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From page 1...
... Computation and automation of data acquisition allow automated systems to analyze data and extract knowledge, to create predictive models, and to use those models to guide the acquisition of additional data, closing and automating the loop in a typical research workflow. The committee uses the term automated research workflow (ARW)
From page 2...
... Fully realized ARWs are not common at present, and so the study examines how and where progress is being made in areas such as advanced computation, use of workflow management systems, laboratory automation, and the use of AI both as a workflow component as well as in directing the "outer loop" of the research process. This report constitutes an initial effort to create awareness, momentum, and synergies to help realize the potential of ARWs in scientific discovery.
From page 3...
... . • In climate science, the generation of high-resolution local simulations to inform lower-resolution global climate models about important small scale processes can be automated, closing the loop of generating compu tational experiments and informing a global model with them (Schneider et al., 2017a)
From page 4...
... These include the use of scientific workflow engines, software that provides a formalization of the computational analysis pipeline, as well as platforms to facilitate data flows and data management pipelines (ODSC Community, 2021)
From page 5...
... • ARWs should facilitate the effective use of artificial intelligence (AI) and machine learning (ML)
From page 6...
... . FINDING C: RESEARCH ENTERPRISE Realizing the potential of automated research workflows (ARWs)
From page 7...
... . Priorities include • Funding support for efforts by research institutions and societies to link disciplines so they can share and benefit from the expertise in statistics, machine learning or data science, and engineering and computer science that is required to build and maintain sustainable infrastructure for ARWs.
From page 8...
... RECOMMENDATION 3: Human Resources Research funders, higher education, research institutions, and scientific and professional societies should support the development and implementation of educational programs and career pathways aimed at building the workforce needed to develop and utilize automated research workflows (ARWs) , including the creation of career tracks that support ARW capabilities.
From page 9...
... . RECOMMENDATION 4: Culture and Incentives Research funders, research institutions, and disciplines should work to create an automated research workflow (ARW)
From page 10...
... FINDING D: LEGAL AND POLICY ISSUES In addition to barriers to progress that exist within the research process itself, there are legal and policy issues that affect implementation of automated research workflows in specific domains that will require international multistakeholder efforts to address. Data collected for use in ARWs will increasingly include data generated outside of a traditional research setting, such as personal health data collected from wearables and medical visits or behavioral data collected online from social media.
From page 11...
... . RECOMMENDATION 5: Preserving Privacy Research enterprise funders, performers, publishers, and beneficiaries should work with governments, data privacy experts, and other entities to address the legal, policy, and associated technical barriers to implementing automated research workflows in specific domains.
From page 13...
... 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 committee uses the term automated research workflows (ARWs)
From page 14...
... Artificial intelligence (AI) and machine learning (ML)
From page 15...
... Based on insights from the workshop, a review of the literature, and other inputs, the committee will produce a consensus report that identifies research needs and priorities in the use of advanced and automated workflows for scientific research. mechanism, a 2-day virtual workshop, "Opportunities for Accelerating Scientific Discovery: Realizing the Potential of Advanced and Automated Workflows," was held March 16–17, 2020.
From page 16...
... Another topic that emerged at the March 2020 workshop and in recent literature is the role of scientific workflow engines as important enablers of effective development and implementation of ARWs. The committee recognizes this technology as critical for advancing the utilization of ARWs, and we refer to various tools and resources throughout this report.
From page 17...
... INTRODUCTION 17 Chapter 3 provides case studies of workflows across disciplines in the sciences and humanities; they are based on March 2020 workshop presentations, a review of the literature, and the committee's own experience. Chapter 4 looks at crosscutting issues across disciplines that ARWs can help with relative to research integrity, reproducibility and replicability, and dissemination.


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