literature, and the research materials themselves as a test case, the Board on Research Data and Information held an International Symposium on Designing the Microbial Research Commons at the National Academy of Sciences in Washington, DC on 8-9 October 2009. The symposium addressed topics such as models to lower the transaction costs and support access to and use of microbiological materials and digital resources from the perspective of publicly funded research, public-private interactions, and developing country concerns. The overall goal of the symposium was to stimulate more research and implementation of improved legal and institutional models for publicly funded research in microbiology.

Recent decades have witnessed an ever-increasing range and volume of digital data. All elements of the pillars of science—whether observation, experiment, or theory and modeling—are being transformed by the continuous cycle of generation, dissemination, and use of factual information. This is even more so in terms of the re-using and re-purposing of digital scientific data beyond the original intent of the data collectors, often with dramatic results.

We all know about the potential benefits and impacts of digital data, but we are also aware of the barriers, the challenges in maximizing the access, and use of such data. There is thus a need to think about how a data infrastructure can enhance capabilities for finding, using, and integrating information to accelerate discovery and innovation. How can we best implement an accessible, interoperable digital environment so that the data can be repeatedly used by a wide variety of users in different settings and with different applications?

With this objective: to use the microbial communities and microbial data, literature, and the research materials themselves as a test case, the Board on Research Data and Information held an International Symposium on Designing the Microbial Research Commons at the National Academy of Sciences in Washington, DC on 8-9 October 2009. The symposium addressed topics such as models to lower the transaction costs and support access to and use of microbiological materials and digital resources from the perspective of publicly funded research, public-private interactions, and developing country concerns. The overall goal of the symposium was to stimulate more research and implementation of improved legal and institutional models for publicly funded research in microbiology.

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.

Digital technologies and networks are now part of everyday work in the sciences, and have enhanced access to and use of scientific data, information, and literature significantly. They offer the promise of accelerating the discovery and communication of knowledge, both within the scientific community and in the broader society, as scientific data and information are made openly available online. The focus of this project was on computer-mediated or computational scientific knowledge discovery, taken broadly as any research processes enabled by digital computing technologies. Such technologies may include data mining, information retrieval and extraction, artificial intelligence, distributed grid computing, and others. These technological capabilities support computer-mediated knowledge discovery, which some believe is a new paradigm in the conduct of research. The emphasis was primarily on digitally networked data, rather than on the scientific, technical, and medical literature. The meeting also focused mostly on the advantages of knowledge discovery in open networked environments, although some of the disadvantages were raised as well.

The workshop brought together a set of stakeholders in this area for intensive and structured discussions. The purpose was not to make a final declaration about the directions that should be taken, but to further the examination of trends in computational knowledge discovery in the open networked environments, based on the following questions and tasks:

1. Opportunities and Benefits: What are the opportunities over the next 5 to 10 years associated with the use of computer-mediated scientific knowledge discovery across disciplines in the open online environment? What are the potential benefits to science and society of such techniques?2. Techniques and Methods for Development and Study of Computer-mediated Scientific Knowledge Discovery: What are the techniques and methods used in government, academia, and industry to study and understand these processes, the validity and reliability of their results, and their impact inside and outside science?3. Barriers: What are the major scientific, technological, institutional, sociological, and policy barriers to computer-mediated scientific knowledge discovery in the open online environment within the scientific community? What needs to be known and studied about each of these barriers to help achieve the opportunities for interdisciplinary science and complex problem solving?4. Range of Options: Based on the results obtained in response to items 1-3, define a range of options that can be used by the sponsors of the project, as well as other similar organizations, to obtain and promote a better understanding of the computer-mediated scientific knowledge discovery processes and mechanisms for openly available data and information online across the scientific domains. The objective of defining these options is to improve the activities of the sponsors (and other similar organizations) and the activities of researchers that they fund externally in this emerging research area.

The Future of Scientific Knowledge Discovery in Open Networked Environments: Summary of a Workshop summarizes the responses to these questions and tasks at hand.

The massive increase in digital information in the last decade has created new requirements for institutional and technological structures and workforce skills. Preparing the Workforce for Digital Curation focuses on education and training needs to meet the demands for access to and meaningful use of digital information, now and in the future. This study identifies the various practices and spectrum of skill sets that comprise digital curation, looking in particular at human versus automated tasks. Additionally, the report examines the possible career path demands and options for professionals working in digital curation activities, and analyzes the economic benefits and societal importance of digital curation for competitiveness, innovation, and scientific advancement. Preparing the Workforce for Digital Curation considers the evolving roles and models of digital curation functions in research organizations, and their effects on employment opportunities and requirements. The recommendations of this report will help to advance digital curation and meet the demand for a trained workforce.

The theme of this international symposium is the promotion of greater sharing of scientific data for the benefit of research and broader development, particularly in the developing world. This is an extraordinarily important topic. Indeed, I have devoted much of my own career to matters related to the concept of openness. I had the opportunity to promote and help build the open courseware program at the Massachusetts Institute of Technology (MIT). This program has made the teaching materials for all 2,000 subjects taught at MIT available on the Web for anyone, anywhere, to use anytime at no cost. In countries where basic broadband was not available, we shipped it in on hard drives and compact disks. Its impact has been worldwide, but it has surely had the greatest impact on the developing world. I am also a trustee of a nonprofit organization named Ithaca that operates Journal Storage (JSTOR) and other entities that make scholarly information available at very low cost.

The culture of science has been international and open for centuries. Indeed, the scientific enterprise can only work when all information is open and accessible, because science works through critical analysis and replication of results. In recent years, as some scientific data, and especially technological data, have increased in economic value frequently has caused us to be far less open with information than business and free enterprise require us to be. Indeed, the worldwide shift to what is known as open innovation is strengthening every day.

Finally, since the end of World War II, the realities of modern military conflict and now terrorism have led governments to restrict information through classification. This is important, but I believe that we classify far too much information. The last thing we need today, at the beginning of the twenty-first century, is further arbitrary limitations on the free flow of scientific information, whether by policies established by governments and businesses, or by lack of information infrastructure. For all these reasons, the international sharing of scientific data is one of the topics of great interest here at the National Academies and has been the subject of many of our past reports. This is the primary reason why this symposium has been co-organized by the NRC''s Policy and Global Affairs Division—the Board on International Scientific Organizations (BISO) and the Board on Research Data and Information (BRDI). The Case for International Sharing of Scientific Data: A Focus on Developing Countries: Proceedings of a Symposium summarizes the symposium.

Openness and sharing of information are fundamental to the progress of science and to the effective functioning of the research enterprise. The advent of scientific journals in the 17th century helped power the Scientific Revolution by allowing researchers to communicate across time and space, using the technologies of that era to generate reliable knowledge more quickly and efficiently. Harnessing today''s stunning, ongoing advances in information technologies, the global research enterprise and its stakeholders are moving toward a new open science ecosystem. Open science aims to ensure the free availability and usability of scholarly publications, the data that result from scholarly research, and the methodologies, including code or algorithms, that were used to generate those data.

Open Science by Design is aimed at overcoming barriers and moving toward open science as the default approach across the research enterprise. This report explores specific examples of open science and discusses a range of challenges, focusing on stakeholder perspectives. It is meant to provide guidance to the research enterprise and its stakeholders as they build strategies for achieving open science and take the next steps.

Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them.

Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use.

Biomedical research data sets are becoming larger and more complex, and computing capabilities are expanding to enable transformative scientific results. The National Institutes of Health''s (NIH''s) National Library of Medicine (NLM) has the unique role of ensuring that biomedical research data are findable, accessible, interoperable, and reusable in an ethical manner. Tools that forecast the costs of long-term data preservation could be useful as the cost to curate and manage these data in meaningful ways continues to increase, as could stewardship to assess and maintain data that have future value.

The National Academies of Sciences, Engineering, and Medicine convened a workshop on July 11-12, 2019 to gather insight and information in order to develop and demonstrate a framework for forecasting long-term costs for preserving, archiving, and accessing biomedical data. Presenters and attendees discussed tools and practices that NLM could use to help researchers and funders better integrate risk management practices and considerations into data preservation, archiving, and accessing decisions; methods to encourage NIH-funded researchers to consider, update, and track lifetime data; and burdens on the academic researchers and industry staff to implement these tools, methods, and practices. This publication summarizes the presentations and discussion of the workshop.

The needs and demands placed on science to address a range of urgent problems are growing. The world is faced with complex, interrelated challenges in which the way forward lies hidden or dispersed across disciplines and organizations. For centuries, scientific research has progressed through iteration of a workflow built on experimentation or observation and analysis of the resulting data. While computers and automation technologies have played a central role in research workflows for decades to acquire, process, and analyze data, these same computing and automation technologies can now also control the acquisition of data, for example, through the design of new experiments or decision making about new observations.

The term automated research workflow (ARW) describes scientific research processes that are emerging across a variety of disciplines and fields. ARWs integrate computation, laboratory automation, and tools from artificial intelligence in the performance of tasks that make up the research process, such as designing experiments, observations, and simulations; collecting and analyzing data; and learning from the results to inform further experiments, observations, and simulations. The common goal of researchers implementing ARWs is to accelerate scientific knowledge generation, potentially by orders of magnitude, while achieving greater control and reproducibility in the scientific process.

Automated Research Workflows for Accelerated Discovery: Closing the Knowledge Discovery Loop examines current efforts to develop advanced and automated workflows to accelerate research progress, including wider use of artificial intelligence. This report identifies research needs and priorities in the use of advanced and automated workflows for scientific research. Automated Research Workflows for Accelerated Discovery is intended to create awareness, momentum, and synergies to realize the potential of ARWs in scholarly discovery.