Data Managment and Sharing
Investigators are expected to adhere to the agency instructions and align their data management and sharing (DMS) plan with stated application guidelines. Additionally, investigators are advised to carefully examine notices of award and award terms and conditions for any project-specific requirements that may be applicable to each funded project.
Guidelines on Data Management and Sharing
Data Management and Sharing Resources
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Guidance and Policies
|NIH Data Management and Sharing Policy Overview
|Learn what is expected of investigators and institutions under the 2023 NIH Data Management and Sharing Policy.
|NIH Budgeting for Data Management and Sharing
|NIH guidelines on what data sharing related costs may be requested in an application for funding. Allowable funds, justifying costs, and related forms.
|HEAL Public Access and Data Sharing
|Through the NIH HEAL Initiative Public Access and Data Sharing Policy, NIH seeks to create an infrastructure that addresses the need for researchers, clinicians, and patients to collaborate on sharing their collective data and knowledge about opioid misuse and pain to provide scientific solutions to the opioid crisis.
|NSF Open Knowledge Network (OKN) Roadmap Report
|This report introduces the OKN concept, and prior initiatives related to that effort. The report covers essential characteristics of the OKN, governance structure, data sources and systems, amd procedures and metrics for data validation. It has various use cases and discusses long term outlook for the topic.
|Research Data Management and Sharing (UChicago Library)
|This guide addresses good practices for research data management and sharing.
|Transformative Agreements (UChicago Library)
|The University of Chicago Library has entered into transformative agreements (also known as Read and Publish agreements), which enable UChicago faculty, students, and staff to publish their research as open access (OA) without the need to pay an article processing charge (APC). Unless otherwise stated, all OA articles covered by these agreements will be published with a Creative Commons Attribution (CC-BY) license.
Data Management and Sharing Plan Templates and Platforms
|Open Science Framework (OSF)
|OSF is a data management platform that promotes open, centralized workflows by enabling capture of different aspects and products of the research lifecycle, including developing a research idea, designing a study, storing and analyzing collected data, and writing and publishing reports or papers.
|A cloud-based platform for software development and version control, allowing researchers to store and manage their code. In addition to version control, GitHub can be used for team management, file sharing, project management, application integration, host discussions, and more. UChicago GitHub Enterprise FAQ
|Provides free web-based templates to construct data management plans. It has templates, funder mandates, institutional requirements, and other instructional material.
|NIH DMS Plan Template
|The template addresses six NIH-recommended core elements that needs to be included in the DMS plan.
|Writing a Data Management & Sharing Plan from NIH
|Guidelines and checklist of elements that has to be included in the NIH data management and sharing plan. It also covers info about the format of the document.
|National Institutes of Health (NIH) data repositories
|This is a list of several NIH data repositories. Many of the NIH institutes, centers, and research programs have instituted specific data sharing policies and repositories and this list links to different repositories available for specific NIH programs.
|National Science Foundation Public Access Repository (NSF-PAR)
|This repository contains an initial collection of journal publications and the final accepted version of the peer-reviewed manuscript or the version of record. When clicking on a Digital Object Identifier number, you will be taken to an external site maintained by the publisher.
|Department of Energy (DOE) Data Explorer (DDE)
|A search tool for finding DOE-funded, publicly available, scientific data records submitted by data centers, repositories, and other organizations funded by the Department.
|Department of Energy (DOE) Public Reusable Research (PuRe)
|The Office of Science (SC) Public Reusable Research (PuRe) Data Resources are data repositories, knowledge bases, analysis platforms, and other activities that make data publicly available to enable better communication, better stewardship, and better science.
University of Chicago Resources
|Knowledge@UChicago is a service managed in the Library to preserve and share the scholarly and creative assets of the University. The institutional repository is supported through a collaboration between the Library and IT Services at the University of Chicago. Content included in Knowledge@UChicago includes (but is not limited to): publications (including preprints), dissertations and theses, white papers and technical reports, and research data sets. Learn more here.
|Research Computing Center (RCC)
|RCC provides a wide range of free resources for University of Chicago researchers including:
High-Performance Computing – Midway, a professionally-managed high performance computing cluster, forms the core of RCC’s advanced computational infrastructure. More info here.
Storage and Backup – RCC hosts and maintains a number of storage systems. Users have access to both persistent high-capacity storage that can be shared among a research group or remain private to each individual user and to high-performance storage when data needs to be temporarily staged and accessed quickly. More info here.
Secure Research Environment – RCC MidwayR is a restricted secure computing environment for the storing and analyzing of sensitive research data at the UChicago. More info here.
Visualization – RCC Visualization Lab creates compelling visual narratives out of scientific, humanistic, and social scientific data. These narratives enable insights that further scholarship, and they support research dissemination within both professional and lay audiences. More info here.