“Open access to shared information is essential for the development and evolution of artificial intelligence (AI) and AI-powered solutions needed to address the complex challenges facing the nation and the world. The Open Knowledge Network (OKN), an interconnected network of knowledge graphs, would provide an essential public-data infrastructure for enabling an AI-driven future. It would facilitate the integration of diverse data needed to develop solutions to drive continued strong economic growth, expand opportunities, and address complex problems from climate change to social equity. The OKN Roadmap describes the key characteristics of the OKN and essential considerations in taking the effort forward in an effective and sustainable manner….”

NSF releases Open Knowledge Network Roadmap report

“The U.S. National Science Foundation today published the Open Knowledge Network Roadmap – Powering the next data revolution report that outlines a strategy for establishing an open and accessible national resource to power 21st century data science and next-generation artificial intelligence. Establishing such a knowledge infrastructure would integrate the diverse data needed to sustain strong economic growth, expand opportunities to engage in data analysis, and address complex national challenges such as climate change, misinformation, disruptions from pandemics, economic equity and diversity….”

ARL Applauds NSF Open Science Investment – Association of Research Libraries

“The Association of Research Libraries (ARL) commends the ongoing commitment of the US National Science Foundation (NSF) to open science. NSF today announced awards for 10 new projects focused on building and enhancing coordination among researchers and other stakeholders to advance FAIR (findable, accessible, interoperable, reusable) data principles and open-science practices.

The inaugural awards in NSF’s Findable, Accessible, Interoperable, Reusable, Open Science Research Coordination Networks (FAIROS RCN) program represent a pooled investment of over $12.5 million in open science from all directorates comprising NSF. This program is particularly unique given that the 10 projects are composed of 28 distinct NSF awards (detailed below) representing many organizations and institutions in the United States seeking to advance open-science efforts….”

NSF Grant for New STEM-focused Commons | Platypus – the Humanities Commons Blog

by Kathleen Fitzpatrick

The Commons team is delighted to have been awarded one of the inaugural FAIROS RCN grants from the NSF, in order to establish DBER+ Commons. That’s a big pile of acronyms, so here’s a breakdown: the NSF is of course the National Science Foundation, one of the most important federal funding bodies in the United States, and a new funder for us. The FAIROS RCN grant program was launched this year by the NSF in order to invest in Findable, Accessible, Interoperable, Reusable Open Science (FAIROS) by supporting the formation and development of Research Coordination Networks (RCN) dedicated to those principles.

We have teamed up with a group of amazing folks at Michigan State University who are working across science, technology, engineering, math, and more traditional NSF fields, all of whom are focused on discipline-based education research (DBER) as well as other engaged education research methodologies (the +). Our goal for this project is to bring them together with their national and international collaborators in STEM education to create DBER+ Commons, which will use — and crucially, expand — the affordances of the HCommons network and promote FAIR and CARE (Collective Benefit, Authority to control, Responsibility, Ethics) practices, principles, and guidelines in undergraduate, postbaccalaureate, graduate, and postdoctoral science education research activities.


ARL and Six Universities Awarded National Science Foundation Grant to Study Discipline-Specific Models and Costs for Public Access to Research Data – Association of Research Libraries

“The US National Science Foundation (NSF) has awarded the Association of Research Libraries (ARL) and six universities involved in the Data Curation Network a $297,019 grant to conduct research, develop models, and collect costing information for public access to research data across five disciplinary areas. The project, Completing the Life Cycle: Developing Evidence-Based Models of Research Data Sharing, will start in August 2021….

This research seeks to answer the following questions:

Where are funded researchers across these institutions making their data publicly accessible and what is the quality of the metadata?
How are researchers making decisions about why and how to share research data?
What is the cost to the institution to implement the federally mandated public access to research data policy? …”

ARL Welcomes Researcher-First Policies in Bills to Reauthorize US National Science Foundation – Association of Research Libraries

“On behalf of the leaders of 125 major research libraries, the Association of Research Libraries (ARL) is pleased to see that the US House of Representatives included the following policies in the National Science Foundation (NSF) for the Future Act (H.R. 2225), which center researchers and create public value by promoting the availability of publicly funded research:

Criteria for trusted open repositories to be used by federally funded researchers sharing data, software, and code. According to the House bill, the criteria would be developed with input from the scientific community. Research libraries look forward to partnering with NSF and the scientific community to develop these criteria.
Data management plans to facilitate public access to NSF-funded research products, including data, software, and code….

We strongly support public access to publications resulting from NSF-funded research with zero embargo, and we are heartened to see language in the Senate-passed US Innovation and Competition Act (S. 1260) requiring the publication of federally funded research data within 12 months, “preferably sooner.” Making research outputs publicly available to the widest possible audience in the timeliest manner possible, and machine-accessible for computation, is critical for developing scientific insights and solutions for public health, climate, technological advancement, and more….”

Leveraging Data Communities to Advance Open Science | Ithaka S+R

“We are excited to announce that Ithaka S+R has been awarded grant funding from the National Science Foundation to support the development of infrastructures for data sharing within data communities in collaboration with the Data Curation Network.  “Leveraging Data Communities to Advance Open Science,” will bring together scientists and information technology professionals for focused discussions about initiating and sustaining data communities….”

Assessment, Usability, and Sociocultural Impacts of DataONE | International Journal of Digital Curation

Abstract:  DataONE, funded from 2009-2019 by the U.S. National Science Foundation, is an early example of a large-scale project that built both a cyberinfrastructure and culture of data discovery, sharing, and reuse. DataONE used a Working Group model, where a diverse group of participants collaborated on targeted research and development activities to achieve broader project goals. This article summarizes the work carried out by two of DataONE’s working groups: Usability & Assessment (2009-2019) and Sociocultural Issues (2009-2014). The activities of these working groups provide a unique longitudinal look at how scientists, librarians, and other key stakeholders engaged in convergence research to identify and analyze practices around research data management through the development of boundary objects, an iterative assessment program, and reflection. Members of the working groups disseminated their findings widely in papers, presentations, and datasets, reaching international audiences through publications in 25 different journals and presentations to over 5,000 people at interdisciplinary venues. The working groups helped inform the DataONE cyberinfrastructure and influenced the evolving data management landscape. By studying working groups over time, the paper also presents lessons learned about the working group model for global large-scale projects that bring together participants from multiple disciplines and communities in convergence research.


COVID-19 Global Research Registry for Public Health and Social Sciences

“Sharing your information will help:

Highlight novel public health and social science research initiated in response to COVID-19
Expand opportunities for research collaboration and reduce duplication of effort
Identify unmet research needs
Create possibilities to share and publish research instruments, data collection and ethics protocols, and data
Set a comprehensive social science research agenda….”

Center for Advancement and Synthesis of Open Environmental Data and Sciences (nsf21549) | NSF – National Science Foundation

“NSF seeks to establish a Center fueled by open and freely available biological and other environmental data to catalyze novel scientific questions in environmental biology through the use of data-intensive approaches, team science and research networks, and training in the accession, management, analysis, visualization, and synthesis of large data sets. The Center will provide vision for speeding discovery through the increased use of large, publicly accessible datasets to address biological research questions through collaborations with scientists in other related disciplines. The Center will be an exemplar in open science and team science, fostering development of generalizable cyberinfrastructure solutions and community-driven standards for software, data, and metadata that support open and team science, and role-modeling best practices. Open biological and other environmental data are produced by NSF investments in research and infrastructure such as the National Ecological Observatory Network (NEON), the Ocean Observatories Initiative (OOI), the Long-Term Ecological Research (LTER) network, National Center for Atmospheric Research (NCAR), Critical Zone Observatories (CZOs), Integrated Digitized Biocollections (iDigBio), and the Global Biodiversity Information Facility (GBIF), as well as by many other public and private initiatives in the U.S. and worldwide. These efforts afford opportunities for collaborative investigation into, and predictive understanding of life on Earth to a far greater degree than ever before. The Center will help develop the teams, concepts, resources, and expertise to enable inclusive, effective, and coordinated efforts to answer the broad scientific questions for which these open data were designed, as well as key questions that emerge at interfaces between biology, informatics, and a breadth of environmental sciences. It will engage scientists diverse in their demography, disciplinary expertise, and geography, and in the institutions that they represent in collaborative, cross-disciplinary, and synthetic studies. It is expected that this new Center will build on decades of experience from NSF’s prior investments in other synthesis centers, while providing visionary leadership and advancement for data-intensive team science in a highly connected and increasingly virtual world. It will serve as an incubator for team-based, data-driven, and open research that includes cyberinfrastructure, tools, services, and application development and innovative and inclusive training programs. The Center is also expected to spur collaborative interactions among the facilities and initiatives that produce open biological and other environmental data, and cyberinfrastructure efforts that support the curation and use of those data, such as Biological and Chemical Oceanography Data Management Office (BCO-DMO), CyVerse, Environmental Data Initiative (EDI), DataOne, EarthCube, and Cyberinfrastructure (CI) Centers for Excellence, to address compelling research questions and to enable training and data product and tool development. The new Center will further enable data-driven discovery through immersive education and training experiences to provide the advanced skills needed to maximize the scientific potential of large volumes of available open data.”

OSF | Center for Open Science – NSF 21-511 AccelNet-Implementation-Community of Open Science Grassroots Networks (COSGN).pdf

“Overview. The Community of Open Scholarship Grassroots Networks (COSGN), includes 107 grassroots networks representing virtually every region of the world and every research discipline These networks communicate and coordinate on topics of common interest. We propose, using an NSF 21-515 Implomentation grant, to formalize governance and coordination of the networks to maximize impact and establish standard practices for sustainability. In the project poriod, we will increase the capacity of COSGN to advance the research and community goals of the participating networks individually and collectively, and establish governance, succession planning, shared resources and communication pathways to ensure an active community sustained network of networks By the end of the project poriod, we will have established a self-sustaining notwork of networks that leverages disciplinary and regional diversity actively collaborates across networks for grassroots organizing, and shares resources for manum impact on culture change for open scholarship.”

Harnessing the Data Revolution (HDR): Institutes for Data-Intensive Research in Science and Engineering (nsf21519) | NSF – National Science Foundation

“In 2016, the National Science Foundation (NSF) unveiled a set of “Big Ideas,” 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (see The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering by bringing together diverse disciplinary perspectives to support convergent research. When responding to this solicitation, even though proposals must be submitted through the Office of Advanced Cyberinfrastructure (OAC) within the Directorate for Computer and Information Science and Engineering (CISE), once received the proposals will be managed by a cross-disciplinary team of NSF Program Directors.

NSF’s Harnessing the Data Revolution (HDR) Big Idea is a national-scale activity to enable new modes of data-driven discovery that will allow fundamental questions to be asked and answered at the frontiers of science and engineering.

This solicitation will establish a group of HDR Institutes for data-intensive research in science and engineering that can accelerate discovery and innovation in a broad array of research domains. The HDR Institutes will lead innovation by harnessing diverse data sources and developing and applying new methodologies, technologies, and infrastructure for data management and analysis. The HDR Institutes will support convergence between science and engineering research communities as well as expertise in data science foundations, systems, applications, and cyberinfrastructure. In addition, the HDR Institutes will enable breakthroughs in science and engineering through collaborative, co-designed programs to formulate innovative data-intensive approaches to address critical national challenges….”

New Report Provides Recommendations for Effective Data Practices Based on National Science Foundation Research Enterprise Convening – Association of Research Libraries

“Today a group of research library and higher education leadership associations released Implementing Effective Data Practices: Stakeholder Recommendations for Collaborative Research Support. In this new report, experts from library, research, and scientific communities provide key recommendations for effective data practices to support a more open research ecosystem. In December 2019, an invitational conference was convened by the Association of Research Libraries (ARL), the California Digital Library (CDL), the Association of American Universities (AAU), and the Association of Public and Land-grant Universities (APLU). The conference was sponsored by the US National Science Foundation (NSF).

The conference focused on designing guidelines for (1) using persistent identifiers (PIDs) for data sets, and (2) creating machine-readable data management plans (DMPs), two data practices that were recommended by NSF. Professor Joel Cutcher-Gershenfeld, of Heller School for Social Policy and Management at Brandeis University, designed and facilitated the convening with the project team….”