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1) University of Michigan news release: $38M NSF data infrastructure initiative will improve access to social and behavioral research https://news.umich.edu/38m-nsf-data-infrastructure-initiative-will-improve-access-to-social-and-behavioral-research/
 
The University of Michigan Institute for Social Research will oversee a $38 million investment from the National Science Foundation to create a new data platform that will help researchers across the gamut of scientific disciplines access, collect, store and secure vital information.

Data-intensive scientific research on human behavior and society can help improve community resilience to natural disasters, avoid supply chain disruptions and accurately predict infectious disease outbreaks, and more. However, researchers in many disciplines have faced obstacles like incompatible data standards, missing or error-filled information and technical difficulties in managing large data sets.

“Imagine a researcher attempting to understand economic growth in small towns and why some towns prosper while others don’t. This project makes such transformative work possible by standardizing and organizing complex data from hundreds of different sources, so it can be analyzed and understood in new ways,” said economist and project leader Margaret Levenstein, director of the Inter-university Consortium for Political and Social Research at ISR.

The $38 million commitment, developed and funded by the NSF, will establish the Research Data Ecosystem: A National Resource for Reproducible, Robust, and Transparent Social Science Research in the 21st Century. . . .
 
2) NSF announcement https://www.nsf.gov/news/special_reports/announcements/020422.jsp

3) NSF grant abstract: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1946932&HistoricalAwards=false

This project will implement a new platform for social and behavioral science data. Diverse types of data enable path-breaking analyses into human behavior but also present challenges of scale, sensitivity, and structure. Current barriers to conducting research include multiple incompatible standards for data, lack of interoperability, and the inherent difficulty of managing big data. There is an urgent need for new modes of access, confidentiality protection, methodological approaches, and tools so that research using a variety of data types meets accepted scientific standards. The Research Data Ecosystem (RDE) will modernize the management of data to enable a new era of interconnected research for the social and behavioral sciences. The platform will improve the quality of data-driven social and behavioral science research over the entire data life cycle. RDE will enable researchers across disciplines to conduct their work more efficiently and to create, organize, archive, access, and analyze data in ways that they cannot with existing infrastructure. RDE will make social and behavioral data more usable outside of academia by making it more findable and accessible. The project will provide training opportunities for graduate and undergraduate students and will broaden and diversify participation in the social and behavioral sciences by removing technical bottlenecks to research. This project is supported by the Foundation-wide Mid-scale Research Infrastructure program.

This project will develop an integrated suite of software to advance research in the social and behavioral sciences. RDE will enable: 1) Interoperability: An integrated system for the entire research data lifecycle, so that work done early in the data lifecycle is useful at later stages, making it possible to integrate data from different sources, 2) Reproducibility: Making it easier to reproduce and build on prior research results by being able to find and re-use data and code, 3) Transparency: Providing information about provenance, including source, code, method of collection, etc. for research data, 4) Increased Efficiency of Data Sharing: Reducing burden on data producers in sharing data and ensuring that shared data are FAIR (Findable, Accessible, Interoperable, Reusable), and 5) Confidentiality Protection: Protecting confidentiality while increasing research access. To achieve these goals, the project will develop the Research Data Description Framework, a metadata specification similar to the Resource Description Framework, for describing different research data lifecycle events. RDE will include stand-alone functional components for each stage of the research lifecycle that will be interoperable with one another and with key existing research infrastructure. The platform will support social and behavioral science researchers using traditional (e.g., survey and experimental) and novel (e.g., digital trace, imaging) types of data over the entire research lifecycle, from data collection to analysis to sharing to re-discovery and re-analysis. This infrastructure will improve the quality, integrity, and safety of data while increasing accessibility to data and collaboration between users across all social science and some behavioral science disciplines.
  
4) ICPSR: ISR Partners with NSF to Build a Research Data Ecosystem https://www.icpsr.umich.edu/web/about/cms/3760
 
With their data, researchers are enriching Americans’  lives — improving community resilience to natural disasters, avoiding supply chain disruptions, predicting infectious disease outbreaks, and more. However, researchers in many disciplines have faced obstacles like incompatible data standards, missing or error-filled information, and technical difficulties in managing large data sets.

To help address a wide range of challenges and create opportunities, the National Science Foundation is investing in the creation of a new data platform that will help researchers across the gamut of scientific disciplines access, collect, store, and secure vital information. The $38 million commitment will establish the Research Data Ecosystem (RDE) , which will be managed at the University of Michigan Institute for Social Research.

RDE will accelerate the advancement and impacts of social and behavioral research. Here are five things to know about this groundbreaking infrastructure initiative.

1. What is the Research Data Ecosystem?
RDE is a national resource for reproducible, robust, and transparent social science research in the 21st Century. This NSF initiative will enable transformative research in fields that leverage complex scientific data about human behavior, society, and the economy. "The Research Data Ecosystem project will modernize the management and use of many types of people-centered data, thus accelerating multidisciplinary research focused on serving society and improving the lives of people all over the country," said acting NSF Assistant Director for Social, Behavioral and Economic Sciences Kellina Craig-Henderson.

2. What is the end goal for this project?
The University of Michigan Institute for Social Research will oversee the modernization of the ICPSR software platform and the creation of new data archives researchers can use to access, organize, analyze and contribute different types of research data. This work will emphasize the researcher user experience to expand and democratize access to different types of research data, such as video and geospatial data as well as administrative and other “digital trace” data. It will provide a state-of-the-art platform for researchers and their funders who want to share and link their data in safe and secure ways.  

3. How is this different from the other resources at the University of Michigan Institute for Social Research?
While historically the projects at ICPSR, the data archival arm of ISR, have been about curating, preserving, and sharing data, the Research Data Ecosystem project is about building infrastructure to support all of these processes for multiple types of data. It does not focus on any particular dataset.

4. How will this affect researchers and their work?
The RDE project tackles the urgent need for new modes of access, confidentiality protection, methodology, and tools that enable research using a wide variety of data types. Scientists across the U.S. conducting people-centered data-intensive research will have the ability to securely access and contribute to the data archives. Economist and project leader Margaret Levenstein puts it this way: “Imagine a researcher attempting to understand economic growth in small towns and why some towns prosper while others don’t. This project makes such transformative work possible by standardizing and organizing complex data from hundreds of different sources, so it can be analyzed and understood in new ways,” said Levenstein, director of ICPSR.

5. Why ISR, and why now?
The Research Data Ecosystem project will modernize data collection and management to maximize the scientific value of people-centered data, enabling efficient and innovative multidisciplinary research focused on serving society and improving the lives of people in the U.S. “We’re excited about the numerous ways that the Research Data Ecosystem will engage current and future scholars,” said Kate Cagney, director of ISR. “ISR’s long history of innovation in data collection and analysis makes us uniquely positioned to build this platform to support and enhance social scientific inquiry.”  
 
5) ICPSR Research Data Ecosystem webpage: https://www.icpsr.umich.edu/web/pages/about/rde/index.html
 
The Research Data Ecosystem will make research data accessible to broaden participation in the frontiers of scientific research. It will accomplish this goal by modernizing the existing software platform so that it supports the entire research lifecycle with an enhanced user experience to increase the ability of researchers to safely and securely access, connect, store, and manipulate data.
 
Tools under Construction:
StatSnap Online -- Online statistical analysis tool to securely analyze data
Research Document Registry Tool -- Tool to help create research plan pre-registration, data management plans, consent statements, and data use agreements
TurboCurator -- A data input preparation application that combines the best aspects of software and human curation
Cobre -- Cloud-based platforms for analyzing large, complex, public and private data
Researcher Passport -- Portable digital user credential for accessing restricted data
Video Archive -- Repository and analysis tools for social science video data
SunGEO -- Repository and tools to support subnational political, economic, and social geospatial data

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